AI Algorithms and the Future of Global Diplomacy

20 Feb 2026 11:00h - 12:00h

AI Algorithms and the Future of Global Diplomacy

Session at a glanceSummary, keypoints, and speakers overview

Summary

The panel examined how artificial intelligence is being integrated into diplomatic work, focusing on its practical use within the German Federal Foreign Office and its broader geopolitical implications. Raphael Leuner explained that the German government launched data labs across all federal ministries in 2021, creating sixteen labs including one in the Foreign Office, where he works as a data scientist [12-15]. He emphasized that being embedded in the ministry allows rapid co-creation of AI tools with short feedback loops, which is essential for a fast-moving field that cannot rely on traditional two-year IT projects [18-21][22-24].


The participants agreed that AI is not a new technology but a new tactical layer in international relations, echoing historical shifts such as the industrial, nuclear, and space revolutions [36-41]. Shahani Yaktiyami highlighted that middle powers like Germany and India can leverage AI by focusing on regulatory influence and sector-specific applications rather than competing for frontier model leadership, which is dominated by the United States and China [48-51]. Norman Schulz warned that without international cooperation AI poses risks comparable to nuclear technology and called for a future US-China dialogue to establish safety regulations [66-78].


He also described Germany’s role in negotiating the UN Global Digital Compact and the creation of an Independent Scientific International Panel on AI to ensure inclusive, science-based governance [166-176][179-184]. Shyam Krishnakumar pointed out that India, while not yet building large-scale frontier models, excels in contextual innovation, large-scale inference at low cost, and a skilled workforce, making it a strong partner for application-driven AI projects [92-102][104-110]. He suggested concrete Indo-German cooperation in industrial AI and healthcare, where Germany contributes automation expertise and data, and India provides model development and extensive surgical data [108-119].


Raphael Leuner added that the Foreign Office deliberately adopts open-source AI, reusing existing applications and developing negotiation-support tools, while monitoring the growing influence of Chinese open-source models and encouraging Indian alternatives [128-136][137-138]. The panel stressed that AI should augment, not replace, diplomatic analysis; AI can accelerate document processing and free diplomats for strategic thinking, but final decisions remain human [250-259].


Regarding media narratives, Shahani warned that allowing AI to shape geopolitical stories risks bias and manipulation, advocating for human-led narrative framing and bias-detection tools [274-283]. Norman noted that AI can help detect bias but should not be used to generate repetitive news content, reinforcing the need for human creativity [287-292].


Overall, the discussion concluded that while AI presents both opportunities and challenges for diplomacy, middle-power collaboration, open-source development, and inclusive governance are essential to harness its benefits responsibly [202-214][170-176].


Keypoints


Major discussion points


AI implementation inside the German Foreign Office – The ministry created 16 data labs across federal ministries in 2021-2022, allowing data scientists like Raphael to work directly with diplomats and develop fast-co-created AI solutions, especially for tasks such as negotiating support and document analysis. The team deliberately relies on open-source models and re-uses existing applications to keep development agile. [12-15][18-23][127-133]


Geopolitical framing of AI as “technology diplomacy” – Panelists stressed that AI is the latest layer of a long-standing pattern where technology reshapes foreign policy (Industrial, nuclear, space revolutions). While great powers compete for frontier AI leadership, middle powers such as India and Germany can leverage their specific strengths-regulatory influence for Germany and application-driven deployment for India-to carve out a role on the AI value chain. [35-41][46-51][78-85][90-110]


Governance, security, and sovereignty concerns – There is a consensus that AI’s rapid diffusion creates risks (bias, weaponisation, dependence on foreign models). Participants called for international cooperation, regulation, and the development of indigenous or trusted AI (avoiding unchecked Chinese open-source models). The UN-led Global Digital Compact and its Independent Scientific International Panel on AI are highlighted as mechanisms to embed inclusive, values-aligned governance. [68-77][146-149][157-166][166-184]


Indo-German cooperation on applied AI – Both sides see concrete collaboration opportunities in sectoral AI (industrial automation, healthcare, robotics). India’s large talent pool and cost-effective model development complement Germany’s industrial data, automation expertise, and investment capacity. Joint open-source projects and shared use-case pilots are proposed as a way for middle powers to create “more than one-plus-one” value. [108-119][130-136][202-214]


AI’s impact on information narratives and media – While AI can accelerate data processing, panelists warned against letting algorithms dictate geopolitical narratives. Risks include amplification of biased or malicious content, especially when AI-generated fake sites are used for influence operations. Human oversight, bias-detection tools, and regulatory safeguards are deemed essential. [274-280][287-292][294-298]


Overall purpose / goal of the discussion


The panel aimed to explore how AI is being adopted as a practical tool within foreign ministries, to assess its broader geopolitical implications, and to identify pathways for responsible governance and collaborative action-particularly between middle powers like India and Germany-so that AI can be harnessed for diplomatic effectiveness while mitigating security and ethical risks.


Overall tone and its evolution


Opening (0:00-3:00): Informative and optimistic, highlighting the novelty of data labs and the speed advantages of internal AI development.


Mid-section (3:00-12:00): Shifts to a broader, more analytical tone, situating AI within historical technology-diplomacy and emphasizing strategic competition among great powers versus opportunities for middle powers.


Later segment (12:00-22:00): Becomes cautionary and policy-focused, stressing governance, sovereignty, and the need for international frameworks (global digital compact, AI panel).


Final part (22:00-38:00): Returns to a collaborative, solution-oriented tone, discussing concrete Indo-German projects, open-source initiatives, and the balance between AI’s benefits and its risks to narrative integrity.


Overall, the conversation moves from enthusiasm about AI’s potential, through a sober assessment of geopolitical and ethical challenges, to a constructive call for cooperative, values-aligned action.


Speakers

Raphael Leuner – Data Scientist at the German Federal Foreign Office; works on AI tools and data labs within the Foreign Office [S1].


Gunda Ehmke – Moderator/Host of the panel discussion [S2].


Norman Schulz – Consul at the Coordination Staff for AI and Digital Technologies, German Foreign Office; diplomat [S4].


Shyam Krishnakumar – Associate at the Pranav (Pranava) Institute; focuses on emerging technology, public policy, and society from an India-first perspective [S5][S6].


Shahani Yaktiyami – Dr., Senior Officer, Technology Program at the German Marshall Fund; specialist in technology diplomacy and AI policy [S1][S7].


Audience – Various audience members (e.g., Sreeni, a student at Ashoka University; Sanjeevni, a radio journalist in the UK) who asked questions during the session.


Additional speakers:


Jian – Mentioned in the transcript as a participant to be addressed by the moderator; no further role or title provided.


Full session reportComprehensive analysis and detailed insights

The panel opened with Gunda Ehmke introducing the participants – Raphael Leuner, a data scientist from the German Federal Foreign Office; Dr Shahani Yaktiyami, senior officer for technology programmes at the German Marshall Fund; and Norman Schulz, a consular officer responsible for AI and digital technologies at the Foreign Office – and set the agenda to explore AI both as a diplomatic tool and as a policy issue [1-4].


German data-lab model – Leuner explained that the 2021 government decision to create data labs in every federal ministry resulted in sixteen labs, one of which is embedded in the Foreign Office [12-15]. Being inside the ministry enables “very, very short contacts and short paths” to diplomats, allowing rapid co-creation of AI solutions that would be impossible with traditional two-year IT projects and large, costly teams [18-21]. The lab’s early work focused on breaking down data silos; since the rise of generative AI it has shifted to building AI tools for negotiations, notably analysing large document collections [16-18][22-24][140-150] (originally cited [130-133]). From the outset the team chose open-source technologies and to reuse existing state-government applications, a strategy intended to keep development agile and cost-effective [127-133][128-136]. Leuner noted the growing worldwide adoption of Chinese open-source models and expressed enthusiasm for Indian large-language-model alternatives, without linking this to Europe’s strategic concerns [134-138].


Geopolitical framing – Shahani placed AI within a long historical pattern in which new technologies reshape foreign policy – from the Industrial and nuclear revolutions to the space race – arguing that while the technology is new, the diplomatic tactics it enables are not [35-41][42-44]. She highlighted that the current “AI race” is dominated by the United States and China, but that middle powers can still exert influence: Germany through regulatory and rule-making power, and India through large-scale application and deployment [46-51][78-85]. Shahani’s view was echoed by Shyam Krishnakumar, who described India as a “digital powerhouse” with a vast talent pool capable of building context-specific models and performing cheap, large-scale inference, even though it does not yet develop frontier-scale models [90-102][104-110].


Regulation and global governance – Norman stressed that AI’s rapid diffusion creates security risks, and in his case also sovereignty risks linked to Chinese models [66-78]. He answered Gunda’s question on how the Foreign Office governs AI, stating “short answer would be no… we need stronger regulation and international cooperation” [70-73]. He compared the emerging AI threat to the nuclear era and called for a future US-China dialogue to set safety limits [66-78]. Schulz outlined Germany’s leadership in negotiating the UN Global Digital Compact and in establishing the Independent Scientific International Panel on AI, which will produce its first scientific report and feed into a follow-up global AI dialogue in July in Geneva alongside the ITU AI for Good summit [166-176][179-184]. Norman added that each country must factor its own security context – such as Germany’s concerns over Ukraine and India’s border disputes – into technology decisions, and noted that many corporations now appoint geopolitical-risk advisors [146-149][141-148].


Open-source versus domestic development – Leuner argued that using open-source AI, even when sourced from China, is a pragmatic way to accelerate deployment and advocated for Indian open-source alternatives to diversify the ecosystem [128-136][137-138]. Schulz counter-argued that the safest route to align AI with national values is to develop systems in-house [157-158] and later warned that Chinese models embed “Chinese ways of thinking” that could compromise sovereignty [157-158]. This tension reflects a broader disagreement on whether reliance on existing open-source models is acceptable or whether new, domestically-controlled models are required [Disagreements].


Middle-power cooperation – Norman referenced Canadian Prime Minister Mark Carney’s call for middle-power collaboration, reinforcing the idea that Germany and India can jointly shape the AI value chain [78-85]. Krishnakumar proposed concrete Indo-German projects: in industrial AI, Germany would contribute automation expertise and industrial data while India would supply model-building capacity; in healthcare AI, India would bring a massive surgical-data set and Germany would provide investment power [108-119][130-136]. Leuner reinforced this vision, stating that middle powers should co-develop non-frontier, open-source AI projects that can be readily adopted by a broad range of users [202-214].


Day-to-day impact on diplomatic work – In response to an audience question on automating foreign-policy research, Norman explained that AI will not replace decision-making but will speed up information consumption, freeing diplomats to focus on analysis, relationship-building and strategic thinking [250-259]. Leuner and Schulz agreed that AI can automate the labour-intensive task of processing large document troves, while final decisions remain human-led [130-133][211-212]. Both cautioned that AI should not replace the creative and innovative thinking diplomats bring to negotiations [159-164].


Risks of AI-shaped narratives – An audience query about AI-generated propaganda prompted Shahani, Norman and Leuner to warn that generative models are already being weaponised to amplify disinformation, create fake websites and shape geopolitical narratives [295-298]. Shahani advocated for bias-detection tools and human oversight; Norman echoed that AI can help detect bias but should not be used to generate repetitive news content; Leuner stressed the need to develop alternatives to Chinese models to safeguard against strategic dependence [277-280][284-286][288-292][294-298].


Points of contention – (1) No consensus on whether open-source models from strategic rivals should be used or whether wholly domestic development is required [Disagreements 1]; (2) Divergence on the novelty of AI-driven diplomatic tactics – Shahani sees continuity with past technologies, while Schulz disputes that claim [Disagreements 4]; (3) Varying emphasis on multilateral regulation versus rapid internal innovation [Disagreements 3].


Take-aways – (1) The German Foreign Office’s data-lab model demonstrates the value of fast, internal co-creation of AI tools for negotiation support and document analysis; (2) AI should be viewed as an augmenting tool that automates routine information processing while preserving human decision-making; (3) Middle powers can wield influence on the AI value chain through regulatory leadership (Germany) and application-driven deployment (India), especially via sector-specific collaborations in industrial and health AI; (4) Inclusive, science-based global governance – exemplified by the UN Global Digital Compact and the Independent Scientific International Panel on AI – is essential to manage security, sovereignty and bias risks, particularly given the proliferation of Chinese open-source models.


The panel committed to continue using open-source technologies, to pursue joint Indo-German pilots in industrial and health AI, and to support the Global Digital Compact and the upcoming UN AI dialogue in Geneva. Unresolved issues include the precise mechanisms for ensuring AI systems align with national values, the development and scaling of non-frontier open-source models, and the detailed governance structures for bilateral cooperation. A suggested “managed interdependence” approach would combine Germany’s regulatory expertise with India’s model-building capacity while jointly developing open-source alternatives to reduce reliance on any single external source [Key takeaways and suggested compromises].


Session transcriptComplete transcript of the session
Gunda Ehmke

Institute. Then we have Raphael Leuner, Data Scientist at the German Federal Foreign Office. We have Dr. Shahani Yaktiyami, Senior Officer, Technology Program at the German Marshall Fund. And we have Norman Schulz, Consulate at the Coordination Staff, AI and Digital Technologies at the German Foreign Office. And to kick off the conversation today, so we will cover both AI as a topic and as a tool, I would like to first start with a tool. So going to Raphael, who is a Data Scientist, how do you use AI in the Foreign Office? And I also know that you have data labs, data and AI labs in the Foreign Office. So could you maybe share a little bit of your day -to -day work?

And yeah, actually, how could AI be used in diplomacy?

Raphael Leuner

Yeah, thanks so much. Yeah, maybe to get to take a step back and answer the question, how like someone like me as a as a data scientist by training ends up in a foreign ministry. I think that’s something that at least when we talk to colleagues around the world is still rather rare. We had kind of the lucky coincidence that I think in 2021, the German government decided to start data labs in all of its federal ministries. And so in the coming years since then, 2022 or until 2022, kind of 16 data labs have been founded in the German federal government. And I was lucky enough to be part of the one in the German federal foreign office. Yeah.

And I was working on AI ever since we started more on traditional data science, I would say. So tearing down data silos between governments or government institutions, in Germany and, of course… And ever since JetGPT and the AI revolution, we have been working mostly on AI tools. And I think the big advantage that we see is that we are in the ministry itself and have very, very short contacts and short paths to our colleagues who are working in Berlin and, of course, all around the world. And I believe in a field that is as fast moving as AI, that is so important because it doesn’t really work to develop these tools in sort of a traditional IT way of doing things, right?

We used to have IT development projects that take two years, have huge teams, cost a lot of money, but that are just not fast enough to deliver on an AI solution that our colleagues, our colleagues are experiencing themselves in their private lives, right? And some of them even… some official aspects. So what we think is the big advantage that we have and what we kind of from our experience would always advertise for is kind of this fast co -creation from within an organization. And I think that is for a topic like diplomacy that is the best way of leveraging AI. And I’m happy to go into more detail about that.

Gunda Ehmke

Thank you. And I will later ask you more on concrete use cases. But first, I would like to switch to the geopolitical dimension. So Sharini, switching over to you. Taking a step back, AI is now in the political landscape more or less present everywhere. From the Arctis, but also here at the Summit. Can you give us a broader picture? How is AI shaping diplomacy or foreign policy in general? What is the debate and where are we at the moment?

Shahani Yaktiyami

Thank you. Thank you for the question and also the invitation to be here, which is actually also me being in my home country. So you’ve invited me to my home country, which is an interesting space to be in. But at the broader sort of geopolitical level, AI is shaping not only sort of how we use technology in our strategic communication as countries as well, but as a tool of technology diplomacy. And I don’t necessarily think this is particularly new. Throughout the history of international relations and foreign policy, technology has always shaped our foreign policy. So this is the AI revolution. But if we take it back to the Industrial Revolution, if we take it back to the nuclear revolution, if we take it back to the space race, technology has always informed diplomacy.

And today it is artificial intelligence. So the technology is not new. Yes. But the tactics aren’t. And today we are here at the AI Summit, and this is also India’s way of communicating that it is being a part of a particular technological revolution, which in its previous histories, because of colonial encounters and things, we’ve been excluded. So in this space, this is a way in which countries from our parts of the world are also trying to kind of claim a space in global technology diplomacy. And this is through AI. And what I would also kind of want to just qualify is what we’re seeing in this particular sort of AI race is narratives of competition.

So if you look at sort of policy documents coming out of the United States, coming out of China, there’s a clear connection between kind of winning an AI race or securing leadership in artificial intelligence. And if you are a country of that size and you are the country that has, invented the frontier technology and you’ve been sort of the first movers in that. if a kind of geopolitical leverage which countries like Germany and India perhaps don’t have because we aren’t at that frontier capability but that being said we’re not powerless we just have a different form of power expressing power and that is when the entire middle power conversation comes into play both India and Germany can see themselves are in fact arguably middle powers and they have different ways of using their specific leverage on an AI value chain as geopolitical leverage so for Germany historically this has been through rules and through regulation and regulatory power for India now it is making a case for applications so India and we’ve seen the fact that the summit has changed from the AI action summit which was the French presidency now is seeing India framing it as the impact summit the slogans of the summit are very very much to do with aspirations to deployment or aspirations to impact.

So that is really a way in which a middle power like India is also trying to kind of claim its position on the stack. So what you’re seeing are the great powers who are competing at the frontier level, and then there are middle powers who are claiming their specific power on the value chain in different ways. And I’ll stop there for a second.

Gunda Ehmke

Thank you very much. And I would like to pick up this statement that you said. But the tech is new, but the tactics aren’t. So I have here a diplomat sitting next to me. Would you agree with the statement? And how do you govern AI in the Ministry of Foreign Affairs? And would you say, is this still the right approach to AI?

Norman Schulz

Oh, well, the short answer would be no. But the topic is so broad that obviously I could give you a four -hour talk about it. But as a diplomat, as you said, one has to start by saying that the AI Impact Summit here in Delhi, where we are all gathered, showcases the broad variety of AI and the broad picture that AI is now part of every day’s life, of all strands of life. That it is a tool in communication. It is a tool in agriculture, in industrial entrepreneurship, in finance, and also in diplomacy and foreign policy. So I find that very interesting what you alluded to, that we have these revolutions all the time. like the Industrial Revolution, like the nuclear revolution after the Second World War?

And where do the foreign ministries, where do foreign policy comes in? I mean, the technological revolution created frontrunners like the UK, maybe a little bit like France. But there was a point in time when people saw that only being at the front and adapting the frontier models is not the way to success. But we have to find a way to regulate things because otherwise people will lose their lives. It’s not work safe. It’s polluting the environment. Even back then, there was a problem. Nuclear power, the same thing. There was a race in the 50s. And the Cuba crisis beginning at the 60s showed to the world that the nuclear race could not go on like it was.

But we need international cooperation to mitigate somehow the risks of it. And I think AI is at a similar point. Maybe it needs a couple of more years when the U .S. and China will actively come together and work out what limitations and regulations we have to put on the technology because the risks in the end are outweighing possible and potential benefits. And the other great question is where do the middle powers come in? And this is what India and Germany are talking about. Well, we had the speech of Mark Carney, the Canadian Prime Minister in Davos, where he actively called for the middle power cooperation. And he said, well, we don’t have the power to do that.

I think India is at a one. wonderful place because you are a digital powerhouse and you have all the structures and all the workforce to also become an AI powerhouse. I would also make the case that Germany has also some advantages. We have infrastructure, we have the money to invest into AI, and we also have industrial data to be a frontrunner. Even if we didn’t succeed at the stage of large language models, maybe when it comes to robotics and embodied AI, Germany will still have a role to play. And obviously we at the Foreign Office are there to accompany the development of this and to prepare. Prepare the ground for international cooperation. And I believe it at that because others…

Gunda Ehmke

thank you thank you i would like to turn now to the printing perspective um the pranav institute works at the intersection of emerging technology public policy and society from an india first perspective um how do you see um how do you see potential room for cooperation between india and germany like we hear now the middle power those are middle power i hear a lot at the summit that india is leading in a ai adoption um i wouldn’t say so maybe in germany maybe my german colleagues would agree or disagree with me but from your perspective where do you see cooperation like potential cooperation could you also go a step back and um explain to the audience where you see india at the moment maybe also in light of the ai summit

Shyam Krishnakumar

yeah can you hear me i think that’s a very challenging question to answer. Where is India at? India is at a very interesting place, certainly. India is not lagging behind. India is not yet at a place where we can build frontier models. I think the infrastructure capacity for that is very high. I do see some interesting innovation coming out of India. When we saw those 14 models that was released over 14 days and very, very interesting in the sense that this is innovation which is grounded, contextual. It is coming from the grassroots. You are able to find native language use cases. You are able to do inference at scale at much an order of magnitude cheaper costs.

So, you are seeing technical innovation which is more context appropriate coming from India. There is, of course, a large workforce which is talented in technology and there is an upscaling possibility that certainly exists when into AI and that is a very large pipeline. So I think India is a very interesting place. India is adopting, India is innovating, India is building applications and use cases, which is a very useful way to think about the technology in its early stages, right? Because there is a huge possibility of investment booms and busts that can come in when you go in a technologically challenging direction without being adaptive. So I think the focus on saying what can we solve is a very useful way to think.

I think the counselor did allude to industrial AI. That’s a fantastic use case of cooperation where you and India could possibly, Indo -German cooperation would certainly work out in that sense because there is industrial expertise, there is automation expertise in Germany, there is industrial data. India has the capability to build technology, build models. So I think if we were to identify and not worry about the race for frontier models, because transformers are not going to be the same. They’re not going to be the only technology paradigm out there and not play the game that leading powers are, but to really think as middle powers do as Sharon said and say that can we focus on sectoral expertise?

For example, AI in healthcare is a fantastic opportunity for. Indo -German cooperation, there is fantastic data available. India performs 10 times the number of surgeries that other countries do. So there’s very interesting data available. Germany has the capacity to invest. Can we cooperate? Germany has expertise in automation. India has, you know, people who can build AI models. Can we cooperate? So I think there is possibility for bilateral cooperation that, you know, gives an argument that is more than one plus one in the case of some of these. And I don’t think it’s a zero -sum game that U .S. is winning or China is winning and they’re all left behind. I think the focus on applications is really where a differentiator is possible, and that need not come at frontier -level costs.

Gunda Ehmke

Thank you. And I would like to focus now on this application side because this is maybe the way to react to big tech or like us as a country being in the middle between these mentioned countries. Rafa, can I hand over to you to share a little bit how you have the foreign office approach? I know that you are working on it. It’s a negotiation tool. And to what extent can open source also be a solution or might be a solution? to the situation where we are at the moment.

Raphael Leuner

Sure. Yeah, so I think it’s exactly as you said, that the focus is on application. We have made a consequential, but I think important decision at the beginning that when we are implementing AI, we are focusing for most of what we do on open source technologies, not just the models themselves, but also a lot of the kind of scaffolding and applications around it. So on the one hand, for example, we are reusing applications that, for example, come from one of our state governments who have done like kind of a general chat and knowledge -based application that we are reusing. But of course, we have specific applications in the foreign office like supporting negotiations. A lot of what diplomats nowadays do is not necessarily sitting in rooms and negotiating face -to -face, but actually digging through huge piles of documents and…

trying to understand the positions of other countries, the impact that NGOs, academia, corporations bring into huge negotiation processes. And, of course, that’s, as we probably all know, is a great chance for artificial intelligence to leverage. I think one important point when we’re talking about AI and open source AI in governments is that we have seen a big trend shift or a shift in the trend last year where we have seen that a lot of the kind of leading open source AI models and actually also the ones that have been adopted in many parts of the world are coming from China nowadays. I think that’s an interesting intersection between my position as a technical observer here where we are looking at the numbers and seeing that really, like, you know, the world is adopting Chinese AI models at the moment.

And, of course, the consequences that that might bring for a country like Germany or a country like Europe. Like India on a global scale, if maybe… some of our partners are implementing Chinese AI models. So that is something that when it comes to open source, I think it’s really important that countries like India, and I think India is at a great position, and I’m super excited to see these new Indian AI models as well, these Indian LLMs, to see if there can be pushes that offer alternatives to these Chinese models.

Gunda Ehmke

Thank you. I would like to come back to this impact aspect. Now we heard impact in the public sector, but maybe also reflecting on the summit, AI Impact Summit. What are your thoughts on how will we now continue the conversation regarding impact, regarding really being concrete and not only writing governance formats or governance frameworks, so how can we make this cooperation very concrete and also continue where we are and face this geopolitical challenge

Shahani Yaktiyami

Shoni, yeah I like that all the geopolitical questions then somehow come back to me but I don’t blame you because my background is in international relations so that serves very well this purpose but I want to kind of also connect your point to what you just said about open source and the China connection I think we’re reaching a stage in international relations in which geopolitics and technology can’t be separated when we are integrating artificial intelligence into our daily life and into our government systems we can’t really separate the security risks that come with it And I think every country has a unique security situation. For Germany, obviously, there is the concern with Ukraine. With India, we have border security challenges as well.

We have territorial disputes that are very significant and have very serious national security implications. So the kind of technology we deploy into our systems, and if it’s open source Chinese models or any other form where we perceive or any country would perceive a national security risk, that needs to be factored in. And that is why even in our technology decisions, they have to factor geopolitical risk, which back in the day was not something that, say, companies would have to do. But now every single company that I see has now a position for a geopolitical risk advisor. And that really comes from the fact that we are living in a world in which if we are using technologies so seriously in our lives, lives, we do need to factor in how those technologies can be weaponized in a particular geopolitical situation.

And then that kind of brings me back to also some of the points that were on, you said, you know, where we, you, foreign office would like find it helpful for reports to be kind of processed to AI. As a think tank, I think I’m a little bit hurt, I have to say, because a lot of our work is producing a lot of those reports, but we will force you to read them. We’re very persistent at the German Marshall Fund. We will reach out and invite you and make you read them. But jokes aside, it is really, we’re aware also that our ability to consume information as well is kind of becoming shorter, but the world is getting more complex.

And therefore, we are also kind of preparing, even in the think tanking that we do, even in the way in which we kind of do our daily jobs, to factor in that. There will be an AI in this system, and we kind of need to put that into consideration as well.

Gunda Ehmke

and since there will be an AI in the system we have to make sure that we can trust this AI and that it’s also inclusive and that it’s yeah ethical in a sense or trustworthy regarding to standards so how do you and the government react to this could you also share more about the global digital compact and what is this panel about this scientific panel I think it’s called and how do we make sure that from this governance it goes to the system to the AI system like how do we make sure that the systems are aligned with our values

Norman Schulz

well that’s big question the best way to align the systems with our values is to develop to develop them ourselves right and not just procure them from from outside and I couldn’t agree more with the point that you made about the Chinese models, that even if it is open source, even if it runs on our servers, there are still Chinese models. They still have the Chinese ways and the Chinese ways of thinking, which comes through maybe not all the time. So using AI to do diplomatic work will not be the way because then every report will be the same, right? So I hope that Germany will not go the way to write the diplomatic reports now only using AI or summarizing it.

But we need our diplomats to insert that innovative thinking. And innovative thinking does not come from AI. Because AI… AI is much rather replicating, summarizing, in my understanding. The new ideas still come from the human side. As far as I make it out. Global digital compact. Thanks for the question. The Foreign Office was the lead in Germany to negotiate the global digital compact. And obviously you can make a point that this is a UN compact and the UN system is under immense pressure at the moment. So what does it achieve? And I would make the point that despite all that, it has at least produced two valuable avenues for future cooperation and discussion, two platforms.

The first is the AI panel. I think it’s called Independent Scientific International Panel on AI, but I could be wrong with the two I’s. It’s rather complicated. But it was just yesterday that the UN Secretary General made the point that the AI panel and the second one, the dialogue I will come to in a second, are the two major things where the UN is coming into the picture. And the panel has the task to put our discussions that we have on a global level about AI on a scientific basis. So those are experts, and I’m happy that there are two experts from Germany on the panel. Only the U .S. and China have also two experts.

I’m terribly sorry. I don’t know how many Indian experts are on the panel. But we’ll find. We’ll find that out. True. So they will produce a first report, a summary of where the AI science is now standing in time for the first global dialogue on AI governance, which will happen in July in Geneva in the margins or back to back with the AI for Good Summit at the International Telecommunications Union. And this dialogue serves the other big purpose of the Global Digital Compact, which is to make the AI discussion inclusive. And so it’s also the UN Secretary General nonetheless that said that AI cannot be a discussion among the few, the ones that are the front runners like the US and China.

They should not be the one to they should not. Not be the only one to set the rules, but it has to be a truly inclusive discussion about the AI. Up until now, more than 100 countries were not part of this discussion because they were not members of the European Union, not members of the Council of Europe, not members of the G7 or the G20. But they are the ones that will use AI, that will adapt AI, and they will also feel the bad results if AI is not doing what it is supposed to do. So it’s good that they have a voice at the table, that all UN member states will in July come together and talk about AI on the scientific base that the panel has provided.

So that is something that the Global Literature Compact is doing. And, of course, we can talk about geopolitics all the time, but I think that’s a way forward. And it’s to make a point. And I stop here and make a point.

Gunda Ehmke

Thank you. Thank you. And, Jian, let me turn to you now. And the fact that there is not a zero -sum game in a lot of this. I think the idea that we can work together to bring a larger voice beyond the worries of two countries or three countries which are able to compete at the top. I think that’s something that they shared. And I think the role of middle powers in bringing a more inclusive conversation is really important. And I think Indo -German cooperation is an opportunity for that. Including, for example, industrial AI that the counsellor mentioned or other opportunities where we can practically create tools like what Rafael is also talking about. Where we can practically create tools that are beneficial and maybe open source.

Why should open source models only come from strategically challenging sources? There could be Indo -German open source models, smaller models, not frontier models that could be beneficial.

Raphael Leuner

Yeah, I can maybe react to that directly because I think it’s super critical. I don’t think some people believe or make us believe that the AI race is already over or kind of only being decided between the US and China. I don’t believe that. I think we’re more at the start of what’s going to come. And I think we can feel this at the summit. And Gunda, you asked the question, what comes next? I think next comes building and implementing AI in all these kind of fields that we have. I think we see so many ideas around here and first steps towards that. But we don’t really see widespread AI adoption in every field, in every kind of part of life.

I do think this is going to happen over the next five years. And I don’t believe for a second that this is only going to be done by the U .S. or China. And, yeah, I think that when it comes to middle powers, Germany, India, I think we are going to see much closer collaboration in like smaller groups that don’t try to kind of, you know, build dependence, right, making you dependent on us, making us dependent on you, but rather ensure that every country can bring to the table what they are particularly good at and make the results kind of improve the application of AI for everybody involved. I do think there is a strategy for that.

And I think, yeah, the way forward you have asked is to start with it and to build AI together. I think this is a great, you know, a great rally cry for

Gunda Ehmke

Yeah, yeah, please.

Shyam Krishnakumar

Rafal, you led me on to a very interesting trail, so I had to intervene. I think one of the interesting moments, if you think about technology again, in the 1990s was the open source revolution, right? And when you really saw operating systems, consider the frontier technology of that time being built by volunteers at a fraction of the cost. diffuse the race in a certain way or diffuse the dominance in a certain way, but also enabled accessibility across the world. So I think even coming together as middle powers, the power of open source and democratizing and reducing the factor costs of access to AI, it becomes very powerful if you draw from it. And now you led me on to a trail as well.

I just want to kind of contextualize the sovereignty thing as well.

Shahani Yaktiyami

And I do think that when we talk about artificial intelligence, it’s not just one application that we see when we use our phones or interact with a particular model, right? It’s an entire stack. And the question of sovereignty or the concerns vis -a -vis the sovereignty debate is also born out of geopolitics, right? So we don’t want to be as a particular country in which suddenly one day we wake up and our technology is not available to us because, because of something else that happened in another country. corner of the world. So the sovereignty debate is coming out of geopolitics as well. That being said, we don’t need to be beholden to it. I fully agree.

And I really like the point on us understanding what our strengths are. I mean, Germany had a high -tech strategy that came out last year. There’s also an emphasis on Germany being a space for data as a data hub. And India is trying to do that as well. Germany already has that. One of the things China is really good at actually is industrial data, because they have been collecting this data for a very long time because they automated quicker than a lot of us. And that’s something where we can collectively build competitiveness. So I do think we need to reset some of the inequalities in the AI stack and that sovereignty, as much as I kind of understand where that comes from, I don’t always think that that’s the…

best language to talk about where we are at. I do think we need more sophisticated and nuanced ways of kind of talking about a managed interdependence where I have a certain value on an AI stack. That is my strength. And the likelihood of you weaponizing that makes it very limited. So that’s why I have leverage. And I do think leveraging a country’s strength on a specific AI stack is a prominent and powerful middle power strategy.

Gunda Ehmke

Thank you. These are all beautiful closing remarks, but I would like to open the floor to the audience. Are there any questions? Yes, everyone around.

Audience

Hi, I’m Sreeni. I’m a student at Ashoka University. I have a question for everyone in the panel. Feel free to. answer. The question is, what are some parts of foreign policy research, decision making and implementation which can be automated by AI or that will use a significant uses of AI to sort of do your day -to -day tasks?

Norman Schulz

Maybe I can quickly answer this question. Well, I certainly don’t think that AI will make any decision in any time soon. So there’s always going to be the human that is making the decision. And it’s not going to be me. It’s not going to be my boss. It’s going to be a collaborative decision by the government and the legislature and all of that. But our job will also not go away. We will use AI to make our job easier to consume data, to consume, I would like to say information, but it’s nothing. Consuming information easier, quicker and which in turn will free diplomats to do the other time, which is connecting, which is connecting the dots, which is thinking out innovative ways of cooperation, which is, it’s basically like drinking coffee and shaking hands.

These start traveling to India and learn a lot about the situation here. So, AI will free us from tedious tasks of skipping through these very valuable documents written by not only NGOs, but also governments, and will make our lives easier, but our work will not go away. Thank you.

Gunda Ehmke

Okay, one more question. The lady maybe in the back.

Audience

Hi, I’m Sanjeevni, and I work in radio journalism in the UK. And my question was for you, Norman. So, specifically, So, Norman and Sharini, both of you, actually. So, you guys are doing your Masters in Journalism. I was studying about how journalists were framing the Russia -Ukraine war. And we were observing how the narratives were changing based on different outlets. But something when we were talking about how AI is coming into play, do you think AI will help change narratives for the better? And I’m not speaking from journalism point of view. In general, geopolitically, do you think the narratives will be framed in a way that’s unbiased? Or how do you think it will help in that?

Shahani Yaktiyami

I don’t take a stab. I’d be very curious to point a question, actually, to you, because one of the things I’ve been really intrigued in in my line of work is how AI has been being deployed in the media and newsrooms. And I’d be very interested to have a chat after to learn how you’re doing that in terms of methodology. But to your question on AI shaping, I think it’s a great question. narratives, I would not let AI shape narratives. I would hope we shape narratives as human beings, depending on sort of what we think and feel and analyze through empirical evidence about the world. And I would be very worried in a world in which AI, we allow AI the space to shape narratives, especially on geopolitics, because then that would depend upon what that particular AI model that is doing the narrative shaping has been trained on.

But that being said, I would also see how AI can do the harm in terms of amplifying incorrect narratives or geopolitically challenging narratives. And that’s when we know that AI cannot replace society and it cannot do. So I do think that we are in a world in which if AI, we allow AI to shape narratives, that’s not a world we want to live in. Thank you. but at the same time, if it is a world in which that can happen, we need to find the right mitigation strategies to do that. One thing that I know India is doing, Shyam, we talked about it earlier, which is these bias detection technologies that are critical. AI is a technology that, on one hand, we do need strong regulation to make sure that we can prevent the harms from doing what they can, but at the same time, we need also technological tools to deal with some of those harms and push a democratic innovation as well in AI for exactly these harms.

And I’ll stop there.

Norman Schulz

Just one sentence. If you let AI write the newspapers, they are becoming incredibly dull because it’s going to be repetitive all the time. But I agree with your point about bias. This is something that we all have to challenge and to face. And AI is helping us. That’s a good thing. AI is not only a risk, it’s also the opportunity, helping us detect bias and then contravene it. Thank you.

Raphael Leuner

Just one sentence I want to add because I found your point so important. I don’t see any risk that AI is going to shape the narratives itself somehow, but of course it’s an incredible tool for actors trying to shape narratives. And we have seen this on so many fronts already. We have colleagues in the foreign office who are actually monitoring this and seeing that it’s, for example, used to amplify certain messages across social media, increasingly now across faked websites that, with the help of AI, you can pull up in seconds and suddenly you don’t have one of them or two of them, but you have thousands of them. And that is something that AI has already used quite heavily as a tool of certain actors who are trying to influence geopolitical discussions in exactly that way.

Gunda Ehmke

Sorry, we are running out of time, but I’m sure that the speakers stay here a little bit. So thank you for listening to our panel discussion. Maybe a big applause. Thank you.

Related ResourcesKnowledge base sources related to the discussion topics (34)
Factual NotesClaims verified against the Diplo knowledge base (4)
Confirmedhigh

“Gunda Ehmke introduced Raphael Leuner (data scientist, German Federal Foreign Office), Dr Shahani Yaktiyami (senior officer, German Marshall Fund), and Norman Schulz (consular officer for AI and digital technologies, German Foreign Office).”

The participant list and their roles are confirmed by the knowledge base entries that name Raphael Leuner, Dr. Shahani Yaktiyami and Norman Schulz with the same titles [S1] and [S8].

Additional Contextmedium

“The lab’s work includes building AI tools for negotiations, notably analysing large document collections.”

The knowledge base describes AI applications in negotiations such as data analysis, scenario modelling and document analysis, providing context for the lab’s focus [S100].

Additional Contextlow

“The team chose open‑source technologies and to reuse existing state‑government applications to keep development agile and cost‑effective.”

European policy discussions highlight a preference for open-source solutions in government systems and view open source as a competitive tool, adding nuance to the lab’s strategy [S109] and [S104].

Additional Contextlow

“Leuner noted the growing worldwide adoption of Chinese open‑source models and expressed enthusiasm for Indian large‑language‑model alternatives.”

The knowledge base mentions China’s use of open-source AI models and Europe’s interest in leveraging open-source technology, providing background for the observation about Chinese models, though it does not specifically reference Indian LLMs [S109].

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AI Algorithms and the Future of Global Diplomacy — Institute. Then we have Raphael Leuner, Data Scientist at the German Federal Foreign Office. We have Dr. Shahani Yaktiya…
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AI Algorithms and the Future of Global Diplomacy — -Gunda Ehmke: Moderator/Host of the discussion
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DAgA EgHIC\_ ʧ GLwE[FAFCE — BYX, EW XLI] EPWS TSMRX SYX, MJ [I HSRƶX JMRH [E]W XS WLEVI HEXE [I [MPP FI QYGL PIWW EFPI XS QEREKI XVERWMXMSRW, GY…
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AI Algorithms and the Future of Global Diplomacy — – Shahani Yaktiyami- Norman Schulz
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AI Algorithms and the Future of Global Diplomacy — -Shyam Krishnakumar: Works at an institute (appears to be associated with Pranav Institute based on context), focuses on…
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AI Algorithms and the Future of Global Diplomacy — Hi, I’m Sreeni. I’m a student at Ashoka University. I have a question for everyone in the panel. Feel free to. answer. T…
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https://dig.watch/event/india-ai-impact-summit-2026/ai-algorithms-and-the-future-of-global-diplomacy — Institute. Then we have Raphael Leuner, Data Scientist at the German Federal Foreign Office. We have Dr. Shahani Yaktiya…
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Islamic State exploits AI to enhance propaganda — Islamic State supporters increasingly use AI tobolstertheir online presence and create more sophisticated propaganda. A …
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Z.ai unveils cheaper, advanced AI model GLM-4.5 — Chinese AI startup Z.ai, formerly Zhipu, is increasing pressure on global competitors with its latest model,GLM-4.5. The…
S108
The rise of large language models and the question of ownership — What are large language models? Large language models (LLMs) are advanced AI systems that can understand and generate va…
S109
Global Perspectives on Openness and Trust in AI — “which is why in France and in Europe we’re very much in favor of open source as a competitive tool and as a way to leve…
S110
Keynotes — Historical Context of Technological Revolutions
S111
Satellite diplomacy — Satellite diplomacy cuts across all three aspects of diplomacy. Satellites are part of reshaping geopolitical environmen…
S112
AI for Democracy_ Reimagining Governance in the Age of Intelligence — I believe this had been the most important event. We are more or less actually reaching to the… culmination of this hi…
S113
Military AI: Operational dangers and the regulatory void — While international forums are yet to find consensus on key issues, many states are straying further from regulation to …
S114
AI race shows diverging paths for China and the US — The US administration’s new AI action plan frames global development as anAI racewith a single winner. Officials argue A…
S115
Building Trusted AI at Scale – Keynote Anne Bouverot — This comment shifts the discussion from acknowledging competition to actively proposing strategic alliances. It introduc…
Speakers Analysis
Detailed breakdown of each speaker’s arguments and positions
R
Raphael Leuner
8 arguments157 words per minute1172 words446 seconds
Argument 1
Fast co‑creation via data labs enables rapid AI solutions (Raphael)
EXPLANATION
Raphael explains that the establishment of data labs across German ministries created short, direct channels to colleagues, allowing the Foreign Office to develop AI tools quickly. This fast co‑creation bypasses the slow, costly traditional IT projects.
EVIDENCE
He notes that the German government launched data labs in 2021, resulting in 16 labs across ministries by 2022, and that he joined the one in the Foreign Office [12-14]. He stresses that being inside the ministry gives very short contact paths to colleagues, which is crucial for the fast-moving AI field and enables rapid co-creation of solutions [18-23].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The establishment of data labs across German ministries in 2021 and their role in rapid AI prototyping are described in the AI Algorithms and the Future of Global Diplomacy report [S1].
MAJOR DISCUSSION POINT
Implementation of AI within the German Foreign Office
DISAGREED WITH
Norman Schulz, Shahani Yaktiyami
Argument 2
AI supports negotiation preparation by processing large document sets (Raphael)
EXPLANATION
Raphael describes AI tools that help diplomats analyse massive amounts of documents to understand other countries’ positions and the impact of NGOs, academia and corporations. This supports more informed negotiation preparation.
EVIDENCE
He mentions a specific application that assists negotiations by digging through huge piles of documents to extract relevant positions and impacts, highlighting AI’s role in this process [130-133].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI’s capacity to synthesize massive document collections for negotiations is highlighted in How AI Is Transforming Diplomacy and Conflict Management [S15] and in the Cybermediation discussion of AI-assisted preparation [S14].
MAJOR DISCUSSION POINT
Implementation of AI within the German Foreign Office
AGREED WITH
Norman Schulz
Argument 3
Prioritising open‑source AI reduces dependence on external vendors, but Chinese open‑source models pose strategic concerns (Raphael)
EXPLANATION
Raphael states that the Foreign Office deliberately uses open‑source AI technologies and scaffolding to avoid vendor lock‑in, yet observes that many leading open‑source models currently come from China, raising strategic worries for Europe and India.
EVIDENCE
He explains that the office focuses on open-source models and tooling, reusing state applications, and notes the recent surge of Chinese open-source AI models being adopted worldwide, which could have consequences for Germany and Europe [128-136].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The strategic shift toward open-source AI and the emerging dominance of Chinese open-source models are analysed in The strategic imperative of open source AI [S16] and China’s AI industry transformation with open-source models [S17].
MAJOR DISCUSSION POINT
Governance, regulation, and international cooperation on AI
AGREED WITH
Norman Schulz
DISAGREED WITH
Norman Schulz, Shahani Yaktiyami
Argument 4
Joint development of non‑frontier AI projects can strengthen both countries’ positions (Raphael)
EXPLANATION
Raphael argues that middle powers like Germany and India can collaborate on AI projects that are not at the frontier, focusing on shared strengths to create practical applications without creating dependency on the US or China.
EVIDENCE
He emphasizes that AI adoption will expand over the next five years, that middle powers will collaborate in smaller groups, and that building AI together on non-frontier models will benefit all participants [202-213].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Collaboration on non-frontier AI models among middle powers is advocated in the AI Algorithms and the Future of Global Diplomacy transcript [S1] and the open-source vs. proprietary debate [S19].
MAJOR DISCUSSION POINT
Indo‑German cooperation and sectoral AI applications
AGREED WITH
Shyam Krishnakumar, Gunda Ehmke, Shahani Yaktiyami
Argument 5
The German Foreign Office adopts open‑source technologies and reuses existing state applications for AI projects (Raphael)
EXPLANATION
Raphael outlines the office’s strategy of leveraging open‑source AI models and reusing existing applications from German states to accelerate AI deployment while minimizing development costs.
EVIDENCE
He cites the reuse of a general chat and knowledge-based application from a state government and the broader focus on open-source technologies for AI projects [128-130].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The Foreign Office’s reuse of state-level applications and its open-source AI stack are documented in the AI Algorithms and the Future of Global Diplomacy report [S1] and reinforced by the strategic imperative of open-source AI [S16].
MAJOR DISCUSSION POINT
Open‑source AI strategy and strategic considerations
Argument 6
There is a need to develop Indian open‑source alternatives to counter the dominance of Chinese models (Raphael)
EXPLANATION
Raphael calls for the creation of Indian open‑source large language models to provide alternatives to the currently dominant Chinese models, thereby diversifying the AI ecosystem.
EVIDENCE
He mentions his excitement about emerging Indian AI models and suggests they could serve as alternatives to Chinese offerings, reducing strategic dependence [135-137].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Calls for Indian open-source large language models as alternatives to Chinese offerings are echoed in analyses of open-source strategy and Chinese model risks [S16] and [S17].
MAJOR DISCUSSION POINT
Open‑source AI strategy and strategic considerations
Argument 7
AI is already being used as a tool for propaganda; continuous monitoring is required (Raphael)
EXPLANATION
Raphael warns that AI is being exploited to amplify political messages and generate large numbers of fake websites, necessitating ongoing monitoring by the Foreign Office.
EVIDENCE
He describes how AI is used to amplify certain messages across social media and to quickly create thousands of fake websites, a practice already observed by colleagues in the Foreign Office [295-298].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The use of AI for large-scale disinformation and propaganda, and the need for ongoing monitoring, are discussed in the AI and Disinformation forum [S21] and in reports on extremist exploitation of AI [S22].
MAJOR DISCUSSION POINT
AI’s impact on diplomatic work and narrative formation
AGREED WITH
Norman Schulz, Shahani Yaktiyami
DISAGREED WITH
Shahani Yaktiyami, Norman Schulz
Argument 8
AI adoption in the Foreign Office is expected to expand significantly over the next five years.
EXPLANATION
Raphael predicts that AI will become widely used across many functions of the Foreign Office within a medium‑term horizon, moving beyond pilot projects to broader deployment.
EVIDENCE
He states that while AI is not yet widespread in every field, he expects widespread AI adoption in the next five years [211-212].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Projected rapid expansion of AI within foreign ministries aligns with global adoption trends reported in Global AI adoption reaches record levels [S23] and the forward-looking outlook in the AI Algorithms report [S1].
MAJOR DISCUSSION POINT
Future trajectory of AI implementation in diplomacy
N
Norman Schulz
7 arguments127 words per minute1437 words675 seconds
Argument 1
AI frees diplomats from tedious data‑consumption tasks, but decisions remain human (Norman)
EXPLANATION
Norman explains that AI can automate the processing of large volumes of information, allowing diplomats to focus on higher‑level analysis and relationship‑building, while final decisions will still be made by humans.
EVIDENCE
He states that AI will make consuming information easier and quicker, freeing diplomats for connecting the dots and innovative cooperation, but emphasizes that decision-making will remain a collaborative human process [257-259].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI’s role in automating data consumption while keeping decision-making human is described in How AI Is Transforming Diplomacy and Conflict Management [S15] and reinforced by AI diplomacy commentary emphasizing human mastery [S24].
MAJOR DISCUSSION POINT
Implementation of AI within the German Foreign Office
AGREED WITH
Raphael Leuner
Argument 2
International cooperation is needed to mitigate AI risks, analogous to nuclear‑era agreements (Norman)
EXPLANATION
Norman draws parallels between the nuclear arms race and the current AI race, arguing that global cooperation is essential to manage AI risks and prevent harmful competition.
EVIDENCE
He references historical nuclear tensions, the Cuban crisis, and suggests that the US and China will eventually need to cooperate on AI regulations, highlighting the need for international risk mitigation [66-76].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The analogy between AI risk mitigation and nuclear arms control is drawn in the IGF 2023 session on AI governance [S26] and in the UNGA Resolution on enhancing international cooperation on AI [S18].
MAJOR DISCUSSION POINT
Geopolitical implications of AI and the role of middle powers
AGREED WITH
Shahani Yaktiyami
DISAGREED WITH
Raphael Leuner, Shahani Yaktiyami
Argument 3
Germany leads the Global Digital Compact and the UN AI scientific panel to ensure inclusive governance (Norman)
EXPLANATION
Norman outlines Germany’s leadership in negotiating the Global Digital Compact and its participation in the UN‑mandated Independent Scientific International Panel on AI, which aims to provide a scientific basis for global AI governance.
EVIDENCE
He details Germany’s role in the Compact, the AI panel’s composition, its upcoming report, and the July AI dialogue in Geneva that will feed into inclusive AI governance discussions [166-184].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Germany’s leadership role in the Global Digital Compact and the UN-mandated Independent Scientific International Panel on AI is noted in the UNGA resolution on AI cooperation [S18].
MAJOR DISCUSSION POINT
Governance, regulation, and international cooperation on AI
AGREED WITH
Shahani Yaktiyami
Argument 4
AI automates information processing, freeing diplomats for higher‑level work, but does not replace decision‑making (Norman)
EXPLANATION
Norman reiterates that AI will handle routine data‑processing, enabling diplomats to concentrate on strategic thinking and relationship‑building, while decision authority stays with human officials.
EVIDENCE
He repeats that AI will free diplomats from tedious document review, allowing them to focus on connecting the dots and innovative cooperation, but stresses that decisions will still be made collaboratively by government and legislature [257-259].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Automation of information processing while preserving human decision authority is highlighted in How AI Is Transforming Diplomacy [S15] and AI diplomacy commentary [S24].
MAJOR DISCUSSION POINT
AI’s impact on diplomatic work and narrative formation
Argument 5
AI can be employed to detect and mitigate bias in media and diplomatic narratives.
EXPLANATION
Norman highlights AI’s capacity to identify biased content and help correct it, turning the technology into a safeguard rather than a source of bias.
EVIDENCE
He notes that AI helps detect bias and then counter it, describing it as both a risk and an opportunity for bias mitigation [288-292].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI-driven bias detection and mitigation tools for media and diplomatic content are discussed in the AI and Disinformation forum [S21] and in crisis-management literature on bias mitigation [S25].
MAJOR DISCUSSION POINT
AI as a tool for bias detection
Argument 6
AI should not replace human creativity in diplomatic reporting; human innovative thinking remains essential.
EXPLANATION
Norman warns that relying solely on AI for drafting diplomatic reports would erase the unique analytical contributions of diplomats, emphasizing the need for human insight.
EVIDENCE
He argues that using AI to write diplomatic reports would make them uniform and that innovative thinking must come from humans, not AI [159-164].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The necessity of human creativity in diplomatic reporting is emphasized in AI diplomacy commentary that stresses human mastery of the tool [S24] and in crisis-management oversight discussions [S25].
MAJOR DISCUSSION POINT
Limits of AI in diplomatic work
Argument 7
Developing AI domestically ensures alignment with national values and avoids foreign model biases.
EXPLANATION
Norman suggests that building AI systems in‑house is the best way to guarantee they reflect a country’s own values and are not influenced by external ideological biases.
EVIDENCE
He states that the best way to align systems with values is to develop them ourselves rather than procure from outside, and cites concerns about Chinese model biases [157-158].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Domestic AI development to safeguard national values and avoid foreign model bias is supported by analyses of the strategic imperative of open-source AI [S16] and concerns about Chinese model bias [S17].
MAJOR DISCUSSION POINT
Domestic AI development for value alignment
S
Shahani Yaktiyami
6 arguments162 words per minute1665 words615 seconds
Argument 1
AI continues the historic pattern of technology shaping diplomacy; tactics are not new (Shahani)
EXPLANATION
Shahani observes that technology has always influenced foreign policy, citing past revolutions such as the Industrial, Nuclear, and Space eras, and positions AI as the latest iteration of this long‑standing dynamic.
EVIDENCE
She references the historical impact of the Industrial, nuclear, and space revolutions on diplomacy, stating that today artificial intelligence continues this pattern [36-40].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The view that AI is the latest in a series of technological revolutions affecting diplomacy is reflected in the AI Algorithms and the Future of Global Diplomacy overview of past revolutions [S1] and AI diplomacy commentary [S24].
MAJOR DISCUSSION POINT
Geopolitical implications of AI and the role of middle powers
Argument 2
Middle powers can leverage AI through regulation (Germany) and application‑focused strategies (India) (Shahani)
EXPLANATION
Shahani argues that Germany can use its regulatory expertise while India can focus on AI applications, allowing both middle powers to exert influence on the AI value chain despite not leading in frontier model development.
EVIDENCE
She explains that Germany traditionally leverages rules and regulation, whereas India emphasizes application-driven AI, illustrating how each middle power can claim a strategic position on the AI stack [48-50].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The complementary roles of Germany’s regulatory expertise and India’s application-driven AI approach are discussed in the UNGA AI cooperation resolution [S18] and the strategic imperative of open-source AI [S16].
MAJOR DISCUSSION POINT
Geopolitical implications of AI and the role of middle powers
AGREED WITH
Raphael Leuner, Shyam Krishnakumar, Gunda Ehmke
DISAGREED WITH
Norman Schulz, Raphael Leuner
Argument 3
AI deployment must factor security and sovereignty risks specific to each country (Shahani)
EXPLANATION
Shahani stresses that AI systems must be evaluated for national security implications, citing Germany’s concerns about Ukraine and India’s border disputes, and notes that companies now employ geopolitical risk advisors.
EVIDENCE
She mentions Germany’s concern with Ukraine, India’s border security challenges, and the emergence of geopolitical risk advisors in companies, underscoring the need to embed security considerations into AI deployment [141-148].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Country-specific security and sovereignty considerations for AI deployment are highlighted in the UNGA resolution on AI capacity-building [S18] and in risk-aware AI governance literature [S25].
MAJOR DISCUSSION POINT
Governance, regulation, and international cooperation on AI
AGREED WITH
Norman Schulz
Argument 4
AI should not autonomously shape geopolitical narratives; human oversight is essential (Shahani)
EXPLANATION
Shahani argues that narratives should remain under human control, warning that AI‑generated narratives could reflect the biases of the underlying models and potentially amplify misinformation.
EVIDENCE
She states that AI should not be allowed to shape narratives, emphasizing the need for human judgment and expressing concern about AI-driven amplification of incorrect or geopolitically charged narratives [277-280].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The need for human oversight over AI-generated geopolitical narratives is advocated in AI diplomacy commentary emphasizing human mastery [S24] and bias-mitigation discussions [S25].
MAJOR DISCUSSION POINT
AI’s impact on diplomatic work and narrative formation
AGREED WITH
Raphael Leuner, Norman Schulz
DISAGREED WITH
Norman Schulz, Raphael Leuner
Argument 5
AI can assist in detecting and mitigating bias in media narratives (Shahani)
EXPLANATION
Shahani highlights that AI tools can be employed to identify and counteract bias in news and social media, suggesting that such technologies are part of India’s efforts to ensure fair information flows.
EVIDENCE
She points to India’s development of bias-detection technologies and calls for strong regulation combined with technical tools to mitigate harms while fostering democratic innovation [284-286].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI tools for bias detection in media and social platforms are covered in the AI and Disinformation forum [S21] and in crisis-management bias mitigation studies [S25].
MAJOR DISCUSSION POINT
AI’s impact on diplomatic work and narrative formation
Argument 6
AI serves as a tool for strategic communication and technology diplomacy, enabling countries to project influence.
EXPLANATION
Shahani describes AI not only as a technology but also as a means for states to conduct strategic communication and advance their diplomatic objectives in the global arena.
EVIDENCE
She notes that AI is shaping how we use technology in strategic communication as countries, and that it functions as a tool of technology diplomacy [35-36].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI’s role as a strategic communication instrument in technology diplomacy is examined in How AI Is Transforming Diplomacy and Conflict Management [S15] and in the AI and Disinformation discussion [S21].
MAJOR DISCUSSION POINT
AI as an instrument of technology diplomacy
S
Shyam Krishnakumar
4 arguments198 words per minute648 words195 seconds
Argument 1
India excels in context‑specific models and has a large, skilled AI workforce, though it does not yet build frontier models (Shyam)
EXPLANATION
Shyam notes that while India is not yet creating large frontier language models, it produces context‑relevant AI solutions, benefits from a sizable talent pool, and can develop applications at lower cost.
EVIDENCE
He states that India is not lagging but lacks frontier model capability; however, it shows strong innovation with 14 models released over 14 days, a large skilled workforce, and cost-effective inference capabilities [92-100].
MAJOR DISCUSSION POINT
Indo‑German cooperation and sectoral AI applications
Argument 2
Cooperation opportunities exist in industrial AI and healthcare, combining German data/automation expertise with Indian model‑building capacity (Shyam)
EXPLANATION
Shyam proposes joint projects where Germany contributes industrial data and automation know‑how, while India provides AI model development, especially in sectors like healthcare where large datasets exist.
EVIDENCE
He cites industrial AI as a promising cooperation area, mentions India’s capacity to build models, Germany’s automation expertise, and highlights healthcare data (India performs ten times more surgeries) as a fertile ground for joint AI initiatives [108-119].
MAJOR DISCUSSION POINT
Indo‑German cooperation and sectoral AI applications
AGREED WITH
Raphael Leuner, Gunda Ehmke, Shahani Yaktiyami
Argument 3
Open‑source democratizes AI, lowers entry costs, and enables middle‑power collaboration (Shyam)
EXPLANATION
Shyam reflects on the 1990s open‑source revolution, arguing that open‑source AI reduces barriers to entry and allows middle powers to collaborate without being dominated by large vendors.
EVIDENCE
He references the open-source revolution of the 1990s, noting how volunteer-built operating systems lowered costs and democratized access, and connects this to current AI collaboration among middle powers [219-222].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The democratizing effect of open-source AI and its suitability for middle-power collaboration are analysed in The strategic imperative of open source AI [S16] and the open-source vs. proprietary debate [S19].
MAJOR DISCUSSION POINT
Open‑source AI strategy and strategic considerations
Argument 4
India’s large, skilled AI workforce creates a strong pipeline for upskilling and capacity development.
EXPLANATION
Shyam points out that the extensive talent pool in India provides a foundation for continuous AI skill development and scaling of AI initiatives.
EVIDENCE
He mentions a large workforce that is talented in technology and an upscaling possibility that certainly exists for AI, indicating a strong pipeline for capacity development [102-103].
MAJOR DISCUSSION POINT
India’s AI talent pipeline
G
Gunda Ehmke
3 arguments111 words per minute927 words500 seconds
Argument 1
AI has become pervasive in the political landscape, influencing diplomacy and foreign policy.
EXPLANATION
Gunda notes that artificial intelligence is now present everywhere in politics, shaping how diplomacy and foreign policy are conducted.
EVIDENCE
She observes that AI is now in the political landscape more or less present everywhere and asks how it is shaping diplomacy and foreign policy in general [28-32].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The pervasiveness of AI in politics and its impact on diplomacy is noted in AI diplomacy commentary stressing human mastery of the tool [S24].
MAJOR DISCUSSION POINT
Geopolitical impact of AI on diplomacy
Argument 2
Open‑source AI models should be co‑developed by middle powers like India and Germany rather than relying on models from strategic rivals.
EXPLANATION
Gunda argues that middle powers can create their own open‑source AI solutions, reducing dependence on Chinese or other strategically sensitive sources and fostering inclusive innovation.
EVIDENCE
She questions why open-source models should only come from strategically challenging sources and suggests that Indo-German open-source models could be developed as alternatives [200-201].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The case for co-development of open-source models by middle powers is made in The strategic imperative of open source AI [S16] and the open-source vs. proprietary discussion [S19].
MAJOR DISCUSSION POINT
Indo‑German cooperation on open‑source AI
Argument 3
The AI Impact Summit should move from high‑level statements to concrete cooperation mechanisms.
EXPLANATION
Gunda emphasizes the need to translate summit discussions into tangible actions and partnerships rather than merely producing governance frameworks.
EVIDENCE
She asks how the conversation on impact can become concrete and lead to real cooperation, highlighting the gap between discussion and implementation [138-140].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Calls for translating high-level AI summit statements into concrete cooperation actions appear in the IGF 2023 session urging practical mechanisms [S26].
MAJOR DISCUSSION POINT
From AI impact discussion to concrete cooperation
A
Audience
2 arguments148 words per minute183 words73 seconds
Argument 1
AI can automate parts of foreign‑policy research, decision‑making and implementation, easing diplomats’ day‑to‑day tasks.
EXPLANATION
A student asks which components of foreign‑policy work could be handled by AI, implying that automation is feasible and desirable for routine analytical work.
EVIDENCE
The audience member asks what parts of foreign-policy research, decision making and implementation can be automated by AI for day-to-day tasks [246-249].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Automation of foreign-policy research and decision support by AI is highlighted in How AI Is Transforming Diplomacy and Conflict Management [S15] and reinforced by AI diplomacy commentary on human-AI collaboration [S24].
MAJOR DISCUSSION POINT
Potential automation of foreign‑policy work
Argument 2
AI has the potential to improve media narratives and reduce bias, but safeguards are needed to ensure neutrality.
EXPLANATION
An audience participant questions whether AI can help create more unbiased narratives in journalism and geopolitics, suggesting that AI could be a tool for better framing if properly managed.
EVIDENCE
The audience asks if AI will help change narratives for the better and whether it can produce unbiased geopolitical narratives [264-273].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The potential of AI to improve narratives while requiring safeguards is discussed in the AI and Disinformation forum [S21] and in bias-mitigation studies within crisis-management literature [S25].
MAJOR DISCUSSION POINT
AI’s role in shaping and bias‑checking narratives
Agreements
Agreement Points
AI can automate large‑scale information processing for diplomats, freeing them for higher‑level analysis while final decisions remain human.
Speakers: Raphael Leuner, Norman Schulz
AI supports negotiation preparation by processing large document sets (Raphael) AI frees diplomats from tedious data‑consumption tasks, but decisions remain human (Norman)
Both speakers state that AI helps handle massive document collections – supporting negotiation prep (Raphael) and easing data consumption (Norman) – but emphasise that diplomatic decisions will still be made by humans. [130-133][257-259]
POLICY CONTEXT (KNOWLEDGE BASE)
The potential of algorithmic diplomacy to support foreign-policy analysis has been highlighted, but experts stress that human judgment must remain central to avoid biased or incomplete conclusions [S49][S50].
Open‑source and domestically developed AI are preferred to avoid strategic dependence on foreign (especially Chinese) models.
Speakers: Raphael Leuner, Norman Schulz
Prioritising open‑source AI reduces dependence on external vendors, but Chinese open‑source models pose strategic concerns (Raphael) Developing AI domestically ensures alignment with national values and avoids foreign model biases (Norman)
Both argue for using open-source or in-house AI to maintain strategic autonomy, noting the rise of Chinese open-source models as a risk. [128-136][157-158]
POLICY CONTEXT (KNOWLEDGE BASE)
Policy papers argue that open-source AI reduces reliance on single foreign providers and mitigates strategic risk, a stance echoed in the U.S. AI Action Plan and calls for diversification of AI sources [S39][S40][S57][S41].
Middle powers such as Germany and India should cooperate on sector‑specific, non‑frontier AI projects and co‑develop open‑source models.
Speakers: Raphael Leuner, Shyam Krishnakumar, Gunda Ehmke, Shahani Yaktiyami
Joint development of non‑frontier AI projects can strengthen both countries’ positions (Raphael) Cooperation opportunities exist in industrial AI and healthcare, combining German data/automation expertise with Indian model‑building capacity (Shyam) Open‑source AI models should be co‑developed by middle powers like India and Germany rather than relying on models from strategic rivals (Gunda) Middle powers can leverage AI through regulation (Germany) and application‑focused strategies (India) (Shahani)
All four speakers see value in Germany-India collaboration on practical AI applications (e.g., industrial AI, healthcare) and in jointly building open-source models, leveraging each country’s comparative strengths while avoiding reliance on frontier-model leaders. [202-213][108-119][200-201][48-50]
POLICY CONTEXT (KNOWLEDGE BASE)
Initiatives like the France-India trusted-AI bridge and South-global inclusive AI norms illustrate how middle powers can jointly develop sector-focused, open-source solutions while preserving strategic autonomy [S53][S52][S41].
AI introduces security and sovereignty risks that require international, inclusive governance and cooperation.
Speakers: Norman Schulz, Shahani Yaktiyami
International cooperation is needed to mitigate AI risks, analogous to nuclear‑era agreements (Norman) Germany leads the Global Digital Compact and the UN AI scientific panel to ensure inclusive governance (Norman) AI deployment must factor security and sovereignty risks specific to each country (Shahani)
Norman stresses the need for multilateral risk-mitigation frameworks (drawing on nuclear-era lessons) and highlights Germany’s role in the Global Digital Compact and UN AI panel, while Shahani points out country-specific security and sovereignty considerations, together underscoring the necessity of inclusive global governance. [66-76][166-184][141-148]
POLICY CONTEXT (KNOWLEDGE BASE)
Reports on sovereign AI emphasize the need to manage critical control points and call for inclusive, multilateral governance frameworks to address security and sovereignty challenges [S42][S46][S47][S48].
AI can be weaponised to spread biased or false narratives, but it also offers tools for bias detection; human oversight remains essential.
Speakers: Raphael Leuner, Norman Schulz, Shahani Yaktiyami
AI is already being used as a tool for propaganda; continuous monitoring is required (Raphael) AI can be employed to detect and mitigate bias in media and diplomatic narratives (Norman) AI should not autonomously shape geopolitical narratives; human oversight is essential (Shahani)
All three agree that AI poses a double-edged risk: it can amplify disinformation (Raphael) yet also provide bias-detection capabilities (Norman), and therefore must be supervised by humans to prevent harmful narrative shaping (Shahani). [295-298][288-292][277-280]
POLICY CONTEXT (KNOWLEDGE BASE)
Studies show AI models inherit biases from training data, enabling both misinformation and bias-detection capabilities, underscoring the necessity of human oversight and risk-assessment mechanisms [S45][S50][S54][S60].
Similar Viewpoints
Both highlight that AI is now a central, recurring factor in diplomatic practice, continuing a long‑standing pattern where new technologies reshape foreign policy. [28-32][36-40]
Speakers: Gunda Ehmke, Shahani Yaktiyami
AI has become pervasive in the political landscape, influencing diplomacy and foreign policy. AI continues the historic pattern of technology shaping diplomacy; tactics are not new.
Both anticipate a rapid scaling of AI use within diplomatic institutions, with the technology handling routine analysis while humans retain decision authority. [211-212][257-259]
Speakers: Raphael Leuner, Norman Schulz
AI adoption in the Foreign Office is expected to expand significantly over the next five years. AI frees diplomats from tedious data‑consumption tasks, but decisions remain human.
Unexpected Consensus
Both diplomatic and policy‑analysis perspectives converge on the need for an inclusive, multilateral AI governance architecture despite their different institutional roles.
Speakers: Norman Schulz, Shahani Yaktiyami
Germany leads the Global Digital Compact and the UN AI scientific panel to ensure inclusive governance (Norman) AI deployment must factor security and sovereignty risks specific to each country (Shahani)
It is notable that a senior diplomat (Norman) and a policy analyst (Shahani) both stress the importance of inclusive, global governance mechanisms (UN AI panel, Global Digital Compact) to manage AI risks, indicating cross-sectoral alignment on multilateral solutions. [166-184][141-148]
POLICY CONTEXT (KNOWLEDGE BASE)
Multiple policy analyses call for a structured, inclusive global AI governance architecture that balances diplomatic and regulatory insights within multilateral institutions [S46][S47][S48][S55].
Overall Assessment

The panel shows strong convergence on four main themes: (1) AI as a supportive tool for processing diplomatic information while preserving human decision‑making; (2) a shared preference for open‑source or domestically built AI to safeguard strategic autonomy; (3) consensus that Germany and India, as middle powers, should co‑develop sector‑specific, non‑frontier AI applications and open‑source models; (4) agreement that AI’s security, sovereignty and bias risks demand inclusive, multilateral governance frameworks. These points cut across artificial intelligence, capacity development, the enabling environment for digital development, and governance/security topics.

High – the speakers largely align on strategic priorities and risk‑mitigation approaches, suggesting a solid foundation for coordinated Indo‑German initiatives and for shaping broader multilateral AI governance.

Differences
Different Viewpoints
Use of open‑source AI models versus the need for domestically‑developed models to avoid strategic dependence
Speakers: Raphael Leuner, Norman Schulz, Shahani Yaktiyami
Prioritising open‑source AI reduces dependence on external vendors, but Chinese open‑source models pose strategic concerns (Raphael) Developing AI domestically ensures alignment with national values and avoids foreign model biases (Norman) There is a need to develop Indian open‑source alternatives to counter the dominance of Chinese models (Shahani)
Raphael argues that the Foreign Office should rely on open-source AI, even though many leading models now come from China, seeing this as a pragmatic way to accelerate deployment [128-136]. Norman counters that the safest way to align AI with national values is to build it in-house, warning that Chinese models embed their own ways of thinking [157-158]. Shahani adds that India should create its own open-source alternatives to reduce reliance on Chinese offerings [224-237]. The speakers therefore disagree on whether using existing open-source models (including Chinese) is acceptable or whether new domestic models are required.
POLICY CONTEXT (KNOWLEDGE BASE)
Debates centre on whether open-source AI reduces or creates vulnerabilities, with some policymakers advocating domestic development to safeguard strategic assets while others promote openness for resilience [S39][S57][S41].
Whether AI should be allowed to shape geopolitical narratives or only be used for bias detection and support
Speakers: Shahani Yaktiyami, Norman Schulz, Raphael Leuner
AI should not autonomously shape geopolitical narratives; human oversight is essential (Shahani) AI can be employed to detect and mitigate bias in media and diplomatic narratives (Norman) AI is already being used as a tool for propaganda; continuous monitoring is required (Raphael)
Shahani maintains that narratives must remain under human control and warns against AI-generated geopolitics [277-280]. Norman acknowledges AI’s risk but emphasizes its role in detecting bias and assisting humans, while also cautioning against AI-written diplomatic reports [288-292][159-164]. Raphael points out that actors already exploit AI to amplify messages and create fake websites, highlighting a security risk [295-298]. The disagreement lies in the permissible role of AI: Shahani limits it to human-only narrative creation, Norman sees a supportive but limited role, and Raphael highlights current misuse.
POLICY CONTEXT (KNOWLEDGE BASE)
Algorithmic diplomacy discussions raise concerns about AI-driven narrative shaping versus its role as a bias-detection aid, highlighting the tension between influence and oversight [S49][S45][S50].
Priority of global cooperation versus domestic rapid development for AI governance and risk mitigation
Speakers: Norman Schulz, Raphael Leuner, Shahani Yaktiyami
International cooperation is needed to mitigate AI risks, analogous to nuclear‑era agreements (Norman) Fast co‑creation via data labs enables rapid AI solutions (Raphael) Middle powers can leverage AI through regulation (Germany) and application‑focused strategies (India) (Shahani)
Norman draws parallels with nuclear arms control and calls for international agreements to manage AI risks [66-76]. Raphael emphasizes internal fast-co-creation within German data labs as the main advantage for AI deployment, focusing on speed over broader governance [18-23]. Shahani proposes that middle powers should use their comparative strengths-Germany’s regulatory expertise and India’s application focus-to shape AI governance without relying on great-power competition [48-50]. The speakers disagree on whether the primary path forward is global regulatory cooperation, rapid domestic innovation, or a middle-power-focused regulatory-application mix.
POLICY CONTEXT (KNOWLEDGE BASE)
Policy literature contrasts the push for swift national AI capability building with the imperative for coordinated international governance, stressing strategic diversification and sovereignty considerations [S41][S42][S55][S56].
Historical claim that AI tactics are not new versus the view that they are new
Speakers: Shahani Yaktiyami, Norman Schulz
The tactics aren’t new (Shahani) The short answer would be no (to the statement that tactics aren’t new) (Norman)
Shahani asserts that while AI is a new technology, the diplomatic tactics it enables have long historical precedents, citing past revolutions [36-40][42]. Norman directly rejects this claim, answering “no” to Gunda’s question about the statement, implying that AI introduces genuinely new tactics [59]. This constitutes a clear disagreement on the novelty of AI-driven diplomatic tactics.
POLICY CONTEXT (KNOWLEDGE BASE)
Analysts note that while AI technology is novel, many underlying influence tactics have historical precedents, a perspective articulated in recent diplomatic summits [S43].
Unexpected Differences
Interpretation of the statement that "the tech is new, but the tactics aren’t"
Speakers: Norman Schulz, Shahani Yaktiyami
The short answer would be no (Norman) The tactics aren’t new (Shahani)
The panelists unexpectedly diverged on a seemingly straightforward historical claim. While Shahani emphasized continuity of diplomatic tactics across technological revolutions, Norman directly contradicted her, suggesting that AI introduces novel tactics. This disagreement was not anticipated given the broader consensus on AI’s transformative potential.
POLICY CONTEXT (KNOWLEDGE BASE)
The same observation about the continuity of tactics despite emerging AI capabilities has been used to frame policy debates on the need for governance that addresses enduring influence methods [S43].
Overall Assessment

The discussion revealed substantive disagreements on three main fronts: (1) the strategic choice between using existing open‑source AI models (including Chinese) versus building domestic alternatives; (2) the permissible role of AI in shaping diplomatic narratives versus merely detecting bias; (3) the priority of global multilateral governance versus rapid domestic innovation or middle‑power‑focused strategies. Additionally, there was a clear split on whether AI introduces new diplomatic tactics. While participants shared the overarching goal of leveraging AI for diplomatic advantage, they diverged sharply on the pathways to achieve it.

High – The disagreements span strategic, technical, and normative dimensions, indicating that consensus on AI governance and deployment strategies among the panelists is limited. This fragmentation could hinder coordinated policy actions and suggests that further dialogue is needed to reconcile differing national priorities and risk assessments.

Partial Agreements
All three agree that AI must be harnessed to strengthen diplomatic capacity, but differ on the primary mechanism: Raphael stresses internal rapid development, Norman stresses multilateral risk‑mitigation agreements, and Shahani stresses a middle‑power blend of regulation and application focus. The shared goal is effective, secure AI use in diplomacy, yet the pathways diverge.
Speakers: Raphael Leuner, Norman Schulz, Shahani Yaktiyami
Fast co‑creation via data labs enables rapid AI solutions (Raphael) International cooperation is needed to mitigate AI risks, analogous to nuclear‑era agreements (Norman) Middle powers can leverage AI through regulation (Germany) and application‑focused strategies (India) (Shahani)
All three want to reduce reliance on external strategic rivals for AI. Gunda proposes Indo‑German co‑development, Raphael supports open‑source use while noting Chinese dominance, and Norman advocates domestic development to ensure value alignment. They share the objective of strategic independence but propose different collaborative or national approaches.
Speakers: Gunda Ehmke, Raphael Leuner, Norman Schulz
Open‑source AI models should be co‑developed by middle powers rather than relying on strategic rivals (Gunda) Prioritising open‑source AI reduces dependence on external vendors, but Chinese open‑source models pose strategic concerns (Raphael) Developing AI domestically ensures alignment with national values and avoids foreign model biases (Norman)
Takeaways
Key takeaways
The German Foreign Office uses fast, internal co‑creation via data labs to develop AI tools quickly, especially for processing large document sets and supporting negotiations. AI is viewed as a diplomatic tool that can automate tedious information‑processing tasks, freeing diplomats for higher‑level analysis and relationship‑building, while final decisions remain human. Historically, technology shapes diplomacy; AI continues this pattern, but the tactics (competition, regulation) are familiar. Middle powers such as Germany and India can leverage AI through regulation (Germany) and application‑focused strategies (India), rather than trying to win the frontier AI race. International cooperation and inclusive governance (e.g., the UN Global Digital Compact and the Independent Scientific Panel on AI) are seen as essential to manage AI risks, similar to nuclear‑era agreements. Open‑source AI is preferred to reduce dependence on external vendors; however, the prevalence of Chinese open‑source models raises strategic concerns, prompting calls for Indo‑German alternatives. Sector‑specific cooperation (industrial AI, healthcare, robotics) is identified as a practical avenue for Indo‑German collaboration, combining German data/automation expertise with Indian model‑building capacity. AI should not autonomously shape geopolitical narratives; human oversight is required, and AI can be used to detect and mitigate bias in media. AI is already being weaponised for propaganda and misinformation, necessitating continuous monitoring by diplomatic services.
Resolutions and action items
German Foreign Office commits to using open‑source technologies and re‑using existing state applications for AI projects. Proposal to pursue joint Indo‑German AI projects in industrial automation and healthcare, leveraging complementary strengths. Support for the Global Digital Compact and participation in the UN Independent Scientific Panel on AI to promote inclusive, science‑based AI governance. Agreement to monitor and counter AI‑driven misinformation and propaganda as part of diplomatic work.
Unresolved issues
Specific mechanisms for ensuring AI systems align with national values and security/sovereignty requirements remain undefined. How to develop and scale non‑frontier, open‑source AI models that can serve as alternatives to Chinese offerings is not yet resolved. Details of concrete Indo‑German cooperation frameworks, funding, and governance structures were discussed but not finalized. Implementation pathways for AI‑driven bias detection tools in media and diplomatic analysis need further elaboration. The broader question of how to balance rapid AI innovation with regulatory oversight across middle powers remains open.
Suggested compromises
Adopt a middle‑power strategy focused on sector‑specific collaboration rather than competing for frontier AI dominance. Utilise open‑source AI to democratise access while jointly developing Indo‑German models to reduce reliance on any single external source. Pursue managed interdependence: each country contributes its strengths in the AI stack (e.g., Germany’s data/automation, India’s model‑building) without creating dependency. Combine regulation (German approach) with application‑driven innovation (Indian approach) to achieve balanced AI governance.
Thought Provoking Comments
We used to have IT development projects that take two years, have huge teams, cost a lot of money, but that are just not fast enough to deliver on an AI solution that our colleagues are already experiencing in their private lives.
Highlights the mismatch between traditional bureaucratic IT cycles and the rapid pace of AI development, emphasizing the need for agile, in‑house co‑creation within ministries.
Set the practical tone of the discussion, prompting other panelists to consider speed and internal collaboration as critical factors for AI adoption in diplomacy.
Speaker: Raphael Leuner
The technology is not new. Yes. But the tactics aren’t. AI is the latest tool in a long history where technology shapes diplomacy—from the Industrial Revolution to the nuclear age.
Challenges the notion that AI is a completely novel disruptor, reframing it as a continuation of historical tech‑driven diplomatic shifts while stressing new strategic tactics.
Shifted the conversation from a purely technical focus to a geopolitical and historical perspective, leading to deeper discussion on middle‑power strategies and value‑chain leverage.
Speaker: Shahani Yaktiyami
Middle powers like India and Germany can express power on the AI value chain: Germany through rules and regulation, India through applications and deployment.
Introduces the concept that countries not leading in frontier AI can still exert influence by focusing on regulatory frameworks or sector‑specific applications.
Prompted subsequent speakers (e.g., Norman and Shyam) to explore concrete cooperation avenues and the role of regulation versus innovation in AI diplomacy.
Speaker: Shahani Yaktiyami
The best way to align AI systems with our values is to develop them ourselves, not just procure them from outside—even if they are open‑source Chinese models.
Raises sovereignty and ethical concerns, arguing for domestic development to maintain control over AI’s underlying biases and strategic implications.
Steered the dialogue toward the importance of indigenous AI capabilities, influencing Raphael’s later remarks on open‑source models and the need for alternative (e.g., Indian) solutions.
Speaker: Norman Schulz
Open‑source is a democratizing force—think of the 1990s open‑source OS revolution. By collaborating as middle powers we can reduce costs and spread access to AI.
Draws a historical parallel to illustrate how open‑source can level the playing field, suggesting a practical pathway for Indo‑German cooperation.
Expanded the conversation from high‑level geopolitics to actionable collaboration models, leading to discussion of sectoral projects like healthcare and industrial AI.
Speaker: Shyam Krishnakumar
We see a lot of AI models from China being adopted globally; it’s important for countries like India and Germany to develop their own models to offer alternatives.
Points out the geopolitical risk of dependence on Chinese AI, linking model provenance to strategic autonomy.
Reinforced Norman’s sovereignty argument and motivated the panel to consider building a diversified, multi‑regional AI ecosystem.
Speaker: Raphael Leuner
AI cannot replace human diplomatic creativity; it can summarize and replicate, but innovative thinking must come from people.
Counters the hype that AI will automate diplomatic analysis, emphasizing the irreplaceable human element in policy formulation.
Grounded the discussion in realistic expectations, influencing the audience Q&A about automation and reinforcing the theme of AI as a tool, not a decision‑maker.
Speaker: Norman Schulz
I would not let AI shape narratives. If we allow AI to do that, we risk bias and manipulation; we must instead develop mitigation strategies and use AI to detect bias.
Raises ethical concerns about AI‑generated propaganda and stresses the need for human oversight and bias‑detection tools.
Prompted a rapid exchange on media influence, leading Raphael to note AI’s role in amplifying fake narratives and highlighting the dual‑use nature of the technology.
Speaker: Shahani Yaktiyami
Overall Assessment

The discussion was driven forward by a series of pivotal insights that moved it from a surface‑level overview of AI tools to a nuanced debate about geopolitical strategy, sovereignty, and ethical governance. Raphael’s emphasis on agile, internal co‑creation highlighted operational challenges, while Shahani’s historical framing and middle‑power lens reframed AI as a diplomatic lever rather than a mere technology. Norman’s sovereignty argument and calls for domestic development introduced a critical security dimension, which Raphael and Shyam reinforced by pointing to the dominance of Chinese open‑source models and the democratizing potential of open‑source collaboration. Together, these comments redirected the conversation toward concrete Indo‑German cooperation, sector‑specific applications, and the limits of AI in shaping policy and narratives, ultimately shaping a balanced view of AI as both an opportunity and a risk for foreign ministries.

Follow-up Questions
What concrete use cases of AI can be applied in diplomacy and foreign policy?
Understanding practical applications will help ministries move from theory to implementation.
Speaker: Gunda Ehmke
How should AI be governed within the German Foreign Ministry and is the current approach adequate?
Effective governance frameworks are needed to ensure responsible AI use in diplomacy.
Speaker: Gunda Ehmke (question), Norman Schulz (response)
What specific areas of Indo‑German cooperation in AI (e.g., industrial AI, healthcare AI) are most promising?
Identifying concrete bilateral projects can leverage complementary strengths of both countries.
Speaker: Gunda Ehmke (prompt), Shyam Krishnakumar (response)
Can open‑source AI be a viable solution for foreign ministries, and what are the security implications of relying on Chinese open‑source models?
Evaluating open‑source options is crucial for cost‑effectiveness and sovereignty concerns.
Speaker: Raphael Leuner
How can the discussion on AI impact be turned into concrete, actionable cooperation rather than just governance frameworks?
Moving from high‑level dialogue to implementation steps is needed to realize AI benefits.
Speaker: Gunda Ehmke (prompt), Shahani Yaktiyami (response)
What are the details of the Global Digital Compact and the Independent Scientific International Panel on AI, and how can we ensure AI systems align with democratic values?
Clarifying these mechanisms will help embed values and inclusivity into global AI governance.
Speaker: Gunda Ehmke (prompt), Norman Schulz (response)
Which parts of foreign‑policy research, decision‑making and implementation can be automated by AI?
Identifying automation opportunities can increase efficiency for diplomats and analysts.
Speaker: Audience member Sreeni (question)
Will AI help create more unbiased media narratives, and how can potential bias be mitigated?
Understanding AI’s influence on information flows is vital for democratic discourse and security.
Speaker: Audience member Sanjeevni (question), Shahani Yaktiyami, Norman Schulz, Raphael Leuner (responses)
How should geopolitical risk be assessed when adopting open‑source AI models from countries like China?
Risk assessment is needed to prevent unintended strategic dependencies.
Speaker: Raphael Leuner (implied), Norman Schulz (implied)
Can Indian open‑source large language models serve as alternatives to Chinese models for Europe and other partners?
Diversifying model sources could reduce reliance on any single geopolitical bloc.
Speaker: Raphael Leuner
Should foreign ministries develop sovereign AI capabilities in‑house to ensure alignment with national values?
Building domestic AI may safeguard against external influence and ensure value alignment.
Speaker: Norman Schulz
How can the concept of ‘managed interdependence’ replace traditional sovereignty debates in AI governance?
A nuanced framework could better reflect the interconnected AI ecosystem.
Speaker: Shahani Yaktiyami
What will be the outcomes of the upcoming UN AI dialogue in Geneva and how will they shape global AI governance?
Monitoring the dialogue’s results will inform future policy and cooperation strategies.
Speaker: Norman Schulz (implied)
What bias‑detection technologies and mitigation strategies are needed to address AI‑driven misinformation and narrative manipulation?
Technical tools are required to counteract AI‑enabled bias and protect democratic processes.
Speaker: Shahani Yaktiyami

Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.