Indias AI Leap Policy to Practice with AIP2
20 Feb 2026 14:00h - 15:00h
Indias AI Leap Policy to Practice with AIP2
Summary
The panel discussed AI diffusion in the Global South and unveiled a practical “Global South AI Diffusion Playbook” as a guide [39-44]. Doreen Bogdan-Martin urged flexible, inclusive, human-centred AI, citing India’s multilingual public-service platform as a model [1-9]. She presented three pillars-Solutions, Skills, Standards-stating that connectivity is essential and noting ITU’s GIGA school-connectivity goal [12-15][15-19]. On skills, she highlighted India’s Future Skills Program and ITU’s Skilling Coalition, offering 180 resources in 13 languages via 70 partners [20-26]. For standards, she cited the voluntary AI Standards Exchange Database with over 850 standards, including deep-fake authenticity rules [27-33]. Dr. Panneerselvam called deep-tech startups “AI natives” that bring expertise and agility, and noted METI’s mentorship, market access and funding up to a thousand crores [54-66]. He described startups as the “AI bridge” linking technology to business needs, especially for SMEs facing technology overshoot [82-84]. Brando Benefi said the EU AI Act sets clear limits for high-risk AI, building trust while leaving low-risk uses unregulated [116-124]. Rachel Adams reported that two-thirds of South Africans lack meaningful AI understanding, creating a democratic gap that demands governance and participation [134-146]. Fred Werner highlighted AI-for-good projects like a voice-based blood-sugar estimator and argued that standards are needed for safety, ethics and interoperability while closing the skills gap [148-156][165-173][174-181]. When asked how to spend a billion dollars, Fred prioritized education, Brando called for AI literacy and civil-society capacity, and Rachel urged investment in state institutions to protect labour and human rights [217][219-220][221-223]. The panel concluded that sustained global cooperation, coordinated standards and capacity-building are essential to turn AI pilots into equitable, scalable solutions worldwide [230-232][233].
Keypoints
Major discussion points
– Inclusive AI diffusion requires three coordinated “S” pillars – solutions, skills, and standards.
Doreen outlines that building infrastructure (solutions) is essential because “without connectivity there is no AI” [13-15]; she stresses the “fundamental importance of skills” and cites India’s Future Skills Program and the ITU Skilling Coalition [20-24]; and she highlights standards for interoperability and trust, noting the AI Standards Exchange Database with over 850 standards [26-32]. She concludes that diffusion is about “giving everyone the same bridge to opportunity” [34-36].
– Start-ups are the engine that can turn AI pilots into scalable impact, especially in India.
Dr. Panneerselvam describes startups as “AI natives” with talent and agility that can transform SMEs and large enterprises [54-57]; METI Startup Hub provides “mentorship, market access and money” to nurture them [61-66]; he notes the availability of massive funding (≈ ₹ 1,000 crores from METI and ₹ 8,000 crores from the India AI Mission) [69-71]; and he frames startups as the “AI bridge” linking technology to business needs [77-83].
– Trust, ethics, and clear governance are prerequisites for diffusion and must be locally grounded.
Brando points to the EU AI Act as a reference for defining high-risk areas, building trust, and setting clear boundaries [116-119]; he warns that without precise frameworks AI can be used for “mass surveillance” and other non-democratic purposes [202-208]; Rachel adds that a “democratic gap” exists because two-thirds of South Africans lack meaningful AI understanding, making governance and public participation essential [127-144]; both stress that standards alone are insufficient without ethical and regulatory clarity [170-176].
– Skills development and education are the top investment priority for accelerating diffusion in developing economies.
Doreen’s earlier emphasis on skilling (Future Skills Program, Skilling Coalition) [20-24] is echoed by Fred, who says that a billion-dollar boost should first target “education skills” across the learning pipeline [217-218]; the consensus across speakers is that closing the skills gap is the most effective way to unlock AI benefits.
– Global cooperation and inclusive standard-setting are needed to avoid a one-size-fits-all approach.
Fred describes rapid coordination of the International AI Standards Summit Series and the AI Standards Exchange Database [170-176]; Rachel warns that past standard-setting has been dominated by well-resourced actors and calls for deliberate funding and representation from Africa, Latin America, and Asia [190-196]; Brando reinforces the need for “global cooperation” and shared understanding [230-232].
Overall purpose / goal of the discussion
The session was convened to launch the Global South AI Diffusion Playbook and to move the conversation from high-level “moonshot” policies to concrete, inclusive actions that enable AI to reach people, businesses, and governments in the Global South. Participants examined how infrastructure, skills, standards, startup ecosystems, and governance can be aligned to create a practical roadmap for equitable AI adoption.
Overall tone and its evolution
– The discussion opens with a hopeful, solution-oriented tone (Doreen’s “bridge to opportunity” [34-36]).
– It then becomes enthusiastic and entrepreneurial as Dr. Panneerselvam celebrates the startup model [54-66].
– Mid-conversation the tone shifts to cautious and critical, focusing on trust, ethics, and the risk of misuse [116-119][127-144].
– Later, the tone turns pragmatic and collaborative, emphasizing concrete actions such as skills investment and inclusive standards [217-218][170-176].
– The closing remarks return to an optimistic, cooperative tone, urging continued global partnership and shared learning [230-232].
Overall, the dialogue remains constructive, moving from optimism to a balanced acknowledgment of challenges, and ending with a reaffirmed commitment to collective action.
Speakers
– Doreen Bogdan-Martin
– Role/Title: Secretary-General, International Telecommunication Union (ITU)
– Area of Expertise: Digital connectivity, AI diffusion, standards, global telecom policy
– Citation: [S16]
– Moderator
– Role/Title: Session moderator / host of the panel discussion
– Area of Expertise: Event facilitation (no specific title provided)
– Dr. Panneerselvam Madanagopal
– Role/Title: CEO, METI Startup Hub (Ministry of Electronics & Information Technology, Government of India)
– Area of Expertise: Startup ecosystem, deep-tech incubation, AI commercialization, entrepreneurship
– Citation: [S10]
– Fred Werner
– Role/Title: Chief of Strategy and Operations for AI for Good; Chief of Strategic Engagement, ITU
– Area of Expertise: AI for Good initiatives, AI standards development, international AI governance
– Citation: [S13]
– Brando Benefi
– Role/Title: Member of the European Parliament (MEP), Italy; Co-reporter of the EU AI Act
– Area of Expertise: European AI policy, AI regulation, digital rights, standards implementation
– Citation: [S7]
– Rachel Adams
– Role/Title: Founder and CEO, Global Center on AI Governance
– Area of Expertise: AI governance, human rights & equity in AI, policy research, AI ethics
– Citation: [S1]
Additional speakers:
– Dr. Bani-Selvan – mentioned in the moderator’s introduction; no further role or expertise details provided in the transcript or external sources.
The moderator opened the session by announcing the Global South AI Diffusion Playbook, positioning it as a practical guide that moves the conversation from lofty “moonshots” to concrete, inclusive actions across five inter-related dimensions [39-44]. This set the stage for a dialogue focused on turning AI ambition into equitable, real-world impact.
Doreen Bogdan-Martin began by emphasizing that AI must generate tangible benefits for homes, communities and businesses and that a “one-size-fits-all” approach is unsuitable [1-2]. She called for flexibility, inclusivity and a human-centred stance that respects each country’s development stage [3-5]. Citing India as a model, she highlighted the Bishini platform, which delivers government services in 22 languages and reaches rural, low-skill populations [6-9].
She then outlined a four-pillar framework – Solutions, Skills, Opportunities and Standards [10-13].
* Solutions – Connectivity is the foundation of AI diffusion. Doreen referenced the ITU-UNICEF GIGA school-connectivity initiative, which aims for 100 billion commitments to connect the hardest-to-connect schools, with 80 billion already pledged [13-15]. She added that this work is carried out in partnership with the Digital Coalition, the body dedicated to reaching the most remote schools [16-18].
* Skills – She pointed to India’s Future Skills Programme and the ITU Skilling Coalition, now comprising about 70 partners and offering more than 180 learning resources in 13 languages [20-26].
* Opportunities – Doreen described AI-driven market-shaping, innovative financing mechanisms and ecosystem incentives that can unlock new economic possibilities for the Global South [27-30].
* Standards – The AI Standards Exchange Database now hosts over 850 standards, including multimedia-authenticity rules to combat deep-fakes. ITU standards are voluntary and developed through an inclusive, multi-stakeholder process [31-34].
She concluded that diffusion is not about everyone using the same technology but about providing “the same bridge to opportunity” and preventing a digital-divide-becoming-AI-divide [35-36], reaffirming ITU’s role as a trusted partner [37-38].
The moderator reiterated that the Playbook’s five dimensions are intended to guide implementation rather than dictate strategy, underscoring the shift from aspirational moonshots to reliable, inclusive AI deployment [42-44].
Dr Panneerselvam Madanagopal positioned start-ups as the engine that can translate AI pilots into scalable economic impact. He described them as “AI natives” with deep technical talent and the agility to serve both SMEs and large corporations [54-57]. He framed the METI Startup Hub as the custodian of deep-tech start-ups and repeatedly used the phrase “AI bridge” to describe its role in linking technology with business needs [58-60]. The Hub delivers the three M’s – Mentorship, Market access and Money – supporting ventures from ideation through commercial development, facilitating customer acquisition (the best investment for a start-up) and providing up to INR 1,000 crore in funding, complemented by an additional INR 8,000 crore from the India AI Mission [61-70]. He stressed that there is “no death of capital” in the Indian market because both government and private funds are available [71-73]. Describing the event itself, he called it an “AI earthquake” happening in Bharat Mandapam, warning that such a seismic shift brings great responsibility [112-115]. He warned that many SMEs suffer from “technology overshoot” – a mismatch between available AI tools and firms’ capacity to integrate them [77-84], and argued that the start-up ecosystem is the essential AI bridge for turning laboratory breakthroughs into market-ready solutions [82-84].
The moderator highlighted the start-up ecosystem as the transmission mechanism that can move AI from capability to real economic impact [45].
Brando Benefi shifted the focus to trust, ethics and governance. He presented the EU AI Act as a reference model that explicitly defines high-risk AI applications-including predictive policing, emotional-recognition in workplaces and manipulative subliminal techniques-while leaving lower-risk uses under existing legislation, thereby fostering trust without unduly restricting innovation [116-124]. He warned that without precise, enforceable frameworks AI could be misused for mass surveillance and repression in fragile, institutionally weak contexts [202-208]. Benefi argued that ethical statements alone are insufficient; clear, binding, time-bound standards are needed so that governance can be implemented before the technology outpaces regulation [205-209]. To illustrate a positive use case, he cited an Italian company that monitors driver fatigue to prevent accidents, showing how AI can serve public safety [120-122].
Rachel Adams provided empirical evidence of a democratic gap in AI awareness: two-thirds of South Africans lack a meaningful grasp of AI – a third have never heard of it and another third cannot explain it [127-136]. She warned that this knowledge deficit hampers public participation in AI-related decision-making and creates a risk of unchecked deployment in public services [137-146]. Rachel called for capacity-building in standards-setting, noting that processes have been dominated by well-resource-rich actors and urging deliberate funding, leadership and co-authorship from the Global South [188-196].
Fred Werner illustrated AI-for-good applications, describing an Estonian start-up that estimates blood-sugar levels from voice patterns on a mobile phone – a potential game-changer for diabetes management [148-156]. He stressed that such innovations must be evaluated for safety, ethics, human-rights compliance and sustainability, and that standards are a practical tool for embedding these safeguards [165-170]. Werner highlighted the rapid coordination of the International AI Standards Summit Series and the launch of the AI Standards Exchange Database within three weeks of the Global Digital Compact call, demonstrating that standards development can be swift when political will exists [173-176]. He also noted ongoing work on deep-fake detection standards with industry partners, while reaffirming that the AI skills gap remains a major barrier worldwide [177-181].
Agreements
All speakers concurred on several points:
* Skills and digital literacy are prerequisites for diffusion – Doreen’s Skilling Coalition [20-23]; Fred’s emphasis on education as the starting point for a billion-dollar investment [217-218]; Brando’s call for AI literacy and civil-society capacity [219-220]; Rachel’s survey-based evidence of widespread AI ignorance [130-136].
* Standards are essential for trustworthy, interoperable AI – Doreen’s AI Standards Exchange Database [31-34]; Fred’s rapid-development model [173-176]; Brando’s insistence on enforceable, time-bound standards [205-209]; Rachel’s demand for inclusive, South-led standard-setting [188-196].
* Diffusion must be inclusive and bridge the digital divide – Doreen’s “bridge to opportunity” metaphor [35-36]; the moderator’s call for universal participation [40]; Brando’s warning against vague ethical frameworks [205-209].
* Start-ups are the key transmission mechanism – highlighted by the moderator and Dr Madanagopal [45][54-56].
Disagreements
* Nature of standards – Doreen described ITU standards as voluntary and multi-stakeholder [31-34], whereas Brando argued that voluntary pledges are inadequate and that enforceable, time-bound standards are required [205-209]; Fred’s rapid-development approach suggests a middle ground but does not resolve the enforceability question [173-176].
* Allocation of a hypothetical $1 billion fund – Fred prioritised education and skills [217-218]; Brando advocated for AI literacy and civil-society capacity [219-220]; Rachel added investment in state institutions that safeguard labour and human rights [221-223].
* Primary lever for diffusion – the moderator and Dr Madanagopal championed start-ups; Doreen emphasised the four-S framework; Fred focused on education and standards; Brando on precise regulation; Rachel on participatory governance [45][54-56][10-13][20-26][31-34][116-124][127-146].
Key Takeaways
1. AI diffusion rests on four coordinated pillars – Solutions (connectivity), Skills (digital agency), Opportunities (market-shaping & financing) and Standards (trust & interoperability) [13-15][20-26][27-30][31-34].
2. An inclusive, human-centred approach that adapts to varied development contexts is essential [3-5][35-36].
3. India’s large-scale digital initiatives (digital ID, financial inclusion, multilingual public services) provide a concrete model for scaling AI responsibly [6-9][41-44].
4. Start-ups act as the catalyst, offering Mentorship, Market access and Money, and serving as the AI bridge between technology and business needs [61-66][77-84].
5. Trust, ethics and governance are critical; the EU AI Act’s high-risk focus and the Italian driver-fatigue example illustrate how clear boundaries can build confidence [116-124][120-122].
6. A significant public-awareness gap exists in many Global South contexts, underscoring the need for digital-literacy programmes [127-136].
7. Rapid, inclusive standards development is feasible, as shown by the AI Standards Summit and Exchange Database [173-176].
8. Funding priorities consistently point to education, civil-society capacity and strengthening democratic institutions [217-223].
Thought-Provoking Comments
* Doreen’s assertion that “solutions, skills, opportunities and standards – we cannot achieve AI for many if a third of humanity is offline” framed the entire conversation [13-15][35-36].
* Dr Madanagopal’s description of the “three M’s” – Mentorship, Market access and Money – highlighted the practical support start-ups need [61-66].
* Brando’s observation that the EU AI Act “identifies high-risk areas … and lets non-included use cases remain unregulated” offered a nuanced regulatory model [116-124].
* Rachel’s revelation that “two-thirds of South Africans do not have a meaningful grasp of AI” exposed a democratic deficit [130-136].
* Fred’s claim that the International AI Standards Summit was launched in “less than three weeks” demonstrated that standards can be developed at “lightning speed” when there is political will [173-176].
Follow-Up Questions for Future Research
* How can SMEs overcome technology overshoot and integrate AI effectively [77-80]?
* What mechanisms can accelerate standards development and counter private-sector resistance [201-209][173-176]?
* How to close the AI literacy gap in the Global South [127-136]?
* How to translate high-level ethics into enforceable, time-bound rules [205-209]?
* How to ensure meaningful Global South participation in standards-setting, including dedicated funding and co-authorship [188-196]?
* Pathways for scaling pilots to large-scale deployment [45]?
* Strategies to address labour displacement and protect human rights [221-223]?
* Ways to mitigate AI-enabled mass surveillance in fragile contexts [202-203]?
Policy Context
The ITU three-S framework was highlighted in regional discussions on AI-ready infrastructure [S32]; the evolution of the AI-for-Good initiative from hype to a year-round movement underscores the importance of practical, collaborative governance [S13]; and the EU AI Act’s targeted high-risk approach aligns with calls for precise, risk-based regulation [S34-35]. The need for inclusive standards reflects concerns that past processes have been dominated by well-resourced actors, a point echoed in recent UN and multilateral reports [S93-94][S95-96].
Conclusion
The panel reaffirmed that AI diffusion must be a coordinated, multi-dimensional effort that simultaneously builds connectivity, cultivates skills, creates market-shaping opportunities and establishes trustworthy standards while leveraging start-ups as the conduit to market. The Global South AI Diffusion Playbook, the continued ITU partnership, the METI Startup Hub’s mentorship and funding programmes, and rapid, inclusive standards-setting mechanisms together constitute the “bridge to opportunity” that can prevent an AI divide and enable equitable, sustainable AI adoption worldwide [35-36][37-38][45][61-66][173-176][219-223]. Ongoing global cooperation and year-round collaboration were identified as essential to translate the Playbook’s guidance into tangible outcomes [230-232][233].
…as to how AI can actually benefit people in their lives, their homes, their communities, and their businesses. The second point that keeps coming up is that it’s not a one -size -fits -all model. I think we do need to be flexible. We need to be inclusive when we look at different AI approaches. I would say for all parts of the world, no matter where countries are in terms of their development journeys. India, as we see, is a leader, really showing how to get from AI ambitions to real results. And, of course, in doing so, keeping people, keeping… …that human -centered approach in focus, as we heard from the Prime Minister yesterday. The Bishini platform… that we’ve also heard about, delivers government services in 22 languages.
I would say as well, similar AI -powered digital public infrastructure solutions in areas from health care to financial inclusion are really working to better serve all Indians, regardless of their economic status, their skill level, especially in rural communities. I would say inspired by these efforts, I wanted to quickly offer three observations, and you’ve actually already referred to them. Three observations about how we can move beyond moonshots from policy to actual practice here in the Asia -Pacific region and beyond. And they all begin with S, and you said them already, solutions, skills, and opportunities. Of course, standards. So Solutions is about building the infrastructure and the platforms that make artificial intelligence accessible because we cannot achieve AI for many.
We can’t achieve AI for all if we still have a third of humanity that is offline. Without connectivity, there is no AI, and that’s why efforts like our school connectivity work with UNICEF called the GIGA initiative to connect every school is so important. Our work in terms of our partner to connect, Digital Coalition, which is about connecting the hardest to connect. We have a target of achieving 100 billion this year. So far, we’re at 80 billion in commitments and pledges to connect the hardest to connect. So we need to tackle that basic infrastructure component. The second element that we need to make sure that we diffuse AI globally in practice is skills. the fundamental importance of skills.
Yesterday I was speaking to a young leader who actually likened connectivity to people feeling that they have digital agency. Skills are that engine of agency. Countries can learn directly from India’s experience of investing in people, namely through its Future Skills Program that’s providing upskilling to support thousands of students at all levels. ITU is also taking a similar approach, and my colleague Fred will be staying on for the panel today. We have a skilling coalition that’s very exciting with some, I think, 70 partners so far, bringing more than 180 different learning resources in 13 languages. And coming to my last S is that standards piece. Ensuring that AI systems work effectively together. Thank you. Standards complement solutions and skills not only for interoperability but also for embedding trust.
As Prime Minister Modi mentioned yesterday, deep fakes and misinformation can destabilize entire societies. And people must be able to distinguish between real and AI -generated material. And that’s why the ITU, together with our partners from ISO and IEC, we created the AI Standards Exchange Database that has over 850 standards and technical publications, including multimedia authenticity standards, that prioritize traceability to combat deep fakes. ITU standards are voluntary. They are developed through an inclusive… multi -stakeholder process. So ladies and gentlemen, AI diffusion isn’t about everyone using the same technology. It’s about giving everyone the same bridge to opportunity and refusing to let the digital divide become an AI divide. So today’s playbook is going to help us really build that bridge, as will our continued cooperation and collaboration on AI solutions, skilling, and standards.
In all of these areas, you can count on ITU as your trusted partner. Thank you.
Thanks, Doreen. As you can see, Doreen has spent her career in ensuring. Every country, every community has access to or is part of digital economy. Could I just invite Doreen, Fred, Rachel, Brando, Dr. Bani -Selvan on the stage as we launch the Global South AI Diffusion Playbook. It’s a framework built around five interacting dimensions, infrastructure, data and trust, institutions for procurement, and skills and market shaping. It’s not designed as a strategy document, but more as an implementation guide, because the next phase of AI is not about moonshots, it’s about how do we ensure AI works reliably, inclusively, and productively for many. This is, I think, the photo op you guys were waiting for, so all yours.
Thank you. Doreen I know you have to leave thank you very much thanks for a great keynote as well thanks Doreenn if diffusion is about moving from capability to real economic impact then startups are obviously the transmission mechanism and a few people understand India startup ecosystem as deeply as Dr. Pani Selvam Madan Gopal CEO of Miti Startup Hub under his leadership Miti Startup Hub has become a key platform connecting government policy with entrepreneurial energy enabling innovations to move from lab to market and from pilot to scale over 6000 plus startups right so he brings over 2 decades of experience and at a moment when India is positioning itself not just as an AI industry but as an AI adopter but as an AI innovation diffusion hub his perspective on enabling startups to scale responsibly and globally particularly valuable.
Doctor, would I just have a few minutes for you.
Thank you, Access Partnership for having me this afternoon for this conversation. I think it’s an important element. How do you know there’s so much happening in the last four to five days in Delhi in Bharat Mandapam. So it’s important to get a grasp of what’s going on. And what each of us have to kind of take away from this and how each stakeholders in this ecosystem can help us. And startups become a very, very important player in this game. And essentially for two or three key reasons. One, they come in as AI natives. They come in with a significant understanding of the technology and the talent is kind of already there and then second they are here to the agility that they bring and the capability they bring to kind of transform businesses is becoming a very very important need for small and medium enterprises and even to large enterprises.
Just prior to this I was having a conversation with a large corporate and how they can actually use startups as a catalyst of change and transformation in their large corporate because the corporates are designed for systems and processes on scale and what need of the hour is actually agility adaptability and more importantly ability to change and bring innovation into a mainstream of any enterprise. So startups play a very very critical role so we at Métis Startup Hub are primarily driving the push to kind of ensure that startups have the wherewithal and the capability to drive and back this change that is required by the corporate ecosystem or the large enterprise ecosystem. So, briefly what do we do at METI Startup Hub?
We are the custodians of the deep tech startups in the country. This whole event has been put together by METI and of course Ministry of External Affairs has been phenomenal partners in this. So, our role in METI Startup Hub is essentially three M’s. Mentorship, market access and money. This is essentially what we provide for startups. We provide mentorship support to the entire journey from almost at an ideation stage to CDC, up to CDC level. And we provide them with market access. I’m a firm believer that your customer is your best investor if you’re a startup. And finding customers for startups is more important than finding investors, right? So, it’s important for me to find, give them the right market access support.
So, we work with large corporates across the board, across the country. when internationally we kind of drive market access support and last but not the least money we provide significant amount of, there is absolutely no death of capital in the Indian market, you know, through my agent, through my organization, MIT Startup Hub, we fund almost up to a thousand crores for startups and the India AI mission has another almost about 8000 crores to be funded for funding for startups. So there is absolutely no death of money in the market, government fund is available, you know, private capital is available, so that’s what we support. And our endeavor is to ensure that startups are at the heart of this renaissance of this change that is kind of happening in the ecosystem and how startups technology can power, help this small and medium enterprises to grow.
So that’s what we are trying to do. Thank you. Thank you. Thank you. journey. So that’s what we have been driving at and conversations like this help a lot and enabling them to drive this change. We have three things I mean there is obviously a lot of challenges. It’s not easier said than done. In some cases I was reading up in a way with medium enterprises we call a technology overshoot. The technology has actually overshot the need and now the ability of the medium enterprises to cope with this technology and say how do I understand what is my need? How do I integrate this into my business need and how do I ensure that this business my business is realigned with a new workflow, a new way of doing business with this current technology with AI or AI based supported technology to kind of drive.
So there is, while there are huge challenges, but every challenge is an opportunity. So, you know, and startups are very well placed to kind of bridge that opportunity because they understand technology and they understand business. So we are hoping to create this, what I call the AI bridge now, which is, you know, kind of bridge the technology and the business need. And it’s going to be a huge opportunity by itself to kind of drive, and startups are what we are hoping will build that bridge and drive the change. So at METI Startup Hub, our endeavor is to nurture, build, and enable tech and deep tech startups in the country. And we partner with all, we collaborate with all stakeholders, domestic and international, to ensure our startups get the right, opportunities and we solve.
problems and we enable capability through building capacity. So that’s essentially in a nutshell what we do and once again I thank the access partners for providing me this opportunity to briefly share my thoughts with you and we are in a cusp of somebody called this an AI earthquake happening in Bharat Mandapam. This is a tectonic shift and this is some laying foundation for something big and better coming our way. Of course with a lot of responsibility also because everything has two sides of its own so we need to be extremely responsible in what we are doing with the technology. Thank you once again. Thank you for the opportunity. Thank you.
As Dr. said, this is really the earthquake of AI and we are at the epicenter. And as you can see, after five days, we are all very, very tired. We started late. We’ll end on time. That’s my promise to you guys. Where is the next chair? So let me introduce our panelists very quickly. Dr. Rachel Adams, she’s the founder and CEO of the Global Center on AI Governance, a leading research and policy institution focused on ensuring that AI development and deployment advance equity and human rights globally. She also advises governments and she was a key contributor to the African Union Commission’s Continental AI Strategy. I have Fred, Fred Werner. He is the Chief of Strategy and Operations for AI for Good and Chief of Strategic Engagement at ITU.
He’s based in Geneva, but as a co -creator of the AI for Good Global Summit. which is happening from 7 to 10 July in Geneva. He brings together a global hub for collaboration standards and actionable AI -driven impact. And I’m also pleased to welcome Brando Benefi, who is a member of European Parliament, and he was a co -reporter of the EU AI Act, which we all love so much, the world’s first comprehensive AI regulation. He is an Italian MEP since 2014, and he has played a key role in shaping European digital and AI policy. Welcome, all of you. Thank you. Quick one, yeah? I’ll really start with you, Brando, in this case. We talked about concrete gains that AI diffusion can unlock in Global South over the next three to five years.
How do we move from pilots to scale deployment? I want to understand a bit more from you. it’s been a while since we have had the EU AI Act. There have been some implementation, obviously, right? So how do you see the AI diffusion being unlocked and how do you see European partnerships with the Global South there?
Well, first of all, I apologize for my voice, but it’s the, I don’t know, work of these days. Maybe we are producing a lot, but this is also the impact, so I apologize for that. But to answer your question, I think that the EU AI Act can be an interesting reference point to reflect on what we can do to implement the idea of a global diffusion, especially looking at the Global South. Because, in fact, even the so -called global north or global minority, we can use different terms, is still struggling with the diffusion of AI among different actors. If you look at the data, for example, on the diffusion among small and medium -sized enterprises, most north of the world countries, they still have very low numbers because of lack of trust, because of lack of AI literacy, because of lack of systems that facilitate understanding on how the usage of AI can ameliorate the activity of a business, a public organization, a civil society reality, etc.
So, the AI Act is a legislation that doesn’t… doesn’t create a comprehensive framework that is vague. comprehensive but confusing maybe instead it chooses to identify a series of high risk areas of usage of AI and lets instead all the non -included use cases to not be regulated further than the existing legislation. Why I’m saying this? Because I think that to overcome one of the issues obviously when we look at the issue of diffusion there are many elements infrastructure, as I said, literacy but on the issue of trust and of risk management I think the UAI Act is an interesting reference point on having clear boundaries where we do not think we need more regulation where we let the systems be used freely, where we want checks and balances to be in place where we even choose to prohibit certain use cases and where we need transparency which is still a lacking element in many of our experiences with AI so I think that in the difference of the context these elements are quite relevant for even a context that is clearly different from the average European country but I think that to build trust we need to clarify where we want governance and limits to be in place and send a clear message to the population that even when we concentrate on EU use cases, on action, this is the topic of the summit we can also build in a smart way, in a clear way, not light, but clear, clarity, elements of protection, of guarantee that can create more trust in the adoption.
Brando, I know why your voice is like that, because people want to hear more from you. That’s why you will have a busy day today as well. I’m sure people want to talk a lot to you. Rachel, coming to you, I think Brando talked about an important point about the trust and clarity, and you have worked extensively with global south countries, right? So how crucial do you think are trust and ethics for diffusion? How do you see that actually getting implemented in practice?
Yeah, I think it is going to take far more work than perhaps we feel it might. So, you know, Brando, I think you mentioned some very important points around public awareness and understanding. In South Africa, the center I lead, the global center on… AI Governance conducted a very comprehensive public perception survey in the country. We interviewed over 3 ,000 South Africans from all walks of life, all demographic groups. We interviewed them in their own language. We have over 11 official languages in South Africa. And two -thirds of South Africans do not have a meaningful grasp of AI. So one -third of South Africans have never heard of AI, and another third of South Africans have heard of it but could not begin to tell you what it meant at all.
So I think if we’re thinking about the relationship between the large -scale private investments we’re seeing in AI diffusion, the large -scale public plans we have around AI adoption in relation to where the public sits, what their kind of levels of understanding are, and awareness and literacy is, this is going to create, this is creating a very significant significant democratic gap, particularly where a lot of these adoption pathways are around the use of AI in the public service. People don’t know about these technologies. They don’t know about the risks. They don’t know about the opportunities. They’re not able to contest it. They’re not able to participate in decision -making. We have a real problem. So diffusion cannot be something that is only about putting in place the infrastructure that sees forward technical delivery and access.
It must be scaled with governance efforts.
I think, Brando, we had that whole discussion separately where you talked about that getting technology in the hand of people doesn’t matter if you’re using it for a lot of autocratic rules, like for example, social scoring, right? So I think maybe going to you, Fred, on this point, looking at the positive side of the story, you talked about that day, AI for good or AI for good. So how do you, some of the use cases and standards that you think are really setting the stage for helping? drive the diffusion?
Yes, I think there’s no shortage of high potential AI for good use cases, especially now in 2026. That maybe wasn’t the case in 2017 when we created AI for good, but we’ve really seen things go from the hype, the fear of a promise, mainly existing in fancy marketing slides, to the advent of Gen AI, the rise of AI agents, and now the physical manifestation of AI in the form of robotics, embodied AI, brain -computer interface technologies, and even space AI computing, right? And just to give you an example, we have an AI startup innovation factory that runs all year, and there was an Estonian startup that had a very interesting application that can basically tell how much sugar is in your blood based on the sound of your voice using a mobile phone and detecting voice patterns, right?
Now, this could be a game changer for diabetes. I mean, it’s a nasty, you know, global disease. Taking your blood sugar is expensive, inconvenient, sometimes painful. It’s a real pain. Right now it’s still a pilot, but you see the potential for scale. But on the other hand, if it can tell how much sugar is in your blood, what else can it tell about you? How late did you stay up last night? What did you have for dinner? Are you on medication? Did you have too much wine? Are you paying attention? Actually, are you paying attention? So you can see where it goes, right? So you can’t take it for granted that these applications will develop in the right way and will be mindful of a lot of things we were talking about here all week.
Are these solutions, are they safe? Are they secure? Do they have ethics baked in? Do they respect human rights? Are they designed with participation from the global south of the table? Are they sustainable when it comes to energy and all types of things? And one way to, I guess, bake that in could be with standards. It’s not the only solution. But when you look at these fast -emerging governance frameworks, popping up all around the world, of course, you have the EU AI Act, you have different frameworks from around the world. I think one of the tricks is you don’t have a one -size -fits -all, and AI is moving very, very fast. but there are many practical things that can start to be implemented so how do you take these ambitious words and texts and turn them from principles to implementation because the devil is in the details and standards have details so I think we’re at the point where these products, services, companies applications, you know even hardware, all these things need to start to interface and interact interoperably, sorry they need to interact internationally and sometimes internationally as well, you’re going to need standards to basically make these things work and that could be one of the way of baking in all of the common sense things into standards now I know the words lightning speed and standards development are not often used in the same sentence and that’s probably a fair statement but I think in the case of AI for example when the Global Digital Compact launched its call I believe two years ago in the fall It took ITU and its partners less than three weeks to respond to that call for international AI standards coordination by launching the International AI Standards Summit Series.
And actually, the very first one was held in this venue in 2024 as part of WTSA, our Treaty Setting Conference on Standards. And we also launched the International AI Standards Exchange Database, which Doreen mentioned a few minutes ago. But more importantly, when you’re looking at the standards gaps and what people should be working on, we’re working with our partners, ISO and IC, on multimedia content authenticity standards development. That’s a fancy way of saying deepfake detection standards. I’m not saying we’ve solved the puzzle, but there’s a lot of energy and work working with industry, C2PA, different bodies there. I think another major gap, which is not only standards related, is, of course, the skills gap. So when we had our governance day in Geneva last year with ministers from over 100 countries, there’s a lot of things they couldn’t agree on.
But one thing they all agreed on is how to address the AI skills gap and democratize access to skills. globally and that didn’t matter if you were a developing or devolved country and then of course the other was how do you handle the epidemic of deepfakes so I think I’ll pause there thank you but hopefully that gives a kind of picture of how you can go from AI use cases to high potential looking at the dual nature of AI and how standards can be one of the tools to help address those issues. Thanks.
Thanks Fred. I mean if that app looks at me right now I think it’s going to tell me that I’m very caffeinated and sleep deprived right but on that point I think standards are obviously the physical manifestation of governance I think we did talk about that that’s very important and Rachel maybe I come back to you I think we do talk about policy tools are important financing mechanisms are important governance approaches because there are many different approaches to AI governance throughout the world how do you see that the participatory whether the governance is actually participatory today some of the frameworks from global north do you think that’s getting imposed on south or south is coming up global south is coming up with their own frameworks how do you see the situation on the ground
How do we use it to help advance developmental outcomes or public value? So I think we can see from those kind of three regulatory or governance approaches from EU, China and the US, there’s this very kind of pragmatic adoption of different elements of that within different global south regimes. I know with the African Union’s continental charter on AI, they’re very, very deliberate to include the word regulation. And there was a huge emphasis on human rights and on gender issues and on children’s rights. So I think that what we want is to have maybe less of a focus on global consensus than I think we’re often talking about, partly because interoperability can often mean the dominance of one particular region or worldview’s regulatory regime everywhere else.
And we’ve seen with the GDPR framework. For example, that that has had a limiting effect on the African continent. So I think we rather want to be seeing kind of. a global consensus around a set of principles, accountability, transparency, safety and human oversight and of course a set of standards but noting that different regions are going to need to adapt those standards in different ways. Sometimes those standards might be a kind of gold standard and sometimes they might need to be a minimum standard and we want to be thinking more about the capacity building approaches to try and meet that standard. One of the things we are worried about from a global south and an African perspective is that standard setting processes in the past have always been dominated by those with the time and the resources to really participate in them.
As you said they’re slow and they’re deliberately slow because there’s a lot of expertise we need to bring to the table and once they’re concretized and finalized they become binding. In their own way particularly on the technical side. really want to ensure that as we’re building out these standards, particularly for generative AI and agentic AI, which is still in formation and that is a socio -technical technology and it evolves as it is used in context, but we have representation from Africa, from Latin America, from Asia that is meaningfully included in these standards processes through deliberate funding, through leadership on committees, through co -authorship of these standards. So I think that’s very important to stress.
I think that’s an interesting point of view because I’m based in Singapore, so we have 11 countries in the Southeast Asia region and everybody runs at their own pace. And everything we talk about is how do we go from starting point, a lot of it is about where do you start and then talk about where do you end and what is the process along the way. I think that’s what you are. But Brando, I’ll maybe let you respond to some of the points she raised about… the regulatory experience that you have had you have talked to people here obviously you would have talked to other people there is always tension between local adaptation versus harmonization should we have a single set of rules throughout the world what are some of the aspects or highlights that you want to maybe highlight in that sense
well first of all on the standards I think it’s a fact that we need to accelerate on that and that we have seen some voluntary delaying I have to be very frank because I look at the implementation of the AI Act where we didn’t need standards so when we decided that some use cases you mentioned social scoring but I can tell you predictive policing emotional recognition in workplaces and study places these are use cases that including if I may also mention manipulative subliminal techniques that are prohibited and they didn’t need standards guidelines on application of these prohibitions were sufficient and we are already implementing that why? other parts of the law for example adequacy of data for training or levels of cyber security that are deemed sufficient these are elements parameters for the high risk use case applications where you need standards otherwise you can’t apply these rules and the standards are being in my view based on the elements I got from those in the standardization process sometimes deliberately delayed because there are some private sector actors that don’t want these standards to be there and so on we need to build mechanisms, I will not delve into that for time reasons, but mechanisms that we are building also in the European context to make it sure that there is a time limit for the standards to be in place because otherwise certain aspects of the governance will not be possible to be implemented.
I want to pick up briefly on also what you said on the risk of AI being used for in fact non -democratic developments, in fact to restrict participation spaces, freedoms. I think this is especially important when we look at fragile, institutionally fragile contexts, which are often countries of the global majority, global south, how you want to call it. we need to be aware that AI can be used for mass surveillance easily for repression of freedoms and to put people under pervasive control even without them fully understanding it I think that we should know that and at the same time I fully share the spirit of the summit concentrate on what we can do for good to mention the summit because a lot of things the example that was just made but yesterday I was meeting with a company from my own country from Italy that is here that deals with systems to anticipate physical status of drivers and to prevent accidents due to physical fatigue, to make it easier to identify earlier this kind of situations that would lead to actually a car accident.
So even in very specific areas, we can find in myriad ways how we can use AI for good. But my point is that enthusiasm for diffusion should not be in substitution for building frameworks that, I insist on my previous point, are precise and not generical ethical appeals, which, to be frank, are not very useful if they are not… pointing to clear deliverables. I want to conclude on this point to be clear that I think an ethical approach is needed. Without ethical approaches, any rule will not be able to function. But if you substitute regulation, governance of all kinds, it can be more binding or more, I would say, co -legislation, co -decision processes. But if you substitute these completely with mere voluntary ethical frameworks, I’m not sure we are getting anywhere.
Especially, I insist, in contexts that might…
I think AI for good always starts with AI not for bad. That’s always the starting point and that’s an important consideration. I did promise you guys I’ll leave you on time. So I’ll just have to do very quick two questions. I just need 30 seconds to 60 seconds responses. Fred, I’ll start with you. if you had a billion dollars to accelerate AI diffusion across developing economies where will you start
I think education skills I think that’s really the starting point actually I was in Johannesburg South Africa for AI for good impact Africa and I had a there’s a lot of conversations about you know using the whole mobile payment revolution of East Africa leapfrogging decades of infrastructure could the same thing be done with AI in Africa I haven’t made up my mind on it yet depending on who you talk to you might be convinced or not I think the opportunities there but also you can’t take it for granted that even if that did happen it would go in the right direction and I think that sort of basic understanding whether it’s for children for diplomats from grade school to grad school that skills gap is massive and I think that would probably be the best spend of money to start there
Brandon what will you do with a billion dollars
I would say I subscribe to priority because I think that literacy, understanding, build consciousness, building capacity also among civil society actors is extremely important when we see a big acceleration of development of AI as it’s happening around us. Thank you.
I completely agree on the digital literacy because I think one of the biggest risks we face, which we haven’t spoken much about, is labour displacement, which I think is going to become significantly more serious. The other thing I would do is invest in building the capacity of our state institutions, of our independent institutions of democracy, our competitions commissions, our gender equality commissions, our human rights commissions, our information regulators. Those are the bodies that will be able to champion the rights of citizens in the face of big tech monopolies.
I would have personally bought the shares of all the company CEOs who were here yesterday. but thank you for that. Quick question Rachel while I have you you have spent this week in India, you have seen the entire thing, you have seen the energies around this what is one lesson you learned from India which you think we should deploy globally?
I think India has made it very very clear that AI isn’t for everyone I think compared to any of the other summits I’ve been to I think it’s wonderful that there are children from schools here, that we have so many people that are local that have come to the summit and feel included, I think feeling like I am in India at the Indian summit has been the biggest kind of heartening and exciting thing for me.
Yeah thanks you have been super inspired to hear the story of how India was able to through a billion plus people create digital ID, financial inclusion, digital payments so there’s a track record of let’s say technology diffusion at scale but in a way that’s beneficial for everyone So that could be a good model for AI diffusion. I know there’s still a long road to go, but if you can do it in India for a billion plus people, I think it should work in smaller places as well. Rando, with whatever is left in your voice now.
Well, I think we can learn a lot from what we are seeing here in these days, and I’m convinced that we need to be determined in building more global cooperation. I don’t think we can get the best out of AI diffusion if we abandon the path of building more common understanding and learning from each other. I think this summit can be a moment of this process, but this is something that must happen during all the year.
I think, thanks to all of you. My lesson was obviously shake hands with your enemies, even if you are. that’s the only way to do diffusion across the world I would like to thank all the panelists thank you very much and Brando especially with your voice giving away I hope you have a good stay and thanks for enjoying and joining the panel, thank you very much thank you
“The **Bishini** platform in India delivers government services in 22 languages and reaches rural, low‑skill populations.”
The knowledge base describes India’s Bhasini/Bhashini program as supporting 22 constitutionally recognized languages and providing services such as speech recognition and farmer advisory, confirming the platform’s multilingual reach and rural impact [S127] and [S129].
“The ITU‑UNICEF **GIGA** school‑connectivity initiative aims for **100 billion** commitments to connect the hardest‑to‑connect schools.”
ITU’s Partner to Connect initiative, linked to GIGA, explicitly aims to raise 100 billion in commitments by 2026 to connect the most remote schools, confirming the target mentioned in the report [S138].
“The GIGA initiative already has **80 billion** pledged toward its connectivity goal.”
The knowledge base does not provide any figure for pledged commitments; it only states the overall aim of 100 billion and describes mapping activities, so the specific 80 billion pledge is not corroborated and appears inaccurate [S138] and [S136].
The discussion shows strong convergence on four pillars: (1) building digital skills and literacy; (2) developing inclusive, rapid, and enforceable AI standards; (3) ensuring AI diffusion is inclusive and bridges the digital divide; (4) leveraging startups as the engine for scaling AI solutions. Participants also uniformly recognize the risks of AI misuse and the need for safeguards.
High consensus across diverse stakeholders (UN agency, EU parliamentarian, South African researcher, Indian ITU official, and the moderator). This alignment suggests that future policy and funding initiatives are likely to prioritize education, standards, inclusive frameworks, and startup ecosystems, creating a coherent global approach to AI diffusion.
The discussion revealed several substantive disagreements: (1) the nature, enforceability, speed, and inclusivity of AI standards; (2) how a large funding pool should be allocated among education, civil‑society literacy, and state‑institution capacity; (3) which lever—start‑ups, the three‑S framework, ethical regulation, or participatory governance—should be prioritized to drive AI diffusion. While participants share common goals of inclusive, trustworthy AI diffusion, they diverge on the mechanisms to achieve it, reflecting differing institutional perspectives (ITU, EU, national startups, civil‑society).
Moderate to high disagreement, especially on standards and funding priorities, indicating that consensus on implementation pathways will require further negotiation and alignment of policy, industry, and civil‑society interests.
The discussion was shaped by a series of pivotal insights that moved the conversation from a high‑level vision of AI diffusion to concrete mechanisms for achieving it. Doreen’s three‑S framework established the structural foundation, which was then enriched by Dr. Panneerselvam’s focus on startups as the market engine, Brando’s illustration of regulatory clarity, and Rachel’s stark data on public awareness gaps. Fred’s rapid standards‑development example and emphasis on deep‑fake detection demonstrated actionable pathways to build trust. Together, these comments created a dynamic flow: from infrastructure and skills, through market mechanisms and governance, to inclusive participation, ultimately framing AI diffusion as a coordinated, multi‑dimensional effort rather than a single‑technology rollout.
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.
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