Panel Discussion: 01
Summary
The AI Impact Summit convened a ministerial conversation to examine how artificial intelligence can be adopted in the Global South and ensure that its benefits reach all citizens.โฏ[8-10] The panel comprised Her ExcellencyโฏSinaโฏLawson, Minister of Digital Transformation for Togo; His ExcellencyโฏNizarโฏPatria, Vice-Minister of Communications for Indonesia; and His ExcellencyโฏRafatโฏHindi, Minister of Communications for Egypt.โฏ[9-11] Organisers stressed that global cooperation is essential so that โAI for allโ does not leave anyone behind.โฏ[14-18] Patria rated the worldโs progress in turning AI infrastructure into impact as six out of ten, citing a persistent digital gap and the logistical challenges of serving Indonesiaโs 17โฏ000 islands.โฏ[44-46] Lawson highlighted that Africa contributes less than one percent of global AI talent and still faces connectivity deficits, yet she believes the continentโs practical AI impact is already close to nine out of ten when solutions are tailored to local problems.โฏ[67-71][72-73] She illustrated Togoโs pandemic response, where two AI algorithms-one using satellite-derived poverty maps and another analysing telecom metadata-prioritized cash-transfer beneficiaries and later led to the creation of a permanent 25-person data-science team within the Ministry of Public Sector Efficiency.โฏ[112-123][128-132] Hindi described Egyptโs AI-driven expansion of essential services, including early-detection tools for breast cancer and diabetes and a new AI platform that provides education support to high-school students in underserved communities.โฏ[87-92] Patria presented an Indonesian startup that combines AI with X-ray imaging to help remote doctors diagnose tuberculosis, a project supported by a government-run AI innovation hub and intended to be replicated across health, education and agriculture.โฏ[97-106] Lawson identified the main obstacles as inadequate infrastructure, low institutional awareness of AI possibilities, and the need for models in Togoโs 42 local languages, all of which limit scalable impact.โฏ[146-155][158-160] Patria added that geopolitical tensions, platform dominance, and the balance between regulation and innovation, together with limited R&D and talent development, further constrain AI deployment in the Global South.โฏ[169-176][177-184] Ghosh noted that the summitโs AI Commons initiative aims to pool best practices and knowledge to accelerate impact across countries.โฏ[80-82] When asked how AI success should be measured, Hindi argued that the key metric is the proportion of people who can access high-quality AI-enabled services, rather than the number of models or compute power.โฏ[198-204] The participants agreed that inclusive, trustworthy AI-backed by capacity building, standards and collaborative frameworks-will be the true north-star for improving lives in the coming five years.โฏ[245-251]
Keypoints
Major discussion points
– Infrastructure and โmeaningful connectivityโ are seen as the prerequisite for AI impact in the Global South.
Patria explains that Indonesiaโs archipelagic geography creates a digital gap and that the government is working to turn high-speed telecom networks into โmeaningful connectivityโ for AI applicationsโฏ[44-58]. Lawson adds that, in Togo, the first hurdle is basic infrastructure and that many officials are unaware of the data-and-AI tools that already existโฏ[146-156].
– Concrete AI-driven impact stories were shared from each country.
Togo used satellite-derived poverty maps and telecom-metadata machine-learning to target cash-transfer beneficiaries during the pandemicโฏ[112-124].
Egypt highlighted AI tools for early breast-cancer detection, diabetes screening and a nationwide AI-powered education support system, made possible by a government-first approach, sovereign AI models, and strong public-private partnershipsโฏ[87-95].
Indonesia described an AI-innovation hub that built a low-cost TB-diagnosis aid for remote doctors by combining X-ray data with a simple AI programโฏ[97-106].
– Several systemic roadblocks limit scaling of AI impact.
Lawson points to limited institutional capacity, low awareness of AI-enabled services, and the need for models in 42 local languages as major barriersโฏ[144-156].
Patria adds geopolitical asymmetries, platform-dominance, the need for balanced regulation, and insufficient R&D and talent pipelinesโฏ[169-184].
Both agree that trust-ensuring transparency, accountability, and protection against deep-fakes-is essential for widespread adoptionโฏ[222-229].
– The panel proposes a shift in how AI success should be measured, from technical metrics to people-centered outcomes.
Hindi argues that the key KPI should be the percentage of people with access to high-quality AI-enabled services, not the size of models or computeโฏ[198-206].
Patria stresses accessibility, problem-solving relevance, and trustworthiness as the three pillars for the next five yearsโฏ[224-229].
Lawson envisions a future where every Togolese can reach any public service with a single phone call, emphasizing inclusion, trusted AI, and interoperable data standardsโฏ[231-242].
– Collaboration and shared knowledge (e.g., an โAI Commonsโ) are essential for collective progress.
Ghosh notes that the AI Impact Summitโs working groups created an AI Commons to pool best practices, and she asks Lawson to contribute the Togo case study to this repositoryโฏ[79-82][138-139].
Overall purpose / goal of the discussion
The ministerial conversation was convened to showcase how Global South nations are adopting AI, to surface common challenges, and to identify cooperative pathways-such as shared standards and the AI Commons-that can ensure โAI for allโ and prevent anyone from being left behindโฏ[13-19][24-28].
Overall tone and its evolution
– The opening remarks are celebratory and forward-looking, emphasizing the historic nature of the summit and the elite panelโฏ[1-8][30-33].
– The dialogue then becomes analytical, with participants candidly rating current progress, describing infrastructure gaps, and outlining concrete obstaclesโฏ[44-58][144-156][169-184].
– As the conversation moves to impact stories and future visions, the tone turns hopeful and inspirational, highlighting successes and a shared commitment to inclusive, trustworthy AIโฏ[87-106][112-124][198-206][231-242].
– The closing remarks reaffirm a collaborative, solution-oriented tone, stressing collective action and common metrics of successโฏ[245-251].
Speakers
– Speaker 1
– Role/Title: Event host / moderator (introduced the ministerial conversation)
– Area of Expertise: Not specified
– Nizar Patria
– Role/Title: Vice Minister of Communications, Indonesia
– Area of Expertise: Communications policy, digital infrastructure, AI adoption in Indonesia
– Rafat Hindi
– Role/Title: Minister of Communications (Minister of Information and Communication Technology), Egypt
– Area of Expertise: AI applications in public services (healthcare, education), national AI strategy
– Source: [S7]
– Sina Lawson
– Role/Title: Her Excellency, Minister of Digital Transformation, Togo
– Area of Expertise: Digital transformation, AI-driven public-sector services, data science capacity building
– Source: [S4]
– Debjani Ghosh
– Role/Title: Distinguished Fellow, NITI Aayog; Moderator of the ministerial conversation
– Area of Expertise: AI policy, ethics, governance, AI impact assessment
– Source: [S12]
Additional speakers:
– None identified beyond the speakers listed above.
The AI Impact Summit opened with a celebratory acknowledgement of artificial intelligenceโs transformative and disruptive potential, stressing that the event marks the first AI summit hosted in a Global-South nation and that it aims to ensure โAI for allโ so that no one is left behindโฏ[1-8][30-33]. The host then introduced the three panelists – Her ExcellencyโฏSinaโฏLawson, Minister of Digital Transformation for Togo; His ExcellencyโฏNizarโฏPatria, Vice-Minister of Communications for Indonesia; and His ExcellencyโฏRafatโฏHindi, Minister of Communications for Egypt – and noted that the discussion would illuminate how Global-South countries are adopting AI, the challenges they face, and the need for global cooperationโฏ[9-13][14-18][19-24][25-28].
A central theme was the prerequisite of robust digital infrastructure that can be turned into โmeaningful connectivityโ. Patria rated the worldโs progress in converting AI infrastructure into societal impact asโฏ6/10, explaining that Indonesiaโs archipelagic geography -โฏ17โฏ000 islands with diverse cultures – creates a persistent digital gap that the government is trying to bridge by expanding high-speed telecom networks and raising internet penetration to aboutโฏ80โฏ% of itsโฏ250โฏmillion-strong populationโฏ[44-58]. He added that the dominance of large platforms poses a risk, and that regulation must protect citizens without over-regulating to stifle innovationโฏ[169-176][179-184].
Lawson highlighted the stark talent disparity in Africa, where the continent accounts for less than one percent of global AI expertise, and pointed out that many public institutions still lack basic connectivity such as linked schools and hospitalsโฏ[67-73][74-76]. She emphasized that Togoโs multilingual reality -โฏ42โฏlanguages and dialects – requires AI models that can operate in local tongues, making multilingual support a key institutional-capacity barrierโฏ[158-160]. Lawson said the continentโs AI impact score is already aroundโฏ9/10โฏwhen AI is applied to priority sectors such as government services, health, education and agricultureโฏ[70-76].
Concrete examples of AI-driven impact were shared. Lawson described how, during the COVID-19 pandemic, Togo deployed two AI algorithms – one that generated a satellite-derived poverty map and another that used telecom metadata to identify the most vulnerable phone users – to prioritise cash-transfer beneficiariesโฏ[112-124]. Following the crisis, the Ministry of Public Sector Efficiency established a permanent team ofโฏ25โฏdata scientists to support multiple ministries, embedding AI into policy design and service deliveryโฏ[128-132].
Hindi recounted Egyptโs โgovernment-firstโ strategy that has produced nation-wide AI tools for early detection of breast cancer and diabetes, as well as a new AI-powered education platform that offers high-school students and teachers personalised learning support, thereby extending advanced health screening and educational resources to underserved communitiesโฏ[87-95].
Patria presented an Indonesian initiative that illustrates how AI can address remote-area health challenges. An AI innovation hub supported a startup that combined X-ray data with a lightweight AI programme to help doctors in isolated regions diagnose tuberculosis, a model that is being replicated in education and agriculture sectorsโฏ[97-106][100-107].
The ministers also identified systemic roadblocks to scaling AI impact. Lawson argued that limited institutional capacity is the biggest impediment: many officials are unaware of existing AI tools and therefore cannot formulate the right questionsโฏ[144-156]. Patria added that, beyond infrastructure, Global-South countries face asymmetric geopolitical conditions, platform dominance, the need for balanced regulation that protects citizens without stifling innovation, and a shortage of R&D investment and digital talent pipelinesโฏ[169-176][179-184].
When asked how AI success should be measured over the next five years, the panel converged on people-centred metrics. Hindi asserted that the key performance indicator should be the proportion of the population that has access to high-quality AI-enabled services, shifting focus away from the number of models or compute powerโฏ[198-205]. Patria echoed this, proposing three pillars – accessibility, problem-solving relevance, and trust through transparency and accountability – as the north-star for AI developmentโฏ[222-229]. Lawson visualised success as a future where every Togolese citizen can obtain any public service with a single phone call, underpinned by trusted AI, multilingual support and interoperable data-exchange standardsโฏ[231-244].
Collaboration was presented as the mechanism to overcome these challenges. Ghosh explained that the summitโs working groups have created an โAI Commonsโ to aggregate best practices and know-how, and she noted that she co-chaired the โeconomic impact and social developmentโ working group together with Indonesia and the Netherlandsโฏ[84-88]. The AI Commons is intended to accelerate impact by enabling countries to learn from each otherโs successes and avoid reinventing solutions, and Ghosh invited Lawson to contribute the Togo cash-distribution case study to this repositoryโฏ[79-84].
In closing, Ghosh summarised the discussion as a demonstration of shared conviction among the ministers: AIโs true value lies in changing lives, not in the size of models or compute capacity; achieving this requires trustworthy, inclusive systems, capacity development, innovation ecosystems and coordinated international actionโฏ[245-251]. The panelโs consensus points to a unified roadmap for the Global South – build meaningful connectivity, strengthen institutional and multilingual capacity, foster trustworthy AI governance, and leverage collaborative platforms such as the AI Commons to ensure that the benefits of artificial intelligence reach every citizen.
for your inspiring reflections and also for highlighting the transformative role of artificial intelligence, as well as the disruptive role of artificial intelligence, drawing our attention to it and shaping our future. Ladies and gentlemen, I would now like to introduce the speakers for a ministerial conversation. The speakers in this fireside conversation is Her Excellency Sina Lawson, Minister of Digital Transformation, Togo. His Excellency Nizar Patria, Vice Minister of Communications, Indonesia. His Excellency Rafat Hindi, Minister of Communications, Egypt. Minister Lawson has made Togo one of Africa’s most watched digital transformation stories, building mobile first government services that reach citizens who were previously entirely excluded from the formal economy. Her work is a reminder that AI’s greatest opportunities may lie in the global south.
Her work is a reminder that AI’s greatest opportunities may lie in the global south. minister patria representing the world’s fourth most populous nation and one of southeast asia’s fastest growing digital economies his excellency is navigating the complex challenge of building ai policy for a country of 270 million people spread across 17 000 islands egypt is positioning itself as an ai hub for the arab world and africa and minister hindi is leading that change with a young population and growing digital infrastructure egypt’s ambitions are both compelling and instructive for developing nations navigating the ai transition ladies and gentlemen i would like to invite our speakers please with a big round of applause i would like to request you to please welcome the minister from togo from indonesia and also from egypt i request our honorable dignitaries to kindly take your place on this stage and this conversation is being moderated by Ms.
Debjani Ghosh distinguished fellow Niti Aayog, I request Ms. Debjani Ghosh to kindly join us AI Summit is a place where everybody looks forward to such ministerial conversations and this is one such conversation that everybody is looking forward to because when we say that this is the first ever AI Summit which is being organized in a country of global south, it makes a difference and here we have very elite panel with us. Her Excellency Sina Lawson, Minister of Digital Transformation, Togo is going to join us. His Excellency Nizar Patria, Vice Minister of Communications, Indonesia. His Excellency Rafat Hindi, Minister of Communications, Egypt. We are expecting our other guests to join us very soon as Ms. Devjani Khosh, Distinguished Fellow Niti Ayog is going to moderate this conversation.
And this will also give us an insight into the countries of Global South, how they are adopting artificial intelligence, what are the challenges before them, and how the world has to come together. This global cooperation is needed so that nobody is left out of the touch of artificial intelligence, the benefits of artificial intelligence. And that’s when Honorable Prime Minister says it’s AI for all. This is what we mean, that it should reach each and every person. Of the continent, of the world, and AI should bring a change into the people of global. South too. Only then we can say that we are going, moving ahead in the right direction. So keeping that in mind, ladies and gentlemen, this ministerial conversation is going to be of utmost importance when we talk of AI Impact Summit, because this conversation will also bring to the fore those points on the basis of which we can say that AI is making an impact into the lives of people, especially the people of Global South.
And when we talk of the challenges, the difficulties which face Indians, our countrymen, that is the time when we can say that if you are able to find low -cost AI solutions to our problems, they will also be the solutions which can be adopted very, very easily by the other countries of the Global South. So here we are bringing to you this ministerial conversation. Our guests are here. And this elite panel from these countries, from Congo, Egypt, and Indonesia, will bring before us those issues that are of utmost importance to the lives of people, especially the people those aspects on which they’ve already been. working, the challenges which they think they need cooperation from other countries as well, if they want to counter these challenges.
Because when you talk of Global South, ladies and gentlemen, unless Global South develops, unless Global South adopts artificial intelligence, it cannot bring a change in the world. And that is what this summit aims at, that we must impact the lives of common men. Nobody should be left behind. And when we say this, we say, which means it’s AI for all. Everybody should be benefited. So, ladies and gentlemen, please welcome our elite panelists here. We have Her Excellency, Sina Lawson, Minister of Digital Transformation, Togo. Please welcome her. His Excellency, Nisar Patria, Vice Minister of Communications, Communications Indonesia, and His Excellency, Raphat Hindi, Minister of Communications, Egypt. It’s over to you, Ms. Devjani Khosh. Thank you.
Thank you very much. much and good afternoon, everyone. And thank you to all of those who are here. So we are all finally here. And as you can see, this is truly a very power -packed panel. So since this is about the Impact Summit, the AI Impact Summit, and since we are gathered from all over the world to talk about the creation of Impact by AI, I want to first start with you, Mr. Petra. You know, when you think about the journey that we’ve had till now, the global community has had till now with AI, a lot of the focus has been on building the infrastructure. So how do you think we have really done on putting that infrastructure to work to create impact?
If you had to rate it on a scale of one to ten, what would you give the world? What score would you give the world? Thank
you, Ms. Jenny. This is really a challenging question, actually. if I had to give a number I would give 6 out of 10 yeah why 6? because well if we talk about the emerging technologies like artificial intelligence is it is the words like a buzz like a mantra right now everyone talking about AI and AI right now is here is with us and many people they don’t scrutinize anymore about the useful of AI they just use but the problem is the level of adoption of this technology, this emerging technology, especially for the global short countries like Indonesia and maybe some of African countries, Asian countries. We still have a digital gap. Yes. Especially for Indonesia, we are an archipelago country.
We are archipelagic. So we have 17 ,000 islands. We have five big islands in Indonesia. And each island has a very unique characteristic, very unique people, culture, and so on. And the telecommunication infrastructure is very, very important for our country. That unites our country with this telecommunication infrastructure. We try to improve. We try to cover all of the archipelago by our telecommunication network. And now the internet penetration into the population is already about 80%. Our population right now is 250 million people. And now what we do with these infrastructures, digital infrastructure or telecommunication infrastructure, we want meaningful connectivity. Yeah, that’s it. Meaningful connectivity. That means how we use this connectivity with the emerging technologies like artificial intelligence on top of these infrastructures to give benefit to the people.
So government try to be the accelerator to build this meaningful connectivity
Now, that’s very well said. So six out of 10. And the main gap or the main reason is we still have miles to go before everyone has access. And access has to be meaningful. Right? I think that’s very well said. Ms. Lawson, would you agree with that? Or would you have a different take on that?
Hello, everyone. Good afternoon. Yes, I do agree. Absolutely. I think that when we talk about AI, for us, at least Africans, it’s not about the technology. It’s about what we can do with it. And so a few comments. Number one is that in terms of AI talent, the African continent represents less than 1 % worldwide. In terms of infrastructure, we also have a lot of AI talent. We also have challenges. You know, a lot of countries don’t have connected schools or hospitals. So we’re still building our connectivity. and I would say that but if you look at few examples few achievements that we had using AI in terms of impact we can see that even today it’s equal to 9 out of 10 so every time we implement it in our way solving our problems then the number comes closer to 10 than anything I would also say that the African Union position was to use artificial intelligence in real life use cases so the impact for us and the sectors, the priority sectors are government infrastructure and the way we function it’s health, education, agriculture so I think that if we succeed to implement AI in those sectors then our continent will change forever
I really like that, the fact that you brought out three very important mission -critical sectors, rather than saying we need to go and do everything. But I think that priority is so important. And by the way, part of the seven working groups that was there under the AI Summit, one of the working groups, which I had the privilege of co -chairing, along with Indonesia and Netherlands, was economic impact and social development. And one of the things we decided that’s needed right now to accelerate impact is the creation of AI Commons that brings together best practices, know -how. So that was one of the key outcomes of part of the working groups that we launched. Mr.
Hendy, if I may come to you. When we talk about impact, one thing we realize is it means so many different things to so many different people. Can you give us an example of something? Something that you believe is truly… a North Star with respect to how impact has been created. A great example of how impact has been created.
Yes, thank you. In Egypt, the most meaningful impact AI has been in expanding the access to the essential public services, such as healthcare and education, in a larger scale and at nation -wide. We are using AI tools for early detection for breast cancer and some diabetes -related conditions. And we are now launching a new AI powerful tool for education support to be used in high school with high school students and teachers across the country. For the first time, advanced medical screening and learning support become available for underserved community. We usually have able to do it in big city and in elite institution, but now we are able to do it with underserved community. Three things made this possible in Egypt.
A government -first approach that puts public interest first and sovereignty AI capability that reflects our language and our local needs. Also, the strong partnership between across the government and national AI ecosystem and the global partners. Thank you.
Mr. Patria, any good example that you would like to share of impact creation in Indonesia or any other country that you think has done a really good job of it?
Well, I will share one example from Indonesia, how this artificial intelligence can help. Because we are a very diverse nation and also archipelago country, so sometimes we in the public services, for instance, healthcare, we need effective and efficient technology adoptions to help these healthcare sectors. So now we try to to encourage our young generation that build a startup. And we try to facilitate them in what he calls is an AI innovation hub. And one of the product is try to help doctors in the remote area to diagnostic the tuberculosis. The tuberculosis or TBC is coming on the stage. And it becomes very difficult for the doctors in the remote area to detect because they have a very limited access on the modern equipment or sophisticated technology to detect this tuberculosis diseases.
But with the artificial intelligence, so this startup tried to gather all of the big data from the health center in the remote areas and then make a simple program and give it to the doctors. And combined with the x -ray machine, it can help doctors to identify whether this is TBC or this is just ordinary lung problems. So I see these initiatives in certain sectors already copied to other sectors for the education, for the agriculture. Many startups try to adopt this AI technology right now. And I can see and we can feel that the enthusiasm is really, really high. But the problem we need as a government, as a policymaker, we need to give the safeguard and to accelerate.
in building this healthy and fair ecosystem to boost the innovation on artificial intelligence.
Fantastic. Ms. Lawson, any favorite impact story that you want to share?
Yes, I have a great impact story. During the pandemic, we were able to use AI to prioritize the beneficiaries for our financial aid program. So at the height of the pandemic, we built a program to distribute cash using mobile phones, right? So the question then was, how do you prioritize beneficiaries? We started in 2020. And in 2020, we didn’t know if the pandemic was going to last for a long time. So we had one certainty, which was that we needed to be super efficient in programming. Prioritizing who needed the money the most. And so we used two AI algorithms. One… applied to satellite imagery. We drew the poverty map of Togo. And then another based on machine learning with telecom metadata, we were able to isolate the phone numbers of people who were, yeah.
So that was really our first major experience using AI. And then after the pandemic, the question for us was, we want this to be sustainable. Right? How do you, because it was during the pandemic, we had a partnership with Berkeley. So we were working, really figuring out things as they were coming. But afterwards, we wanted to build capabilities in -house. So we now have within the Ministry of Public Sector Efficiency, a team of 25 people, data scientists, and we support other branches of government. Because when we talk, you know, here we talk about AI and everybody really, knows what AI is and the type of applications that, you know, things we can do with AI. But a lot of people, they don’t know what AI is.
don’t know. So it’s very important to have a team of people who work, say, with the Ministry of Agriculture or the Ministry of Environment and producing images and really data that can help these ministries improve policies. So I think this is a great learning experience for us. It’s applying AI to improve policies.
It’s such a brilliant example because one, it impacts the grassroots, right? The people who need it the most. And second, it’s, you know, government has a lot of, I mean, especially in the Global South, a lot of government usages, augmentation of services. I think what you’re doing is really enabling better development of policies. And that’s that. I would, in fact, request you to please share this case study so we can put it in the AI Commons that we have built. So I would really request you to do that. The next question is also to you, Ms. Lawson, which is… As government, what do you think is the biggest roadblock to scaling impact creation where it can reach population?
Is it data? Is it infrastructure? Is it regulation? Or is it even geopolitical dynamics?
So I think it’s a combination of various things. We’re tackling all of these things. But first, it’s infrastructure, because that’s the starting point. But you also have something, when I was referring to the data lab, a lot of people don’t know this universe exists, right? That you can apply, you know, you can use AI to gather information as to when you want to design a new infrastructure, like an itinerary. For example, when we build our fiber optics network, we use satellite imagery and so on. But a lot of people just don’t know it exists. Right. So they can’t ask. They don’t know which question to ask. Right. And so. So even if we’re there, so we do a lot of outreach within government going and saying, look, this is what we were able to do using AI and so on.
So I think that what I would call institutional capacity is a roadblock because people just don’t know. So it’s a lot of training required. The other thing is, and I think it’s also one thing that we’ve been working on is right now AI is in French or English, right? It’s not in, it’s not, we have in Togo, we have 42 languages and dialects. And for AI to, if we want massive AI adoption, we need to be able to provide these models in local languages. So that’s one very important aspect of what we’ve been up to. 42 languages. Yeah. Wow. And dialects, you know, I’m sure that, yeah. Yeah. So that’s the challenge. But that’s also the opportunity because when you think about creating.
impact for AI. Think of education. Imagine, and that’s what I imagine, imagine a world where every school children has an AI tutor being able to explain to them, you know, math and science in local languages, in their own dialects. That’s for me, the power of AI, really.
So institutional capacity is one of the biggest roadblocks that you see. Mr. Pedra, is there anything you want to add to that in terms of the biggest roadblocks to mass scale impact creation?
Yeah, I agree with the colleagues from Togo. I think it’s the problem today for the global sub -countries like Indonesia, and I think some of African countries and other ASEAN countries. is now we are facing the geopolitical condition that you mentioned is really challenging times today because we are facing asymmetric conditions amongst global sorts and global norms. And that’s one problem because the platformization, the dominance of the platform is so important to define or to determine the progress of the fair ecosystem in one country. That’s the first thing. And the second one, I think the infrastructure is one of the critical things that we need to pay attention. We need to improve. We need to heighten the standard of services on this infrastructure.
And then regulations. I think regulation is also very important. in this sense because… Do we over -regulate? No, no, no. We don’t intend to heavily regulate these AI sectors because we try to balance protections and also innovations. That’s most important, I think. If you heavily regulate, so no innovations at all. I cannot agree more. Yeah, so we try to balance. And the most important, the last thing that is most important, I think, we need to improve our research and development and then attract the investment to support these innovations and to nurture our digital talent. That’s the most important that we have to do in the short term.
Extremely well said. And I think between the two of you really captured it. While infrastructure is always important and you always want to, you want more compute, you want to build it out. But if you don’t have institutional capacity, then investment in that infrastructure will not give you the returns. And regulation needs to help innovation, needs to help scale. And R &D is absolutely critical. So I think these are brilliant points. I know our time is up. So my last question, and I would request all three of you to answer. If we look at the next five years, the future, how should AI success be measured? Today, we are primarily looking at how many models we are building, how big are the models.
How should we be looking at AI success? What’s the North Star? I’ll start with you, Mr. Hendy.
If I have to choose now, it would be this. The business. The percentage of people that have access. Wonderful. To high. Quality AI enabled services. Wonderful. Not the number of models, not the compute. The people’s benefits are the most important. They have to benefit from healthcare, from education, from agriculture and government. And the KPI matters for three reasons, actually. First, it shifts the focus from technology to people. And AI is advancing very fast. But access to it is not that fast. We need to make sure this happens. And this is what I can see for 2030, maybe for AI. Second, it exposes the global gaps, not hiding them. So gaps in the compute, gaps in infrastructure, in local language models.
So this is very important. The third one is it’s framing AI as a development tool. Not a dominant tool. where compute power is shared and public service is prioritized. I think this is what I look forward to.
So success is not the size of models or the size of your compute infrastructure, but how many lives we are able to change. And are we able to do that in a way that no one is left behind, right? It’s inclusive. Brilliant. Anything you all want to add? Any different thoughts, Mr. Petra and then Ms. Lawson?
Yeah, just a very short on this. I just want to add three more. But the first one I think is similar like colleagues from Egypt. In the next five years, AI should be accessible. That’s the first one. And the second one, for the global south countries, AI must solve the problem. That’s the most important. And the third one, I think AI, need to be trusted. trusted yeah need to be trusted so it need to comply with the transparency and accountability standard so no more AI deep fake can cheat people yeah so because people have good awareness on this AI product especially generative AI like AI deep fake or synthetic reality that produced by this AI machines so I think that three points we can give mark whether this AI workable in the society or it’s become a disaster to the
I cannot agree more with you on all three but I think the one that is most important is trust because if it’s not trustworthy it’ll never be adopted it’ll never be used so I think that is brilliant brilliant point Ms. Lawson the last words to you
I would echo what has been said and for me success would be I think If five years from now, every Togolese is one phone call away to access any public services, right? And so that’s how I’m going. Personally, I’m going to measure success with regards to AI in Togo because then it talks to the people, right? Because so far we’ve been talking about digital transformation, which was really going from paper to screen. But what is going to be a real game changer is if I can talk to the machine and the machine can reply and so on. So that’s one thing. And obviously, the comment about trust is a very important one. We are a very young continent.
Half of the African population is less than 18 years old and 75 % is less than 35. And so it’s very important for us to have a trusted AI. AI infrastructure and so on. And so there’s a lot of work that we need to do. We didn’t mention to have also standards and platform for data exchange, which is going to be extremely crucial in our relationship with the global north. So these are really important issues that we need to tackle if we want to be successful five years from now.
I think that’s very, very well put. And, you know, this was, ladies and gentlemen, such a powerful discussion because what’s coming out of it is how despite all the differences between countries, I think governments today are thinking very similarly about artificial intelligence. Its success, again, is not about the size of your infrastructure, but about how many lives changed. And in order to scale transformation of lives, you need to ensure your technology. It’s trustworthy. You need to ensure it’s inclusive by design. You need to invest in capacity development, innovation. And it’s fantastic to see everyone thinking along the same lines because it really. brings to forward the importance of collective action and collaboration and I think that’s what has come out of this summit.
So with that, thank you to all three of you and please give them a huge round of applause. Thank you.
โThe AI Impact Summit was the first AI summit hosted in a GlobalโSouth nation.โ
The knowledge base states that this was the first summit to be held in a Global South country, confirming the claim [S107].
โThe host introduced Her Excellency Sina Lawson, Minister of Digital Transformation for Togo, and His Excellency Nizar Patria, ViceโMinister of Communications for Indonesia, as panelists.โ
Panel discussion records list Her Excellency Cina (Sina) Lawson, Minister of Digital Transformation, Togo, and His Excellency Nizar Patria, Vice-Minister of Communications, Indonesia, confirming their participation [S4] and [S6].
โPatria rated the worldโs progress in converting AI infrastructure into societal impact as 6/10.โ
A speaker in the knowledge base explicitly gave a rating of 6 out of 10 for AI progress, matching the reported figure [S5].
โLawson highlighted a talent disparity in Africa, noting the continent accounts for less than one percent of global AI expertise.โ
While the knowledge base does not provide the exact 1โฏ% AI-expertise figure, it notes that Africa holds less than 1โฏ% of global data-centre capacity and faces broader capacity gaps, offering related context on the continentโs limited AI resources [S22] and [S116].
โLawson pointed out that many public institutions in Africa still lack basic connectivity such as linked schools and hospitals.โ
The knowledge base highlights infrastructure challenges across Africa, including unreliable electricity and limited connectivity, which supports the broader point about missing basic digital links, though it does not mention schools or hospitals specifically [S10].
The panel displayed strong consensus that AIโs value lies in tangible, peopleโcentric outcomes, requiring solid digital infrastructure, institutional capacity, sectorโfocused applications, and collaborative mechanisms such as an AI Commons. All speakers aligned on measuring success by impact, not by technical metrics, and on the need for trustworthy, accessible AI solutions.
High consensus across all speakers, indicating a unified vision for AI in the Global South that emphasizes inclusive impact, capacity building, and cooperative governance. This convergence suggests that future policy and investment efforts can build on shared priorities to accelerate AIโdriven development.
While the panel shares a strong consensus that AI must be inclusive, peopleโcentric, and supported by collaborative mechanisms, they diverge on the assessment of current infrastructure, the hierarchy of barriers (geopolitics vs institutional capacity vs multilingual needs), and the precise metrics for success. These differences reflect varied national contexts and priorities, suggesting that a oneโsizeโfitsโall policy may be challenging and that coordinated efforts will need to accommodate multiple pathways to impact.
Moderate โ the speakers largely agree on overarching goals but differ on priority challenges and measurement frameworks, which could complicate unified policy formulation but also enrich the dialogue with diverse perspectives.
The discussion evolved from a broad appraisal of AI infrastructure to a nuanced, peopleโcentric view of impact. Key commentsโespecially those introducing “meaningful connectivity,” sectorโspecific success stories, the pandemic cashโdistribution case, and the emphasis on institutional capacity, language localization, and trustโserved as turning points that redirected focus toward practical implementation, capacity building, and ethical considerations. These insights unified the ministers around a common North Star: AI measured by the proportion of citizens whose lives are improved, not by the size of models or compute, thereby shaping the conversation into a cohesive call for inclusive, trustworthy, and locally relevant AI development in the Global South.
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.
