The Last Shall Be First: Africa's Path to Leading in the AI Revolution

Part 2: Lagos Chapter's first salons

Editors Note: The Ai Salon’s 🇳🇬 Lagos Chapter 🇳🇬 had their first two salons in February and March of 2025! Celebrating these first Ai Salons in Lagos, Nigeria, Africa and the entire southern hemisphere, we will post distillations of both of these conversations this week. I found them incredibly interesting and hope you will two!

This is Part 2! As always, this is an AI-supported distillation of an in-person event, this time held in Lagos on April 04, 2025 facilitated by the Lagos Chapter Lead,

Francis Sani

- it is meant to capture the conversations at the event. Quotes are paraphrased from the original conversation and all names have been changed.

👉 Jump to a longer list of takeaways and open questions

The Last Shall Be First: Africa's Path to Leading in the AI Revolution

In the heart of Kigali, a diverse group of technologists, entrepreneurs, and visionaries gathered to tackle an audacious question: What is Africa's path to leading in the AI revolution? The question itself carries a provocative tension—can a continent often characterized as "behind" in technological development somehow leapfrog to the forefront of AI innovation? As Leila, the Nigeria chapter lead for AI Salon, framed it: "Do we think it's possible for us to lead? From a practical standpoint, I think for me, the conversation today, I'd like us to make it as pragmatic as possible."

This call for pragmatism animated a rich conversation that revealed something profound: perhaps Africa's greatest strength lies not in competing with Western benchmarks but in leveraging its unique position to build AI systems that reflect African values, solve African problems, and ultimately create a more expressive, self-actualized future for its people.

"I genuinely have these daydreams sometimes," shared Leila toward the end. "In my daydreams I see futuristic cities, I see futuristic towns, I see futuristic people. But the beautiful thing about those daydreams is that the cities, the towns, the people I see are not white people, they are black people. They are African people. Not from a comparison standpoint. From the standpoint of expression."

This vision—of an AI-driven future that reflects African identity rather than mimicking Western models—emerged as the conversation's central undercurrent. Beyond the technical challenges of data scarcity, compute limitations, and talent retention, participants wrestled with deeper questions about identity, agency, and what "leadership" truly means in a global AI landscape.

Main Takeaways

• Africa's leadership in AI should be measured by solving indigenous problems rather than competing with Western benchmarks

• Africa's youth demographic (60% under 30) represents a competitive advantage that could drive AI innovation if properly equipped

• Building AI-native systems without legacy infrastructure constraints gives Africa an opportunity to leapfrog traditional development paths

• Policy development must be co-created with innovators rather than imposed by consultants with limited local context

• The diaspora represents a valuable resource that must be purposefully connected back to the continent through structured mentorship programs

• Traditional knowledge and cultural context must inform Africa's approach to AI development and deployment

• Africa produces 30% of the world's rare minerals essential for AI hardware, presenting an economic opportunity alongside AI applications

Redefining Success: Beyond Western Benchmarks

When discussing Africa's AI future, the conversation quickly pivoted from global competition to local relevance. Multiple participants challenged the frame of the discussion itself, questioning whether being "first" or "last" was even the right metric.

"I don't think we are competing with anybody," stated one participant firmly. "By the time you build tech that works for us, we know that it works for us. We know that makes us eager. That's all that matters. First or last as long as it works for us."

This sentiment resonated across the room. Rather than measuring progress against external yardsticks, participants advocated for success metrics tied to solving uniquely African challenges. A technologist elaborated: "What can we do for Africa for the younger population? How can we position AI service either as a product or as a service or as a life tool?"

Another participant from Kenya provided a more nuanced perspective: "I think we ultimately need to focus more on tech. It's important that we're doing very important work as we sort of ride to address socioeconomic challenges in agriculture, education, healthcare—those are where we often hear these spaces. But I think we ultimately need to focus more on tech."

The question of competition versus collaboration emerged as a key tension point. A participant who identified himself as King argued that "competition is healthy for innovation," noting: "The reason that we have 200 fintech startups in Lagos—let the best man win. If everybody is collaborating, believe me, innovation will be stifled. Innovation strives when there is competition."

Others countered that Africa's resource constraints demand collaboration. "I see a lot of us building the same thing across different countries," observed one frustrated participant. "We don't have these resources... but yet we're building the same small thing."

A participant working in agriculture noted that data scarcity in farming presents both a challenge and an opportunity: "There are no multi-language tools for 60% of small farms. Africa has the largest amount of small farms globally, and they are disconnected from AI tools that could help." He then pointed to a concrete success: "Something that launched six months ago in five languages has helped 500,000 farmers in Nigeria access over $10 million."

By focusing on solutions for such distinctly African contexts, innovators could develop technologies that not only serve local needs but potentially create exportable solutions for similar contexts worldwide.

Africa's Youth: Promise and Paradox

Africa's demographic profile—with 60% of its population under 30—emerged as both a tremendous asset and a complex challenge. This youth bulge represents potential human capital that could drive AI innovation for decades to come.

"What does Africa have that majority part of the world does not have?" asked one participant rhetorically. "We have the youngest population currently in the world, right? What does that translate to? When you look at that population, that human resource, look at AI, we begin to talk about, okay, what can AI be like in the next 20 years time?"

Yet this demographic advantage comes with significant responsibilities. The conversation repeatedly returned to education as a fundamental priority. One participant stressed: "I want to see them [AI system] in universities. I want to see them in places where young leaders are learning prompt engineering, also learning how to use. I wanted to come out of those places smart and ready for knowledge of today."

Another participant shared a practical example from Rwanda: "In my school when you're going to do a final project, they require you to go look for a company, propose to that company, and that company should give you data. That's what you work on as a final project." He also mentioned "Rwanda Hub, the type of quality of students they bring out—competitive university levels—they come into hackathons, university hackathons."

This focus on practical education contrasted sharply with what several participants described as a culture of "career entrepreneurship" prevalent in the ecosystem. One participant observed with frustration: "We see a lot of startups or entrepreneurs these days who are just in entrepreneurship as a filler, not because they want to build something useful. We also now have a culture of career entrepreneurs—get 70k here, get 50k here."

The participant continued, referencing a respected industry figure: "If people at his age are still wearing T-shirts at their startups, something is wrong with us. And that is the truth. Before she started doing Budget, there was no civic technology that you could point to. And with Budget, you know, you could see products that you can use for accountability and it works. It's not that they're traveling around to raise money to just fly the next business class."

Perhaps most concerning is the ongoing talent exodus. "That youth doesn't want to work for Africa. Everybody is leaving," noted one participant. "We're shipping people out. And so as much as we're saying we are rich because we have talent, that talent is not working for Africa."

Yet others pushed back, arguing that migration can be beneficial if structured properly: "People should go out. If you look at China, most of the guys developing cutting-edge technologies traveled from where they were to where the opportunities are. Those who come back are coming back with knowledge that benefits society."

The China example was referenced again later: "China did something very smart. They just opened up the phone and called back everybody from that worked in big tech to come back home. They said if you're Chinese and you're working in Google, Amazon, all these places, we're going to give you a few million just come back. All my colleagues were just resigning. They were just going back home, and now most of those companies are multi-million dollar companies."

Building Without Legacy: The AI-Native Advantage

One of the most counterintuitive insights from the conversation was how Africa's perceived "lateness" to technological development might actually represent an advantage in the AI era. Without legacy systems to replace, African innovators can build AI-native solutions from the ground up.

"When we say fintech in Nigeria moved at a faster pace than in European countries, sometimes that which we see as a strength can also be a weakness," noted Leila. "The legacy systems that they had were built in certain ways, and for them to move from legacy systems to new systems was harder. Because we're starting from the beginning, we have the ability to build AI-native systems today."

This perspective reframes what might seem like disadvantages into strategic opportunities. Rather than playing catch-up, Africa has the chance to leapfrog older technological paradigms entirely.

Leila elaborated: "Today if you're building a solution that is using satellite imagery to be able to help farmers plan better, improve their yield, you're literally going to be building these solutions with AI native technologies and AI native tools. So it means that literally the existing solutions that are in the market that the larger guys are using today, they are not going to be able to change as fast as you might."

This "clean slate" advantage extends beyond technical systems to regulatory frameworks as well. A legal expert explained: "The African Continental Free Trade Area Digital Trade Protocol presents a unique opportunity for the harmonization of cross-border data protection regulations across member states. The moment we're able to effectively communicate the needs for these regulations to happen, that's when you begin to see this proliferation of AI knowledge and knowledge sharing."

Another participant highlighted Africa's untapped economic potential in the AI supply chain: "I was going through some research and I realized that Africa as a continent, we produce 30% of the world's rare minerals. And these minerals are very essential in AI technology."

However, this advantage comes with significant responsibility. "As much as we're saying we are rich because we have talent, that talent is not working for Africa," warned one participant. "Fifty years ago the North moved South and used your own people to better themselves. We might see it again."

Co-Creating Policy: Beyond Consultant-Driven Approaches

Throughout the conversation, participants repeatedly highlighted the disconnect between policy development and innovation realities on the ground. A clear consensus emerged: effective AI policy must be co-created with innovators rather than imposed by external consultants with limited local understanding.

"When we talk about policies in Africa we talk about it's going to suddenly create an environment that makes innovation move faster," observed one policy expert. "I lived in South Korea for five years and what I learned in that place is that the government chases the private sector because the evolution is at the speed that government cannot capture."

The speaker continued with concrete examples: "We've had a lot of situations where the government has invited the consultants that has no context about our situation. They've written the policy and they slap it on what we're doing. And that's why sometimes the Nigerian politicians call it policies for myself, right, even though it doesn't disagree with. So it's very important that we understand that policies is not what we need to do. We should not wait for policy to innovate."

This frustration with consultant-driven approaches reflected a deeper concern about whose knowledge and experience shapes Africa's technological future. "A good policy is a policy co-written by the people who have led that industry to the point where the government has gotten a wind of what they are doing and they are inviting them back to the table," the same participant concluded.

One participant shared a concrete example of successful policy engagement: "Rwanda is working on regulating digital assets. So Bitcoin to get my data. And one thing that is so impressive, I mean blockchain, the Rwanda Blockchain Association had a meeting to propose ideas that should be put in that regulation. As people that have the knowledge too."

He continued: "The foundation of policy is knowledge. So if you're able to build associations—Education Association, AI Association, Blockchain Association—in your communities and you're considered knowledgeable enough, the government will listen to you."

This model of collective expertise influencing policy represents a promising middle path between individual entrepreneurship and government-led initiatives. By aggregating knowledge and speaking with a unified voice, technical communities can help shape policy that enables rather than constrains innovation.

Cultural Context: Preserving Traditional Knowledge

A profound thread throughout the discussion was the importance of cultural context and traditional knowledge in Africa's AI development. Rather than seeing AI as a foreign import, participants emphasized the need to ground it in African values, wisdom, and ways of knowing.

"The things that they taught us were wrong, like our mud houses," noted one participant, referencing colonial dismissal of indigenous architecture. "Today people are discovering that mud houses are environmentally friendly. One special case that happened in the north—we have a lot of cattle keepers. And what happened when the government was looking down all mud houses and huts that use grass is that the cattle's milk went off. Because the houses work as a good condition for their milk to be right."

The participant concluded: "You see that our ancestors had systems, and we need to tap into the logic of that perspective. But we didn't do that, and now we have a gap."

Leila highlighted another aspect of cultural context—the oral tradition: "One of the things that we've done a lot is oral communications. A good example is Ifa, the Ifa mythology in Yoruba. The entire breadth of it is not written somewhere because there's the thinking that it's important for you to be able to pass it along orally. That's also one of the challenges we have because we don't have a huge documentation culture versus the West."

This disconnect between traditional knowledge and modern technology represents a significant loss—not just culturally but practically. Solutions mentioned included creative applications of AI itself to preserve this knowledge.

We want to build for communities, nations, economy, continent where as many people as possible... can come into this world and they don't spend 80% of their lifetime thinking about what to eat. They don't spend 80% of their lifetime thinking about the most basic needs in Maslow hierarchy. They spend the entire chunk of their lifetime self actualizing themselves.

"Until the lion learns to write, every story will glorify the hunter," quoted Leila, highlighting how narratives about Africa's technological past and future are often controlled by others. "Until we learn to take charge of the situation—who's telling our stories, the narratives that we have about ourselves, about our countries—who's telling those stories?"

Another participant emphasized the importance of cultural values in shaping technology development: "I think those values need to go back to those artifacts, those standards, those belief systems, those respect for ourselves...We were a collective society as Africans. And this conversation in this business school has taken us back to those underlying prime systems, what shapes us as a people, which of course should inform what we celebrate."

Yet this cultural grounding must be balanced with forward-looking innovation. As Leila reflected near the end: "We want to build for communities, nations, economy, continent where as many people as possible can come into this world and they don't spend 80% of their lifetime thinking about what to eat. They don't spend 80% of their lifetime thinking about the most basic needs in Maslow's hierarchy. They spend the entire chunk of their lifetime self-actualizing themselves."

Building Community Across Borders

The final major theme centered on the critical importance of building communities across nations to create a truly pan-African approach to AI. Participants recognized that while implementation happens locally, the power of collective action across borders could accelerate progress dramatically.

"One of the first things is to have connections between people in colleges or places where people can meet and share small ideas, get a startup," suggested one participant. "We have the numbers. Something connected at some point."

This community-building extends beyond physical borders to include the diaspora—a tremendous resource often disconnected from local innovation ecosystems. "In Kenya recently, last Thursday the national AI strategy was launched," shared one participant. "I think there are 15 sort of national strategies on the continent from Egypt to Morocco to Rwanda, etc. What is that other frame of reference to understand what other things other African prisoners are doing to enable or to create an innate environment so that AI can press?"

Dr. Bayo from Data Science Nigeria spoke about a concrete initiative to connect diaspora talent with local needs: "We're trying to see how we can support the local ecosystem through connecting the dots together. There's a brother you have in Enugu or in Shokotu that you can mentor and inspire. So we hope that in the next few weeks we're going to launch that battle where we're calling on diaspora network to help our deep tech."

He elaborated: "Deep tech competence is not pervasive naturally. So we need to tap to regions of high concentration so that it can diffuse to region of low concentration so that there can be some level of equality of knowledge."

Another participant described the Africa Deep Tech Foundation: "The goal of Africa Deep Tech foundation is to build deep tech for Africa. That is the goal—like you build deep tech for Africa, by Africans, simple. No more, no less. You're building blockchain, you're building IoT, you're building VR, you're building AR, you're building AI. Whatever it is that you're doing deep tech and this is for Africa and you an African, then this is that kind of space is solely for you."

The most powerful expression of community came in the closing remarks, where Leila encouraged participants to see themselves as part of a larger historical continuum: "The best way to look at how the world works is to look at history. Because there are over 100 billion humans that have lived on this planet. We are not the first; we will not be the last. According to history, as with everything, the minority usually nudges the majority, the individuals and the small group of individuals usually influence the larger majority."

This perspective—of being links in a chain stretching back to ancient African innovations and forward to future generations—offered both humility and inspiration. It suggested that today's efforts, however small they might seem, are laying foundations for transformations that might not fully manifest for decades.

Conclusion: Fire Stolen from the Gods

As the conversation drew to a close, one participant offered a metaphor that captured the essence of Africa's relationship with AI: "In the Greek mythology, Prometheus stole fire from the gods and gave it to humans. And today we can do all kinds of things with fire, including metalwork. We can even cook. So just like fire is a tool, AI is equally a tool."

He continued with practical examples: "When we talk about AI today we have similar tools. You can download an AI model on your computer without Internet. You can download GPT3, GPT4 and you can do all kind of things you want on top of it. We have things like Lambda from Facebook. You can download the offline version of it and build anything you want on top of it."

This framing of AI as "fire stolen from the gods"—a powerful tool that can be downloaded, learned, and applied locally—offers a path forward that balances ambition with pragmatism. It suggests that Africa need not wait for permission to harness AI's potential, nor must it compete on terms set by others.

Instead, by focusing on applications that solve distinctly African challenges, building educational foundations for youth, preserving cultural knowledge, co-creating appropriate policies, and fostering cross-border communities, Africa can chart its own path to AI leadership—one defined not by global rankings but by impact on human flourishing.

"If you want to go fast, you go alone. But if you want to go far, we go together," quoted one participant, reminding the group of traditional African wisdom. Another added: "Fall seven times and stand up eight."

This vision—of technology enabling self-actualization rather than mere survival—may represent the most profound form of leadership possible. In this light, the Biblical wisdom that "the last shall be first" takes on new meaning: perhaps leadership in the AI era will be measured not by who builds the most powerful models, but by who most effectively harnesses AI's potential to unlock human flourishing.

Africa, with its unique challenges, youthful population, clean-slate advantage, rich cultural heritage, and growing cross-border communities, may be uniquely positioned to demonstrate precisely this kind of leadership—not by competing with established players, but by reimagining what AI leadership truly means.

Notes from the Conversation

1. The AI Salon community believes AI will impact everyone, and everyone should impact AI, not just experts but average enthusiasts

2. Africa has unique challenges requiring tailored AI solutions rather than adopting Western benchmarks

3. With 60% of Africans under 30, Africa's young population represents a competitive advantage in the AI space

4. Many participants believe success is not about competing with Western countries but solving local problems effectively

5. Africa has an opportunity to build AI-native systems without being constrained by legacy infrastructure

6. Policy development should be co-created with innovators rather than imposed by consultants with little local context

7. The diaspora represents a valuable resource that should be connected back to the continent through mentorship

8. Cultural context and preservation of traditional knowledge must inform Africa's approach to AI development

9. There's criticism of "career entrepreneurs" who chase grants rather than building sustainable solutions

10. Open innovation and community collaboration are essential for Africa's AI development

11. Data scarcity in sectors like agriculture presents a significant challenge for AI development in Africa

12. Africa produces 30% of the world's rare minerals essential for AI hardware, presenting an economic opportunity

13. Technology transfer from the diaspora needs structured programs to be effective

14. There's a tension between collaboration and competition among African entrepreneurs that affects innovation

15. Association-building (AI associations, blockchain associations) can help shape policy through collective expertise

16. Educational systems need fundamental reform to incorporate AI and prepare youth for an AI-driven future

17. Experimentation should happen in "labs" before commercialization to avoid redundant startups

18. AI should be viewed as a tool (like "fire stolen from the gods") that can be downloaded and applied locally

19. Community-building across countries is key to creating a pan-African approach to AI

20. The ultimate goal should be using AI to enable more Africans to self-actualize rather than focusing on basic needs

Open Questions

1. How can Africa balance building AI solutions for local problems versus participating in global AI development?

2. Is Africa truly in competition with the rest of the world in AI, or should it focus on its own development path?

3. How can Africa retain talent when many skilled professionals are migrating to Western countries?

4. What sustainable funding models can support AI innovation in Africa beyond foreign grants?

5. How can educational systems be transformed rapidly enough to prepare youth for an AI-driven future?

6. What role should government policy play in fostering AI innovation without stifling entrepreneurship?

7. How can African entrepreneurs balance collaboration and competition to drive innovation effectively?

8. What mechanisms can ensure that traditional knowledge is preserved and enhanced by AI rather than displaced?

9. How can Africa build the necessary computing infrastructure when GPUs and other hardware are expensive and scarce?

10. What are the most urgent sectors where AI should be applied for maximum impact in Africa?

11. How can AI innovation in Africa avoid the pitfalls of "career entrepreneurship" and focus on real solutions?

12. How can African countries harmonize data protection regulations to enable cross-border AI applications?

13. What role should external funding play, and how can it be structured to avoid neo-colonial dynamics?

14. How can Africa create an open innovation culture when there's concern about ideas being stolen?

15. How can AI initiatives in Africa be more inclusive of rural communities and marginalized populations?

16. What metrics should be used to measure success in Africa's AI development beyond Western benchmarks?

17. How can African innovation move beyond solving immediate problems to creating transformative technologies?

18. What ethical frameworks should guide AI development in Africa considering its cultural diversity?

19. How can we ensure that AI development doesn't exacerbate existing inequalities on the continent?

20. How can Africans build resilient innovation ecosystems that don't depend on foreign support?