Transcript of Panel Discussion on Small AI: More and Better Jobs at the World Bank Group (WBG) – International Monetary Fund (IMF) Annual Meetings on 12 October 2026 in Bangkok, Thailand

Rajini Vaidyanathan, Moderator and Chief Presenter of BBC World Service Moderator:

Do join me in welcoming three leaders who are helping to shape that conversation. I'm joined by Ajay Banga, President of the World Bank Group, President Tharman Shanmugaratnam, President of the Republic of Singapore, and Kristalina Georgieva, of course, the Managing Director of the International Monetary Fund. Welcome to all of you.

Welcome to all of you. The 81st meeting, as we were saying? And a lot has changed, of course, hasn't it?

So, I think we'll start with you, Ajay. This session is called "Small AI: More and Better Jobs.” Jobs and opportunity are at the heart of the World Bank's agenda. How's the Bank changed in that way, and how does AI fit into all of this right now?

Ajay Banga, President of the World Bank Group: Yes, thank you. Being on the panel with the two of them is a privilege, and I'm lucky to be here.

I believe that the Bank's entire focus has to be on jobs for a very simple reason: 1.2 billion young people in the coming 15 years are going to become 18 years of age. So that could be a huge demographic dividend if, when they're growing up, they get clean air, clean water, healthcare, education, skilling.

But once they're grown, they need the opportunity to have and be a productive part of society.

So, the word “job” does not mean working for a big company or a small company or as an entrepreneur. It's being productive in society, having a sense of optimism and a sense of dignity that comes from earning and being a part of that system. That's what we're talking about.

The bank's entire focus has moved towards that over the last few years. It's not that we don't build a school, or we won't build a highway, or we won't build a skilling centre or a healthcare clinic. We have to do all those, but we got to do them with the perspective of job creation.

Which starts from having the right foundations, which is physical and human infrastructure, having the right governance and policies in place, something that Singapore has done very well in its history.

And then having the right way to de-risk private capital to be able to come in and invest at scale because it is private capital that creates jobs. Governments enable, and the private sector generates between 75 and 85 percent of jobs in any country. That's what we are trying to do.

How does AI fit in? In the emerging markets where the conversation is not about large language models, where people are concerned about the possible impact on jobs - possible, not proven yet, but possible.

In the emerging markets, it's about applications that could add enormously to productivity for a school, an educator, a healthcare system, an agricultural system for small farmers to get to scale. And hopefully, as we speak, as well as from subsequent panels, you'll get a bunch of examples of that type.

That is what we are focused on: the rollout of small AI into the emerging markets as a productivity enhancer.

Moderator: Okay, thank you very much, Ajay.

Let's move on to you, President Tharman. Ajay mentioned your country and the work that you're doing when it comes to developing AI. You've said in the past that AI may disrupt jobs in advanced economies but could create a different risk for developing economies. And Ajay made that distinction in some way just then. You said that new jobs may simply not be created fast enough in developing countries.

What do developing nations need to do now, President Tharman, to make sure that their young people are able to participate and benefit from the next wave of technology and economic growth? And as we just heard there from Ajay, you know, it's the future of young people and jobs that's so crucial to all of this conversation.

Tharman Shanmugaratnam, President of the Republic of Singapore: Good. Well, I’ll take off from what Ajay said, although I'll speak at 10 percent the pace that he spoke at.

The first thing we have to realise is, it's early days. This is not a one-off shock. This is a whole new era.

And we should start with the recognition that growth is going to be critical to secure good jobs, but growth is not in itself going to be sufficient to achieve good jobs. The evidence is already there. If you look at China, India, developing Southeast Asia, they're growing quite well, but job creation is weak.

So, there's already a divergence between growth and job creation, and AI is going to widen that divergence if we are passive in how we deal with it.

We've got to do everything we can to, first, use AI to create good jobs, and second, to create jobs that can be done well by humans despite AI.

Second thing we've got to be concerned about and avoid is a K-shaped economy and a K-shaped labour force.

In the first wave of automation, it was the lower-skilled manufacturing workforce that fell out; some of them moved into services, to the gig economy and so on.

This time around it is the broad middle in the workforce that we have to be concerned about.

We cannot afford to have a K-shaped workforce or population where the broad middle in the workforce and the skills they have accumulated falls out.

So, bear those two broad, structural challenges in mind.

I'm an optimist, like Ajay and Kristalina. I think there are sectors of the world economy that still offer very significant promise for the developing world.

First, don't give up yet on manufacturing. There are whole swaths of the labour force of the developing world where costs are much cheaper than in China and are still cheaper than robots. Just look at the four or five states in India that are now growing at a remarkable pace in export manufacturing. If the other states could do the same, India gets lifted up despite its late start in exporting. Look at Vietnam. They each show what is possible by courting investment, making land available without encumbrances, sorting out labour regulations so that workers can be hired and move up the ladder.

Second, green energy is another opportunity for jobs, with multiple benefits.

It provides for energy security, for sustainability, and it allows you to take part in the AI economy because you need energy. But it's also a job multiplier. Because renewable energy generates three times as many jobs as fossil fuel energy for the same million dollars that you invest in building out.

Third opportunity: think of the jobs that can be enhanced by AI but are very unlikely to be displaced by AI. Healthcare has huge opportunities for job creation in the developing world.

Just closing half the gap in standards compared to the advanced world will require many more doctors, nurses and community health workers. The proportion of nurses per capita in the developing world is one-fifth to one-tenth the level of the advanced countries. In India, community health workers too are now a major part of the health system, helping with immunisation, maternity health, and helping to educate families.

So, it's a whole set of jobs in healthcare that can be created.

Finally, a point which cuts across sectors.

AI is going to blur the distinction between being an employee and being an entrepreneur. We are seeing the rise of the one-person company, companies that start with one person, and may then bring in a few more.

It’s a new phenomenon that's already coming up in many parts of the developing world and the developed world. And we should encourage it. It’s a new form of job creation, but it's different. You have agency.

Small players using AI can reach markets and access knowhow and technology much more efficiently and at lower cost compared to before.

What can we do to support this? Zhejiang province in China is an example - they have set up a service alliance for one-person companies, providing shared access to computing power, AI models, and professional services.

So that's itself a new growth sector in the job market, and we've got to encourage it.

Moderator: Thank you, President Tharman. It's interesting you mentioned healthcare there because we do have a speaker who's using small AI in India coming up in the programme. So, we'll get more on that later. Thank you.

Kristalina, now over to you. What's the economic impact on all of this, particularly, of course, in developing countries, as we've heard?

Kristalina Georgieva, Managing Director of the International Monetary Fund: So, AI, love it, hate it, fear it, it is here. And we are already seeing the first wave of impact. It is a demand shock, an investment shock that has lifted up growth in a small number of economies because of construction of data centres, because of the investment in the models that are driving AI.

When you look at supply chains, you have, broadly speaking, three economies: United States, China, India, that are the most important AI producers. But then you have those that build the infrastructure for AI, and many of them are in Asia, including Thailand.

So that shift in higher gear is what is keeping the world economy growing at 3 percent, around 3 percent, despite the fact we are being dragged down by the energy supply shock.

But this is only the beginning, and this is not the most exciting thing of the AI story. The next wave of AI would be adoption, and there, everybody can participate.

Actually, adoption, if we work hard to have the basics for it, can be very democratic. As democratic as the cell phone.

However, we have to be fair and safe for developing economies. There are some preconditions, and the World Bank Report is very clear about them.

Well, you need access to electricity. You need access to digital infrastructure. People have to be geared to adoption, and the government should be able to give some safety, protect against bad actors, so that adoption can work.

We have done some estimates. I admit, we all look into the future, and it's a bit foggy. By our estimates, growth in Asia, for the advanced Asia, can go up somewhere between half a percentage and one percentage point. One percent additional growth is a very big deal. And even in the emerging Asia, it could be somewhere between 0.2, 0.8 percent.

Now, when I talk percentages, very often people say, "So what? What is one percent” Let me tell you what it is. If advanced Asia, that is ageing very rapidly, was to gain one percent, this would more than offset the loss that comes from ageing population. So, AI would compensate for ageing in and even exceed that compensation.

Now, why is it that we are excited about AI? It is a transformative technology. It so completely changes how we work, how we live. I'll finish with this.

This morning, my AI assistant, in the 30 seconds instruction that it gives me every day, said, "Your number one thing today is the panel with President Ajay Banga and President Tharman. Be ready.”

Moderator: Thanks, Kristalina. Imagine if it got it wrong. It told you you were doing something else.

Ajay Banga: They say AI can give you false results. The only real president in this group is this guy. The rest of us are not. So, I think there's the false result.

Moderator: Well, I'm going to call you President of the World Bank right now. So that's not an AI instruction. So, let's get back to you then, Ajay.

So, we heard from Kristalina there talking about the economic opportunities, particularly in developing countries. I want to pick up on what this event is all about in some ways, which is Small AI in developing countries. What does it look like in practice, Ajay? And how can it create jobs and opportunity?

And I think just picking up from what Kristalina said about electricity and, you know, getting people online in the first place. How can Small AI be accessible in the way that it sort of developed? It's different, isn't it?

Ajay Banga: Yeah. So, you know, I've been very fortunate that President Tharman has helped us at the Bank run what's called a Jobs Council. He's the co-chair of it. And we have a group of people from academia, from public and private companies, as well as from civil society.

And we came out with five sectors that were critical to grow jobs. All of which are not reliant on outsourcing jobs from the developed world to the developing world, kind of the last 30, 40 years model, but instead build locally relevant jobs. And those five sectors connect to this conversation.

The first is infrastructure. It's construction, but then what it enables: bridges, roads, airports, digitisation, electricity, water, but also human infrastructure in terms of skilling and education and the like.

The second is agriculture for small farmers. Most of our economies are very heavily dependent on food grown by small farmers. They get competed to the point where it's tough for them to play in the system. But access to cooperatives, access to technology of the type we are building - I'll give you a couple of examples - enables them to get past that.

The third one is primary healthcare and its delivery. President Tharman was just speaking to it. But think of Indonesia with primary healthcare centres, each with a nurse, a midwife, and a medical diagnostic technician. Think of the quality and number of jobs you create through that extension and then use technology and AI to connect to remote doctors and the skills that may not be present in a primary healthcare centre.

And the fourth is tourism and what it can multiply in terms of jobs. I mean, Thailand is a principal example, but they've got ambitions to go even further than what they've done this far.

And then manufacturing. Particularly value-added manufacturing, which is not pure extraction but creation of local jobs. Minerals and metals, the emerging markets are gifted with large quantums of deposits, but they need real quality jobs. But also look at Africa, the creative industries or the like.

There's so many opportunities on manufacturing across. Whether you do this as an entrepreneur to President Tharman's point about individual agency, or you do it out of working for others, all are possible. That's the idea.

Examples. Healthcare clinic in Indonesia: you're the patient, I'm the nurse. You walk in and you say, "I have a rash here.” And I look at it, and I can't figure out what it is. But I can take a photograph and send it to the doctor I share with 20 other clinics.

Moderator: I do actually have a rash right now.

Ajay Banga: Sorry about that, but I'll ask the doctor to intervene. And so, he in turn can either look at it himself or run it through a simple local AI tool developed at the edge in a 3G phone, local. It's very simple to do. Gets that and says it's an eczema. Give her this appointment. Tell her to go home. Or, don't like it, tell her to come to the regional hospital to meet the specialist in 14 days at 10:30 in the morning.

That is a very difficult thing to do, even in the advanced economies today. Getting a specialist appointment organised digitally is a very hard thing to do. So, you can cut through the arbitrage of all this by creating simple AI tools.

Another one, something we're doing right now with farmers in India and elsewhere, with Google's help actually. And I think the…

Moderator: We’re going to be talking about that.

Ajay Banga: …Google guys around town…

Moderator: …in the next panel. Yeah.

Ajay Banga: …you're going to see this. It's the idea is a platform that's been built to connect farmers and cooperatives to better fertiliser, better seeds, better crop insurance, better credit, and most importantly, better offtake prices for their product.

And so, an illiterate woman farmer in India can point a 3G phone at the back of a leaf and say ‘that disease’. I don't need to know the name, but that disease equal to this insecticide. Press the button because India has put bank accounts in everybody's hands. You press the button, 25 rupees. That insecticide at my cooperative. That's the kind of stuff that small AI is about.

The reality is that large language models are estimated probably to create some degree of disruption in jobs of the developed world. But by the time you get to middle income countries and lower middle income countries, actually the opportunity from Small AI to build jobs and build productivity is enormous.

That's what we are trying to do, and that's what the Jobs Council started out. In fact, the “Small AI” word came from a Jobs Council meeting with President Tharman.

Moderator: Okay, thank you. And I think what's interesting, isn't it, Ajay, is the accessibility of it. Like you say, it can just be in someone's pocket. Countries like India, where smartphones have a huge uptake.

We'll come to you next, Kristalina. You've described AI as a tsunami for the labour market, with young entry-level workers especially exposed. What should policymakers be doing now to ensure that it creates more opportunities rather than disrupts? And I know President Tharman touched on some similar areas already.

Kristalina Georgieva: Well, it is a slow-moving tsunami, but tsunami nonetheless. The impact over time on jobs globally, we estimate to be around 40 percent jobs either augmented, or kind of downgraded, or eliminated.

And we are already seeing some of this impact. In advanced economies, 60 percent. Low-income countries, 23 percent. You may say, "Oh, they are better off.” No, that is just because AI is further away. The Small AI hasn't quite yet reached all of them.

So, you're asking a question that is really important to answer: What can be done?

Well, first we need to carefully research what is happening in the labour market. We have to gather information, analyse this information. And this is what we do at the Fund.

We did a study in the United States that shows that already 10 percent of jobs require AI skills, higher skills. They pay better. It shows that the routine, repetitive jobs are shrinking.

And very interestingly, it shows that low-paying jobs are increasing. And they're increasing in two directions: construction, data centres, and services.

And you would ask, and the net impact of the area we studied is actually positive, but that's not a story to celebrate because it is positive on the side of low-paying, lower-paying jobs.

And when we look at this, what we recognise is that the people to worry about first and foremost: young people that are coming into the labour market. Normally, they would get into these routine, repetitive jobs and then grow up the ranks. But if they're gone, I don't think any young person wants to be a barista in a coffee shop as, you know, professional future.

So, from studying… so, my first point is study, understand what is happening. You know, burst the myth that AI is shrinking demand for people. What it is doing is it is shifting demand for people now. That may not be the case in the future.

Second, get governments to recognise they have a huge responsibility to rethink how education should be done in the world of AI. And recognise that no more we can acquire a skill and hold on it for our life, and that lifelong learning is actually a paramount necessity.

And three, and what I would say clearly would show I'm the managing director of the IMF. Think about the fiscal side of the story. Why? Because traditionally governments would generate revenues by taxing mostly people. Well, if AI changes the structure of the labour market, and then there is less labour, more capital, what do we tax? How do we generate the revenues so governments can help play their most important role, which is help society adapt to the world of AI? If revenues are shrinking, they would be in a tough spot.

So to make that long story about the slow-moving tsunami short, we cannot today imagine what exactly the world of work will be five years from now. But we can be disciplined and carefully assess what is happening and then draw lessons. But most importantly, act on them.

Moderator: Okay, thank you, Kristalina. You mentioned a lot of things that government should do. Conveniently, we do have a president sitting next to you. Obviously, you have a role on the Jobs Council as well. There's lots of really interesting points that Kristalina raised about fiscal issues, about skills in particular.

And let me ask you about skills then. Because you've emphasised the need to invest in skills regularly, particularly the importance of public-private partnerships.

What do you think governments and businesses can do differently then, to make lifelong skills development a reality? I mean, it really does pick up on what we've just heard from Kristalina, doesn't it?

President Tharman: Well, you know the silver lining in the displacement of human skills by AI is that it's going to happen task by task. And that gives us time - whilst people still have jobs, there's that opportunity to adapt, to learn new skills, to build on what you already know and stay agile.

So, AI isn't like a tsunami, it isn't going to come all of a sudden, just as Kristalina was saying. It takes time to be diffused through the economy, and what's critical is to keep learning on the job.

There is a particular problem that we have to address soon, though, across the world – in advanced countries and developing. And that, is that there is less hiring been seen at the first rung in employment, your first job upon graduation.

It's clearest in the most AI-exposed sectors, the tech companies themselves. But it's becoming clear across the board in the US and elsewhere.

How to respond? What governments did to support the first job, as a crisis measure during COVID, and what some governments did during the global financial crisis, now has to be part of the menu of structural policies that governments have – not merely for a crisis, but for new era. Governments have to get involved with the private sector to make that first job possible, to make that pathway to a career ladder possible.

We can't afford to lose that. Because if you lose that, and a cohort of young people waits say a year before getting a job, you are not only then competing with the next cohort the following year, you also lose skills, you lose intangible aptitudes, and you lose trust in the future.

So, there has to be a public-private collaboration, with the public sector incentivising the private sector to take in fresh graduates, so they get that first foothold in the market, and they can learn from there.

But we also want to work backwards from what's happening in the world of work, into the changes required in tertiary education.

If we think about how we avoid the middle of the workforce getting displaced, it means we also have to change how they get educated.

If you look around Asia, you look around the developing world, and in fact, if you look around the advanced world, the reality of higher education, universities and the like is that it's overwhelmingly academically-focused. And here again, the data is already clear: the link between academic credentials and career prospects is weakening.

In the U.S. for the first time in a century, demand for graduates has gone down. The wage premium that college graduates earned (compared to non-college graduates) has also gone down significantly.

So, we've got to take these as early signals of a new era. Work this backwards into the education system, and reduce that academically oriented skew, and work towards an education that's more applied. More bursts of work as part of education - more internships, or more of the dual model of education where you spend serious time in a firm as part of your tertiary education.

That's a major shift that has to be made. It's a critical issue for developing countries where you still have to develop that applied education stream.

But a final point I'll have to make is one that comes from what Kristalina said about the fact that we don't know what will happen in five years' time.

We need some humility in education planning. Don't fixate on one particular model of education, particularly on the issue of depth versus breadth in higher education. We don't know what will be required in time to come. The reality is, in some areas, you will need a serious depth of expertise to stay agile and be able to learn continually on the job. And there'll be other areas where you need more breadth of exposure to different disciplines, say because you have to integrate AI across functions, or you've got to interact widely or do many varied tasks that require a breadth of human skills. But there is no one model.

So don't fixate on one model. Being clear-eyed means recognising that the future is fuzzy, and we just have to be agile. Not just within firms and industry, but in pathways within education itself.

Moderator: Okay, thank you so much, President Tharman. We've run out of time, but it was really interesting to talk to.

I wonder if, just in two words, you can just give me, or three words, a quickfire thought on where you think things are going to be. You mentioned five years, things are going to change a lot. Where, what you would like, your one big goal in five years' time? Start with you, Ajay.

Ajay Banga: A realistic application of Small AI in as many emerging markets as possible. That's what I'd like to get to.

Moderator: Thanks, Ajay. President Tharman?

President Tharman: Well, avoid a new divergence between the developing world and the advanced world. And see a continuation of the convergence we've seen in East Asia, using AI, using technology, and developing the best of human capabilities.

Moderator: Okay. Thank you, and last but not least, Kristalina.

Kristalina Georgieva: Get AI to do all the stuff we don't want to do and let us enjoy the things we love to do. High productivity, high standard of living, but also the dignity of being socially viable.

Moderator: Thank you so much for your time, all of you. Round of applause, everyone. Thank you, Ajay. Thank you, President Tharman. Thank you, Kristalina. Thank you. Thank you.