Preparing the workforce for the AI economy: Closing the AI skills gap

Aishat Iretiola Abisiga is a passionate software developer, aspiring AI innovator, and Computer Engineering student at Yaba College of Technology. She was recognized as the Best Graduating Student with the Highest WAEC Result at Aquinas Private College, where she also served as Head Girl.

Her achievements include developing an experimental programming language, contributing to AI projects, authoring a biomedical engineering publication, and earning a National Skills Qualification in Web Application Development. She is driven by a passion for technology, innovation, and impactful solutions.

In this report, she shares insights on how to optimise the AI economy.

Section 1: Understanding AI and the Workforce

1. How is artificial intelligence changing the way people work across different industries?

Well, AI is changing a lot of things without us actually realising, probably because we don’t pay much attention to it. I mean, your bank app literally flags a transaction before you even realise something is wrong. Students like me and young freelancers use AI to write, design and debug code in about half the time it would normally take. Farmers are starting to get crop and weather advice from AI-powered tools. And zooming out, it’s the same everywhere: hospitals use it to detect diseases, factories use it to reduce waste, and offices use it to handle all the boring paperwork.

It’s interesting that AI isn’t exactly taking whole jobs, it’s only taking parts of them, the parts that seem repetitive. But we still need humans, because AI can’t truly understand context or take responsibility for decisions the way a person can. So why worry about whether AI WILL take your job, when you can think of ways to adapt to the changing system?

2. What does the term AI skills gap mean, and why is it becoming a major concern for employers and employees?

So, the AI skills gap is basically the distance between what employers need and what employees can actually do right now. Companies want people who can work with AI tools, but a lot of workers, and even fresh graduates, were never trained for that. That’s a problem for employers, who can’t find the right people, and for employees, whose skills are getting outdated faster than they can catch up.

Some of us think AI has already replaced workers. It hasn’t. But if you can work with AI, you have a very good chance of getting a job or keeping the one you have.

3. Which AI-related skills do you believe will be most important for workers over the next five to ten years?

The first one is AI literacy, basically knowing what AI can do, what it can’t, and when it’s just making things up. Then comes knowing how to actually work with the tools, like giving clear instructions and getting useful results out of them. Data literacy matters too, because AI runs on data.

But the one I’d put at the top is the ability to check AI’s work. Anyone can get an answer from AI now. The real skill is knowing whether that answer is correct.

4. How is AI affecting employment opportunities for graduates and young professionals?

Honestly, it’s a double-edged sword. In Nigeria, a lot of graduates were already struggling to land a first job, and now AI is taking over basic entry-level tasks like data entry, simple writing and customer support. It’s the same globally, so companies expect more from fresh graduates than they used to.

But a young person who knows how to use AI properly can do the work of someone with much more experience, and some are using it to start freelancing or small online businesses. So AI isn’t closing the door on young people, it’s changing what the door looks like. Will you walk in with a certificate alone, or with the skills to back it up?

5. Do you think AI will create more jobs than it replaces, or will it lead to widespread unemployment? Why?

Personally, I don’t think it’ll lead to widespread unemployment, at least not the way people fear. We’ve seen this before. When computers came, people said offices would be empty, but the jobs just changed. Social media manager wasn’t a thing a few years ago, now it’s a full career.

Will AI create more jobs than it replaces? Probably, in the long run. But the in-between part is going to be rough, especially here where training isn’t easy to come by. So for me, the real danger isn’t “no jobs”. It’s people being left behind because they didn’t get the skills in time.

Section 2: Education, Training, and Skill Development

6. What role should universities and other educational institutions play in preparing students for an AI-driven economy?

Schools can’t keep teaching like it’s still 2005. A lot of us in Nigeria sit through lectures where the goal is to memorise notes and pass exams, while the companies we want to work for already use AI every day.

Schools should teach AI literacy to everybody, not just computer students, let students actually use the tools instead of banning them, and work with companies so students get real experience. The schools that will do well are the ones that train students to think and solve problems, because that’s what AI can’t do for us.

7. How can workers with little or no technical background develop the skills needed to work alongside AI?

First of all, you don’t have to be a “tech person” to do this. Using AI is not the same as building it. If you can explain clearly what you want, you can already start. Pick one task you do every day, like writing emails or planning your schedule, and try an AI tool for it. Some results will be bad, and that’s fine, that’s how you learn. Free courses and YouTube are enough to get going, which matters here where data isn’t cheap.

A lot of people hold back because they feel learning alone is pointless, so they wait for a friend or colleague to join them. But if you wait for someone else, you might wait forever. Start by yourself, then share what you’ve learned. The only real mistake is waiting until you feel “ready”, because nobody does.

8. Are current educational curricula adequately preparing students for the demands of the AI economy? Why or why not?

Not really, and I think most students already feel it. In a lot of schools here, the curriculum takes years to update, so by the time something new gets added, the industry has moved on. We learn a lot of theory, but there’s very little practice with real tools, and sometimes the lecturers haven’t had the chance to train on the latest technology either, so it’s not even their fault.

It’s not just Nigeria, though. Even countries with more resources are struggling to keep up. So the answer is no, not yet. But it’s fixable: update the curriculum more often, train the lecturers, and treat AI as part of the course instead of something extra.

9. What practical training programmes or certifications would you recommend for individuals who want to build AI skills?

Start with the free stuff, because you can learn a lot without spending money. I’m speaking from experience, since I took Introduction to Computer Science on edX, taught by a lecturer from Harvard, and it was very beneficial. Google, Microsoft and Coursera also have beginner AI courses, and many of them can be audited for free. If you want a certificate to show employers, Microsoft’s Azure AI Fundamentals is a good first one, because you don’t need to be a programmer. And here in Nigeria, the government’s 3MTT programme is also worth looking into.

But a certificate alone won’t carry you. After any course, build something small, like a simple chatbot or a report you put together with AI tools. A certificate says “I attended.” A project says “I can do it.”

10. How can organisations encourage employees to continuously learn and adapt as AI technologies evolve?

Nobody learns well when they’re scared of losing their job. So first, organisations should make it clear that learning new tools is about helping staff grow, not replacing them. Then give people time, even an hour or two a week, because telling workers to learn AI on their own time just doesn’t work.

Pay for courses or point people to free ones, let the quick learners teach the others, and reward the effort with recognition, a bonus or a promotion. The companies that keep up are the ones where learning is part of the culture, not a one-time workshop.

Section 3: Employers and Workplace Transformation

11. What challenges do companies face when trying to recruit employees with AI-related skills?

The first problem is simple: there aren’t enough people with these skills, so the few who have them can pick and choose. In Nigeria it’s worse because many of the best ones leave for companies abroad, and local businesses can’t match foreign salaries.

Then there’s what companies ask for. Some job posts want one person to do the work of three, with years of experience in tools that barely existed two years ago, so good candidates don’t even apply. On the other side, many fresh graduates have certificates but no real projects, so it’s hard for employers to know who can actually do the job.

12. How can businesses identify the AI skills their employees currently lack?

Just ask them, honestly. A short survey or a simple practical test, like “here’s a task, show us how you’d do it with AI”, tells you far more than a CV does. You’ll quickly see who’s already using these tools, who’s curious, and who’s lost.

Then compare that with where the business is heading. If the company plans to automate reporting next year, find out who can handle that now. That’s the gap. You can’t fix what you haven’t looked at.

13. What strategies can employers use to retrain and upskill existing workers rather than replace them with AI systems?

Retraining is usually the smarter move. These workers already understand the business, the customers and how things really run, and no AI tool picks that up overnight. Replace them and you lose all of that.

Start with their current jobs. Show a customer service staff how AI can handle the repetitive questions, so she can focus on the difficult customers. Pair beginners with colleagues who already know the tools, and let people move into new roles inside the company. Where jobs are hard to come by, a company that trains its people also earns a lot of loyalty.

14. How can employees use AI tools to improve productivity without becoming overly dependent on them?

My rule is simple: use AI to start the work, never to finish it. Let it give you a first draft, an outline or a quick summary, then do the thinking yourself. Check the facts, change the wording, make it yours. AI gets things wrong, and sometimes sounds very confident while doing it.

Also try some tasks without it every now and then, like a gym for your brain. If you can’t write a simple email or solve a basic problem without opening an app, that’s a warning sign. The goal is to be faster, not to forget how to do the job.

15. What human skills, such as critical thinking, creativity, communication, and problem-solving, will remain important in an AI-driven workplace?

All of them, honestly, and they’ll matter even more. AI can produce a lot, but somebody has to decide what’s worth producing, what’s correct and what’s right for the situation. That’s critical thinking, and it’s not going anywhere.

Communication is another big one. Explaining an idea to a team, calming down an angry client or convincing your boss needs a real person. Same with empathy and good judgement, especially when a decision affects other people. Employers keep saying these skills are hard to find, and I think that’s because no tool can really teach them for us.

Section 4: Closing the AI Skills Gap

16. What can governments do to make AI education and training more accessible to the general workforce?

First, the basics. It’s hard to learn AI when data is expensive and the light keeps going off, so government has to deal with data costs, electricity and access to devices. It’s not glamorous, but without it nothing else works.

After that, put AI literacy into the school curriculum early, and support affordable training for people who are already working. Programmes like 3MTT are a good start, but they need to keep reaching people outside the big cities too.

17. How can public-private partnerships help reduce the AI skills gap?

Government can’t do this alone, and neither can companies. Government has the reach and sets the direction. Companies know which skills are actually needed and have the tools and the money. Put them together and training stops being just theory.

We’ve already seen some of it here, with MTN Nigeria putting money into the 3MTT programme, including data grants to help learners stay connected. The best partnerships go further and let companies tell schools what they need, then hire the people who come out.

18. What barriers prevent people in developing countries, particularly Nigeria, from accessing AI education and training opportunities?

There are quite a few, and they stack on top of each other. Data is expensive, electricity is unreliable, and a lot of people don’t own a good laptop, or even a smartphone that can handle the tools. You can’t take an online course if you can’t stay connected for an hour.

Then there’s the school side: outdated curricula, and lecturers who haven’t been trained on new tools themselves. Most learning material is also made for people in other countries, so it doesn’t always fit our situation. And when someone does get the skills, there’s a good chance they’ll leave for a job abroad.

19. How can we ensure that AI training opportunities reach women, people from disadvantaged backgrounds, and workers at risk of job displacement?

By going to them, instead of waiting for them to show up. Many women and people from poorer backgrounds never hear about these opportunities, or can’t afford the data, the transport or the time. So training should be cheap or free, flexible, and available on a phone. Evening and weekend classes help a lot, especially for women balancing work and family.

Scholarships and community learning centres matter too, particularly outside the big cities. For workers at risk of losing their jobs, the training has to be practical and quick, tied to a real job they can move into. And inclusion has to be planned from the start, not added at the end.

20. If you could recommend three practical actions to prepare today’s workforce for the AI economy, what would they be?

Number one, make AI literacy a basic skill, taught early in school and available to anyone already working. Everybody should at least know what AI can do and what it can’t.

Number two, make learning affordable and easy to reach. That means cheap data, free and low-cost courses, and training that works on a phone. Number three, get government, companies and schools working together, so training matches the jobs that actually exist.

If we do these three things, AI becomes an opportunity for a lot of people and not a threat. The technology isn’t the hard part. Getting people ready in time is.