Beneath the Surface: Why the Generative AI Dividend Depends on Going Deeper

By Richard Sebaggala

A few weeks ago, I sat across from my longtime friend Allan as we enjoyed a quiet lunch at a beautiful hotel in Entebbe. The breeze from Lake Victoria carried a gentle calm, while our conversation turned, as it often does these days, to artificial intelligence.

Allan shared how he uses AI tools like ChatGPT to simplify his routine. He mentioned things like getting quick summaries, organizing his thoughts, or generating short drafts. Like many people, he saw AI as a helpful assistant. However, when I showed him how I use the same tools for in-depth document analysis, extracting patterns from research data, and explaining complex concepts to students, his expression shifted. He paused and admitted with some surprise, “I didn’t know it could do all that. I think I’ve only been using it on the surface.”

That moment stayed with me.

It reminded me of another experience just a few Sundays before. I was in church, listening to Pastor James Kiyini preach a heartfelt sermon about salvation. His message was clear and filled with passion. As he spoke, my thoughts drifted briefly to artificial intelligence, a completely different subject, yet oddly connected.

It occurred to me that those of us who have gone deeper into AI often find it difficult to explain its full potential to those who have only used it casually. It is similar to trying to explain the power of faith or salvation, or the depth of love, to someone who has only skimmed the surface. Words alone can’t communicate transformation. It must be experienced.

This gap between surface users and deep users of AI is growing. It is no longer just a technical issue. It is also becoming an economic one. Recent reports show that the demand for generative AI skills has skyrocketed. In one year alone, job listings asking for AI-related skills more than tripled. Employers are even prioritizing candidates with AI experience over those with traditional qualifications. A shift is clearly underway in how we define value and talent in the workforce.

Yet even as workers, especially younger ones, begin to embrace AI, many institutions are falling behind. A global survey by McKinsey found that only about one-third of companies are actively involving senior leaders in AI adoption. Fewer still are integrating AI meaningfully into their daily operations. This is not just a missed opportunity. It is a structural limitation. Individuals can only go so far when the systems around them remain unchanged.

It is now clear that engaging deeply with AI is not optional. It is essential. But the responsibility to make that shift cannot be left to individuals alone. We need support structures, leadership, and an enabling environment. Institutions such as universities, government bodies, businesses, and even faith-based organizations need to ask tough questions. Are we preparing people for a future where generative AI is no longer a special advantage but an expected baseline? Are we equipping our teams to explore, test, and build with AI, or are we merely observing from the sidelines?

The good news is that access to AI tools has never been easier. Many of the most advanced platforms such as ChatGPT, Gemini, Avidnote, DeepSeek, offer free versions. Anyone with curiosity and an internet connection can begin to explore the deeper layers of AI.

This kind of access is unprecedented. In past technological revolutions, tools and knowledge were tightly guarded or prohibitively expensive. Now, some of the most powerful tools in the world are available to everyone, at no cost, at least for learning. That makes this moment particularly important for Africa and other developing regions. For decades, lack of infrastructure and financial barriers have kept us behind in global technology trends. AI provides a rare opportunity to change that. The tools are here. The door is open.

Today, what separates people is not access but how deeply they are willing to learn and apply what is available. That shift from scarcity to depth marks a profound change in how we think about technology and progress.  I believe that this could be the most inclusive technological revolution we have ever seen. For the first time, the global knowledge economy has a real chance to become more equal. However, this will not happen by itself. It will take intention, effort, and leadership.

We need institutions that actively invest in building AI capacity. We need schools, workplaces, and public offices that create room for experimentation and learning. Leadership should not simply approve AI use; it should drive it, integrate it into decision-making, and normalize it as a tool for problem-solving and innovation.

This is not just about productivity. It is about empowerment. People deserve the chance to be full participants in the digital future, regardless of where they were born or how much they earn. What I have learned, in both life and work, is that real transformation never happens at the surface. Whether in love, faith, or technology, it is depth that makes the difference. We need to go beyond convenience and curiosity and begin to engage with AI as a serious tool for personal growth, institutional transformation, and national development.

The deeper we go, the more value we unlock. That is the AI dividend. And it is ours to claim—if we are willing to reach for it.

Don’t Blame the Tool: Rethinking Intellectual Effort and Ownership in the Age of AI

By Richard Sebaggala

I have spoken to countless academics, researchers, and students from diverse backgrounds who express a quiet but persistent anxiety about generative AI. They whisper their concerns, often overlooking a simple truth: AI is not magic. It is a statistical machine, a digital parrot that repeats patterns drawn from vast oceans of human data. It works by calculating probabilities. This is engineered brilliance, but brilliance rooted in prediction, not in original human thought.

As someone who has used and tested nearly every major AI tool on the market, I can say with confidence that generative AI is among the most powerful inventions of our time. It can translate, summarize, visualize, code, debug, compare alternatives, and analyze data—often faster and more accurately than we can. Yet despite this, many still ask: if machines can write, where does that leave us? Some feel displaced, sidelined, or even obsolete. But this anxiety often misses the mark. AI, no matter how advanced, is still just a tool. It is no different in principle from the tools we embraced long ago without hesitation.

There is a paradox worth reflecting on. We do not doubt the validity of a graph produced in Stata, nor do we question the output of SPSS when it generates regression results. Those of us in economics and the social sciences have always relied on statistical software to process data and help us see patterns we could not compute by hand. We have learned the syntax, interpreted the output, and confidently reported our findings. The real skill lies in knowing the command and making sense of the results. Why then do we hesitate when ChatGPT helps us structure an email, brainstorm ideas for a project, or draft a first version of a research abstract?

Part of the hesitation lies in what writing represents. Unlike regression or visualization, writing has always been treated as sacred, almost inseparable from human intellect and creativity. But writing is not simply typing words. It is thinking, choosing, constructing, and editing. The act of prompting—framing a question, guiding an argument, anticipating an answer—is itself a form of intellectual labor. Every useful response from AI begins with a human spark. The person crafting the prompt plays the same role as the one interpreting coefficients in a statistical table: they are the mind behind the tool. The machine’s output merely reflects the direction it was given.

When I began publishing essays on the economics of AI, some of my friends assumed I was not really doing the work. A few told me, half-jokingly, that it must be easy since I was "just using AI." What they missed is that the thoughts, the curiosity, the structure, and the point of view in each piece were mine. The tools I used helped me reach my conclusion faster, but the ideas still came from me. You can take away the interface, but not the thinking. What you read is the product of my experience and insight—not a machine’s.

Legal scholar Dr. Isaac Christopher Lubogo has explored the question of authorship in the age of AI. Should work produced with AI tools be credited to the machine or to the human using it? His view is clear. Authorship still lies with the person. AI is no different from a camera or a calculator. It enhances what we already know or imagine. It cannot create out of nothing. It can respond, imitate, and refine, but it does not dream, interpret emotion, or seek meaning in the way a human does.

Those of us trained in economics understand the phrase "garbage in, garbage out." A model, no matter how sophisticated, will only be useful if the assumptions behind it are sound. The same logic applies to AI. A vague prompt produces empty content. A well-formed prompt generates something coherent and often useful. But the credit for that value still belongs to the person who gave it purpose and direction.

Public suspicion toward AI today reminds me of historical fears about other technological advances. When the printing press emerged, it threatened the role of scribes. Calculators were said to ruin mental arithmetic. The internet was blamed for weakening critical thinking. And yet, all these innovations became instruments of empowerment. They liberated people from repetitive tasks and allowed them to focus on what truly matters. Generative AI is simply the next step in this long journey—if we dare to use it wisely.

What concerns me today is how good writing is being treated with suspicion. As journalist Miles Klee recently noted in Rolling Stone, tools like ChatGPT are trained on large datasets of professional writing. As a result, they tend to produce content that follows grammar rules quite well. Ironically, this precision has caused some readers to believe that anything too polished must have been generated by AI. In other words, a typo is now seen as proof of authenticity. If we continue down this path, we risk devaluing the effort and discipline that go into clear, compelling human writing.

And here lies the real danger. Once we start assuming that any well-crafted argument or clean paragraph is the work of a machine, we erase the labor, thought, and voice behind it. We do not just insult the writer. We also erode the principle that effort matters.

Thinking that AI will replace human intelligence is as mistaken as crediting a hammer for building a house. The tool amplifies our ability, but it does not imagine the blueprint. ChatGPT may help us write faster, but it cannot choose our ideas or shape our insights. It is still the person behind the screen who makes the final decision. If we learn to treat AI as an assistant rather than an author, we can start to see it more clearly for what it is—a tool, not a threat.

This is especially important for Africa. For too long, we have remained consumers of technology rather than innovators. Now is the time to change course. We can either watch others master this new wave or take our place in it. We can use AI to strengthen our research, refine our business strategies, and tell our own stories better. But we must first stop viewing the technology with suspicion and start seeing it as a partner in progress.

We already trust Excel for financial models. We do not feel guilty using Stata or R for statistical analysis. Grammarly has become a standard tool for editing. Prompting an AI to help us write or brainstorm should be no different. When used responsibly, it becomes a legitimate part of the thinking process.

History shows us that the future belongs to those who adapt. The pen did not disappear with the rise of the typewriter, and the typewriter did not vanish with the arrival of the keyboard. Each new medium simply extended our ability to express ourselves. AI is the latest medium. It will not speak for us, but it can help us speak more clearly—if we choose to use it that way.

So do not blame the tool. It is only as good as the hand—and the mind—that guides it.

 

The Pool Table and the AI Revolution: A Reflection on the Cost of Late Adoption

By Richard Sebaggala

 

Recently, during a quiet conversation with my longtime friend Moses, our discussion took an unexpected turn — from artificial intelligence (AI) to pool tables. This detour took me back in time, back to my first year of University over two decades ago.

Back then, pool tables had just found their way into our neighborhoods and were especially popular with high school dropouts and younger boys in urban areas of the country. As university students, we initially dismissed the game as trivial and not worthy of our time. But curiosity eventually got the better of us.

 

The experience was humbling.

Every time I approached the table, I was clearly defeated by players who had left their formal education behind. They had already mastered the game, while we, the supposedly more educated, struggled with the basics. The embarrassment was palpable. I quietly withdrew and never played pool again.

That memory resurfaced as Moses and I pondered the rapid rise of AI. The parallels were striking

AI is the pool table of today, only with much higher stakes. It is a tool, a platform, a revolution that touches the essence of intelligence. And like the pool table of old, it is being embraced early by the bold, curious, and unconventional, many of whom have no formal training in AI or technology. They are exploring, experimenting, and inventing new ways of thinking, writing, teaching, and working.

 

In fact, a 2024 survey by the National Bureau of Economic Research found that 39.4% of adults in the US have used generative AI tools like ChatGPT, with 28% having used them for work-related tasks. Notably, even among blue-collar workers, 22.1% reported using generative AI at work, suggesting that adoption is moving beyond traditional tech roles. Furthermore, Generation Z is leading the way in the use of AI. A study by Aithor found that nearly 80% of Generation Z professionals (18-21 year olds) use AI tools for more than half of their work tasks.

 

Interestingly, many of these users are integrating AI into their workflows without formal training. Microsoft's 2024 Work Trend Index reports that 75% of knowledge workers use AI at work, with 46% having started within the last six months. Remarkably, 78% of these users bring their own AI tools to work, often without formal training or organizational support.

 

In the meantime, many professionals, scientists and experienced experts remain on the sidelines — hesitant, skeptical or overwhelmed. Some are waiting for legislation, others are looking for clearer use cases. But the longer we wait, the greater the embarrassment could be when we finally try to engage and realize we have some catching up to do in an area that was once our intellectual domain.

 

A 2024 study by the National Bureau of Economic Research found that the use of AI in the workplace decreases with age: About 34% of workers under 40 use AI at work, compared to only 17% of those over 50. in 2024, a survey by Ellucian found that while the use of AI in academia has increased, there are still significant concerns: 59% of college staff expressed concern about data security and privacy, and 78% of administrators feared that AI could compromise academic integrity.

 

In Africa, these global trends are mirrored. A 2024 survey conducted by KnowBe4 in several African countries, including Nigeria, Kenya and South Africa, found that a significant proportion of AI users are in the 18–34 age group, suggesting that AI adoption is being led by a youthful demographic. However, this enthusiasm is tempered by concerns about data privacy and the ethical implications of AI technologies.

 

In academia, South African universities are looking at integrating AI into their curricula and research. A study by the University of the Western Cape has highlighted challenges such as inadequate technological infrastructure, limited funding and a lack of clear guidelines for the use of AI in education.

These findings underline the importance of a proactive approach to AI technologies in all sectors. Waiting for perfect conditions or comprehensive regulations can lead to missed opportunities and a widening skills gap. It is imperative that professionals, academics, and institutions in Africa invest time and resources in understanding and integrating AI into their respective fields.

 

This is not just about technology. It's about identity, relevance, and the future of work. AI is a tool for thinking — fast, smart, and scalable. Delaying the adoption of AI could mean missing out on one of the greatest opportunities of our generation.

 

As an economist by training, I never considered myself tech-savvy. In fact, I often felt out of place in conversations about emerging technologies. But when I recognized the transformative potential of AI, I made a deliberate choice not to be left behind. I committed time to exploring and experimenting with AI tools, and that decision has paid off. Today, I can confidently say I operate at the same level as many professionals with a tech background. It’s a reminder that with curiosity and dedication, anyone can bridge the gap and thrive in the age of AI.

 

Let us not allow history to repeat itself with the table game. Let's embrace the discomfort of learning something new, even if others seem to be far ahead. The sooner we get to grips with AI, the more likely we are to use it responsibly, creatively, and inclusively. Because this time it's about intelligence. And we can't afford to sit it out.

The AI Revolution: What Happens When We're Not the Smartest Anymore?

 By Richard Sebaggala

Not long ago, historian and bestselling author Yuval Noah Harari, known for his insightful books on the history and future of humanity, made a simple but unsettling comparison. He reminded us that chimpanzees are stronger than humans, yet we rule the planet—not because of strength but because of intelligence. That intelligence allowed us to organize, tell stories, cooperate in large groups, and build civilizations. Now, for the first time since we became the dominant species, something else has emerged with the potential to outmatch us—not physically, but cognitively.

Artificial Intelligence is not just another technology like the internet or the printing press. It is not simply an upgrade to how we compute, search, or automate. It is something more fundamental—a new kind of intelligence that doesn’t think like us, doesn’t learn like us, and doesn’t need to share our goals to reshape the world we live in. This isn’t merely about faster tools. It’s about a shift in cognitive authority, where machines are beginning to generate content, solve problems, and offer decisions that many humans now accept as credible—often without question.

In a previous article, I argued that AI is forcing us to rethink what intelligence really means. We are used to associating intelligence with human traits—consciousness, memory, creativity, even ethical reasoning. But AI doesn’t need any of these to function impressively. It uses statistical patterns and probability, not lived experience. It doesn’t need to “understand” to produce results that look meaningful. This has introduced a quiet but deep disruption: intelligence is no longer something uniquely human.

This realization calls for a different kind of response. We need to stop asking whether AI will “replace” humans and start asking how we, as humans, can live meaningfully and ethically in a world where we may no longer be the only—or even the dominant—form of intelligence.

 

To do that, we’ll need to rethink our policies. AI isn’t just another app to regulate; it’s a system capable of influencing elections, research, shaping public opinion, managing hospitals, and delivering education. We need strong, clear rules about what AI is allowed to do, and under what conditions. These rules must go beyond technical fixes and deal with deeper questions about accountability, fairness, and the role of humans in decision-making.

 

We also need to rethink education. If AI can access all the world’s information and summarize it instantly, what becomes the role of the classroom? What becomes the value of memorizing facts or writing essays? In this new world, human education must shift toward what AI still lacks: ethical thinking, emotional intelligence, creativity, empathy, and the ability to live with ambiguity.

 

Economically, things are shifting too. In the past, knowledge work—thinking, writing, analyzing—was a scarce and valuable resource. But now, the cost of generating “thinking” is falling. AI can produce text, summaries, even insights, at scale. This creates an economic twist. As thinking becomes abundant, what becomes rare is discernment—the ability to judge what matters, what’s true, and what’s worth acting on. Human judgment, not information, may be the next frontier of value.

 

But perhaps the biggest adjustment we need is psychological. For generations, we’ve grown up believing that humans are the smartest species on the planet. That belief shaped everything—from how we designed schools and workplaces to how we structured religion, law, and government. Now, as we encounter a form of intelligence that doesn’t look like us but can outperform us in many ways, we need to make space in our worldview for another mind. That takes humility, but also imagination.

 

We must remember that intelligence doesn’t have to be a “zero-sum” game. In economics, a zero-sum situation is one where if someone gains, another must lose. But intelligence can grow without taking away from others. AI getting smarter doesn’t mean humans are getting dumber. In fact, if we use it wisely, AI can help us become more reflective, more creative, and more human. But only if we remain active participants—questioning, interpreting, and shaping its use, rather than passively consuming its outputs.

 

What happens next is not inevitable. It depends on the choices we make—politically, socially, and personally. We don’t need to compete with machines, but we do need to learn how to live with them. That means adapting, not surrendering. Guiding, not resisting. Coexisting, not collapsing.

 

If we manage to do that—if we protect what makes us uniquely human while embracing what machines can offer—we might discover that the rise of another kind of mind is not the end of human relevance. It could be the beginning of a deeper kind of human flourishing.