AI Is Dead. Welcome to the Age of Super Intelligence. Are We Ready?

For most of the past decade, we have asked the same question about artificial intelligence: will it take our jobs? I have come to believe that is the wrong question. The better one is this: what happens to human value when intelligence itself becomes cheap, plentiful and available on demand?

That question took on new weight on September 29, 2026, when President Donald Trump signed an executive order directing the executive branch to use “Super Intelligence” and “SI” in place of “Artificial Intelligence” and “AI” in official non-statutory communications. It is worth being precise about what the order does. It does not turn today’s systems into scientifically established superintelligence. For now, it defines Super Intelligence using the existing federal statutory definition of AI, and it gives officials 60 days to propose a new one.

Still, names matter, because they reveal how we see the moment we are in. Whatever you think of the new terminology, it captures something real about the speed, ambition and uncertainty of this technology. We are no longer talking only about machines that answer questions. We are talking about systems that reason through complex problems, write software, analyze vast amounts of information and, through autonomous agents, carry out multi step tasks on our behalf.

After hosting two major conversations on the subject through AfroVibes TV & Radio, our AI Summit and, more recently, our AI & Real Estate event, I am convinced this discussion cannot stay inside Silicon Valley, universities, government agencies and tech conferences. It belongs in our businesses, our schools and our creative industries. It belongs in Africa and across the developing world. And it belongs at ordinary dinner tables, because what is happening will eventually touch almost everyone.

What our AI events taught me

We organized the AI Summit to give people a place to move past the headlines and talk seriously about what AI means for business, entrepreneurship and society. AI & Real Estate continued that conversation, bringing professionals and thought leaders together to look at one of the world’s largest and most human-centered industries.

Real estate is a good illustration of what is changing. Buying, selling, leasing and managing property have long depended on personal relationships and on a great deal of repetitive administrative work. Intelligent agents are now beginning to take on parts of that work, from leasing and maintenance coordination to investment analysis and tenant communication. McKinsey describes agentic AI as a shift from systems that help people understand something to systems that help them get things done. Its analysis of real estate, construction and development estimates that automation, including AI applied to knowledge work, could unlock hundreds of billions of dollars in value each year.

But as I listened to those conversations, I found myself thinking past productivity. If machines can increasingly do the intellectual work that once required people, where will people create value? That question has stayed with me.

From tools to digital workers

The early internet gave us access to information. Search engines helped us find it, social media helped us spread it, and generative AI began to create it. The next stage is about acting on it, and that is a meaningful difference.

Consider an entrepreneur who once needed ten employees to research markets, answer routine inquiries, prepare marketing materials, study customer behavior, schedule appointments and handle administration. Many of those functions can now be supported, or performed outright, by intelligent systems. McKinsey describes an emerging hybrid workforce in which people and agents work side by side. Sometimes the agent assists a person; sometimes several agents do the work while people oversee decisions, exceptions and outcomes.

This changes the economics of starting a business. A small company may soon have operational capabilities that once required a much larger organization. A young founder in Lagos, Houston, London, Johannesburg or Accra could build a global business with a laptop, an internet connection, creativity and a team of digital agents.

That possibility excites me. It should also challenge us, because every technological revolution produces winners and losers. Technology doesn’t choose them deliberately. The winners are often simply the people who understood the transition first.

The jobs question is really a skills question

Fear makes good headlines, but the reality is more complicated. The International Labour Organization’s 2026 review of the evidence found genuine, if uneven, productivity gains from generative AI, while large-scale job displacement has so far been limited. That does not make disruption imaginary. The ILO also flags real concerns about inequality, fewer opportunities for young workers, and changes to worker autonomy and job quality.

So perhaps the real contest is not human versus machine, but people who work with intelligent systems versus people who don’t. An accountant who uses advanced tools well may outperform one who refuses them. A real estate professional who understands automation may manage a much larger portfolio. A journalist may research faster with AI but will still need judgment, credibility and accountability. A physician may gain better diagnostic support while remaining responsible for the patient. And an entrepreneur who knows how to orchestrate these systems may compete with companies many times larger.

That turns the jobs question into a skills question. What should we teach our children? What should universities teach? What should companies train their employees to do? And what should a 45-year-old professional learn today to stay valuable at 55? Those conversations need to start now.

For media, the problem is trust

As someone who runs a television and radio organization, I think constantly about another consequence. AI does not just change how content is made; it changes the economics of reality. Convincing photographs, videos, voices, advertisements, presenters and even entire personalities can now be generated without the production infrastructure they once required, and the cost keeps falling.

That creates a paradox for media companies: as content becomes cheaper, trust becomes more expensive. In a world flooded with synthetic material, audiences will care more about who is speaking, why they should be believed and whether a real institution stands behind the information.

For AfroVibes, that means our future cannot be about producing more content. It has to be about deeper credibility and stronger community. Technology can generate a voice. It cannot generate trust.

What fashion teaches us

Founding VELIOR Fashion Group has given me another vantage point. AI is already reshaping fashion. Designs can be generated digitally, campaigns built faster, virtual models created and trends analyzed. Images that once needed photographers, models, stylists and elaborate locations can now be synthesized. Those capabilities are remarkable.

Yet stand inside a real fashion show and something else happens. You hear the audience react. You watch a designer see a collection come to life as a model steps onto the runway. Music, movement, nerves, confidence and anticipation all fill the same room. There are imperfection and unpredictability; in other words, there is humanity.

This contributes to what may become one of the great economic paradoxes of the intelligence age: the more artificial our world becomes, the more valuable authentic human experience is likely to be. When anyone can produce a beautiful image in seconds, beauty alone is no longer scarce, and the story behind it becomes what matters. When anyone can generate music, human connection gains value. When anyone can create digital fashion, physical experience does.

Rather than destroying creativity, AI may force us to rediscover what creativity actually is. That shift could reshape entertainment, fashion, hospitality, sports, media and the creator economy.

Africa cannot be a spectator this time

One dimension of this conversation deserves far more attention than it gets. Too many technological revolutions have reached Africa after the infrastructure, intellectual property, platforms and economic value were already controlled elsewhere. That cannot happen again.

This week at the United Nations, representatives of developing nations pressed for a greater voice in global AI governance, warning that the technology could deepen inequality if its development and regulation stay concentrated in wealthy countries. The concern is legitimate. The World Bank notes that high-income countries dominate AI innovation, computing infrastructure and startup funding, while many lower-income economies still face gaps in connectivity, computing capacity, locally relevant data and skills.

Africa faces a choice: consume intelligence built elsewhere, or take part in building, adapting, governing and owning it. The continent has more than 2,000 languages, yet the data used to train most internet-based AI systems is concentrated in a small number of them. If Africans do not participate meaningfully, who will make sure African languages, histories, cultures and business realities are properly represented?

This is not only a cultural question but an economic one. Data, computing power, electricity and education are all AI infrastructure now. Talent could become one of Africa’s most valuable exports, or one of its greatest missed opportunities.

The African Union has already named AI a strategic continental priority, calling for African-led research, homegrown solutions, stronger infrastructure, skills development and a larger African role in global AI governance. That direction now has to become investment and execution. Africa does not need to replicate every trillion-dollar race between the United States and China. But it does need entrepreneurs building AI businesses, universities developing AI talent, governments digitizing responsibly, companies deploying AI productively and investors funding African technology. Above all, it needs young Africans who see themselves as creators of the intelligence economy, not merely its customers.

The divide that worries me most

When people talk about AI and inequality, they often picture robots replacing workers. I worry about a different divide. It runs between people who know how to direct intelligent systems and those who don’t, and between businesses redesigned around intelligence and those operating as if nothing has changed. It runs between countries with the infrastructure to participate in and those left as consumers, between children educated to work alongside machines and children trained for jobs machines are taking over, and between communities that own intellectual property and those that merely rent access to it. That gap could become enormous.

This is why I don’t think fear is the right response to AI, though I reject blind optimism too. Technology is not destiny. What we choose to build with it will determine its legacy.

Super Intelligence still needs human wisdom

The timing of this debate is striking. In the same month the U.S. government adopted the language of Super Intelligence, technology executives and world leaders were debating AI’s risks at the United Nations. Some urged faster development; others warned that more capable systems demand stronger safeguards and international coordination. Those disagreements will continue.

But there may be a deeper principle we can all agree on greater intelligence does not automatically bring greater wisdom. History makes that plain. Intelligence tells us what we can do; wisdom asks whether we should. Intelligence can optimize an advertising campaign, automate a workforce, generate a human face, build a surveillance system or raise productivity. Wisdom asks whether the message is true, what happens to the workers, whether audiences should know that face belongs to no one, who controls the surveillance and how the gains are shared.

That is why I believe the central question of this revolution is not whether machines become more intelligent than people. It is whether people become wise enough to manage increasingly powerful intelligence.

We cannot sit this out

Our AI Summit and AI & Real Estate conversations left me with one firm conviction: none of us can watch this revolution from the sidelines. Business leaders need to experiment, and employees need to learn. Educators need to rethink curricula, and governments need to understand the technology they regulate. Media organizations must protect their credibility, while creators must defend authenticity and still embrace useful tools. Developing economies, in Africa and beyond, need infrastructure, investment, skills and ownership. Parents need to understand the world their children are entering, and entrepreneurs need to see the opportunity hidden inside this disruption.

Seventy years from now, historians may look back on this period the way we look back on the arrival of electricity, the automobile, television, the personal computer or the internet. They probably won’t remember which chatbot had the most users in 2026. They may remember it as the moment intelligence itself became infrastructure.

If that is where we are heading, our greatest task is not simply learning to use artificial intelligence, or Super Intelligence, as the U.S. executive branch now calls it. It is deciding what kind of society we want to build with it. Machines may become astonishingly capable, faster than us at work we once believed only humans could do, and they may transform industries in ways we cannot yet predict. But the future should never be handed over entirely to an algorithm. The technology may be artificial, and the intelligence may one day be super, but the responsibility for what we do with it remains profoundly human.

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About the author

Philip Balonwu is a computer scientist and entrepreneur. He is the Founder and CEO of AfroVibes TV & Radio and the Founder of VELIOR Fashion Group. Through media, technology, entrepreneurship, fashion and live experiences, his work focuses on building platforms that connect businesses, professionals, creators and communities across cultures.