As the year draws to a close, I have found myself having the same conversation repeatedly. Clients, partners, teams and even peers in the technology space keep asking some version of the same question: now that AI is here, what happens next? Closely followed by, are you guys safe? Are developers still relevant?
For the greater part of the last quarter, even within our own business, we have been quietly interrogating what this AI moment actually means. Not from a place of fear, but from responsibility. When you lead in technology, people look to you not just for tools, but for direction.
Over the decades, different technologies have impacted different classes of people in very different ways. The fears, however, have remained largely consistent: deskilling, demotions, job insecurity, displacement. From mechanisation to computers to the internet, history shows a familiar pattern, anxiety first, adaptation later, opportunity eventually.
For the first time though, we are confronted with a technology that feels figuratively “out of hand.”
Artificial Intelligence, particularly Large Language Models, generative AI systems and what is now casually referred to as vibe coding, is moving at a pace that even seasoned IT professionals are struggling to match. Unlike previous waves of automation that primarily threatened manual or repetitive work, this one cuts directly into what was once considered an insulated sector, IT and software engineering itself.
For decades, engineers built the tools that disrupted others. Today, we are watching tools that increasingly build themselves.
A Familiar Pattern, Repeating Itself
Yet history offers perspective.
Every foundational technology not only disrupted industries but also gave birth to some of the world’s best-performing companies. The internet enabled Google, whose model revolved around organising and monetising information at scale. Social connectivity enabled Facebook to monetise human relationships. Digital maps and GPS unlocked Uber, optimising idle assets and changing how we move. Online platforms and trust systems enabled Airbnb, turning spare rooms into a global hospitality network. Cloud computing reshaped entertainment through companies like Netflix, while smartphones and app ecosystems created communication giants like WhatsApp.
In every case, the technology was not the business, it was the enabler. The winners understood human behaviour, inefficiencies and unmet needs, then reimagined them through technology.
AI as Internet 3.0
AI feels like the natural continuation of a long arc. We moved from connected devices through IoT, generating oceans of data. Big Data emerged to store and process it. Machine Learning followed, helping us find patterns. Blockchain briefly promised trust and decentralisation. Now AI sits on top of all of this, learning, synthesising and acting,Godknows what will come next?
Where the internet gave us access to information, AI gives us access to outcomes. It collapses searching, reading, comparing and deciding into a single interaction. It removes friction rather than merely speeding it up.
In that sense, AI is an optimiser, compressing analysis, decision-making and execution into tighter, more reliable cycles.
Why Human Intelligence Still Matters
Despite the anxiety, one truth remains. Human intelligence will always be superior where context, experience, judgment and meaning matter.
AI does not feel. It does not care. It does not truly understand lived experience. Humans connect ideas across emotion, intuition and ethics. We build trust. We imagine futures. We decide what should be built, not just what can be built.
AI can generate answers. Humans still define the questions worth asking.
Harnessing the Opportunity
From a leadership perspective, the real opportunity lies in understanding AI’s most powerful feature, its ability to learn.
This is what will truly reshape industries. Systems that continuously learn from behaviour, environment and feedback will outperform static products every time. The winners will not be “AI companies,” but businesses that embed AI to optimise decisions and deliver outcomes faster through continuous learning. This spans fintech, where credit, risk and inclusion improve with every transaction; agtech, where productivity and resilience improve with every season, every field and every satellite signal; edutech, where learning adapts to each individual; and healthcare, where systems grow smarter with every diagnosis. In all cases, AI is not the product, it is the learning engine beneath it.
Just as Uber was not a maps company and Airbnb was not a real estate company, the most valuable AI-driven businesses will be problem-first, human-centred, AI-powered.
In comes adaptation
Every generation believes its disruption is unprecedented. History suggests otherwise. Tools evolve, fundamentals remain.
AI is not the end of human relevance. It is the end of unnecessary friction.
Strive Masiyiwa – ” The next wave of Billionaires in Africa won’t be the Masiyiwas and the Dangote’s of this continent, but young people who understand and act decisively on the AI opportunity.(Paraphased – not exact words)
Like every technological leap before it, it will create fear first, opportunity next and eventually some of the most valuable companies the world has ever seen.
The question is no longer whether this will happen.
It is who will learn fast enough to harness it.
