By Stantin Siebritz
The recent slowdown in artificial intelligence (AI) enthusiasm has sparked a wave of commentary suggesting the so-called “AI bubble” is bursting.
Will Lockett’s widely circulated piece, “The AI Bubble Is About To Burst, But The Next Bubble Is Already Growing,” captures this sentiment well.
He argues that AI, once heralded as a miracle technology, is now revealing its limitations – particularly in the workplace, where it has often added complexity rather than reducing it.
He also speculates that quantum computing may soon take AI’s place as the next speculative frontier.
There’s truth to this. The media frenzy has quieted. The flood of overnight “AI experts” has slowed to a trickle. And businesses are beginning to ask more grounded questions – not about AI’s potential, but about its actual value.
This is not a collapse; it’s a correction. It mirrors the trajectory of every major tech wave since the 1980s – from the internet to mobile apps to blockchain.
As I’ve previously written, this is the natural progression of the hype cycle: from inflated expectations to disillusionment, and eventually, to enlightenment.
Where I diverge from Lockett is in the interpretation of this shift. AI was never meant to be a standalone business model. It is a force multiplier – a tool to enhance human creativity, decision-making, and operational efficiency.
Critics who claim AI has increased workloads without improving productivity miss a key point: if more is being produced in the same amount of time, that is productivity.
The real issue lies in how organizations manage the time and capacity AI frees up. Do they reinvest it in innovation, or squander it on low-value tasks?
This moment is not the end of AI – it’s the beginning of its most meaningful phase. As the hype fades, we are entering what Gartner calls the “Slope of Enlightenment,” where experimentation gives way to integration, and value becomes measurable. This is where the real transformation happens.
As for quantum computing, while its potential is immense, it remains decades away from practical application.
Betting on it now means diverting attention from the powerful, evolving AI infrastructure already in place. The next wave of computing power will come not from quantum leaps, but from smarter algorithms, more efficient hardware, and better data practices – breakthroughs like DeepSeek are already showing the way.
A Namibian (and African) Imperative
For Namibia – and Africa more broadly – the AI opportunity is not about chasing the next tech bubble. It’s about closing the industrial gap.
AI can flatten learning curves in critical sectors like healthcare, agriculture, mining, logistics, education, and public administration.
It can help triage clinic backlogs, automate routine filings, translate regulations, and surface market insights for SMEs – at a fraction of the cost and time.
The hype may be fading, but the real work is just beginning. This is our moment to act. We must invest in local talent and curricula, establish procurement and safety standards, build responsible data ecosystems, and create incentives that move AI from pilot projects to production-scale solutions.
Namibia doesn’t need to follow the global narrative. We can write our own – one that turns a cooling tech trend into a generational advantage. Less sizzle, more steak. And that’s a story worth telling.
* Stantin Siebritz is Managing Director of New Creation Solutions, and a Namibian Artificial Intelligence Specialist
