OFENTSE RAPAKGADI

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Artificial intelligence has moved from being an emerging technology to becoming an everyday workplace reality. Across industries, organisations are integrating AI into their operations to improve productivity, accelerate decision-making and remain competitive.

Governments are developing policy frameworks to guide its responsible use, while universities continue to debate its implications for teaching and assessment. The conversation has been both necessary and overdue.

Most of this conversation, however, has focused on the technology itself. We ask whether AI will replace jobs, increase productivity or reshape entire industries.

These are important questions, but they are not the only ones worth asking. There is another question that, in my view, deserves greater attention: what happens when the widespread adoption of AI begins to change not only how we work, but how we develop the human capabilities that work has traditionally required?

This question feels particularly relevant in South Africa. We continue to face significant challenges in education, youth unemployment and skills development, while employers consistently identify analytical thinking, creativity and problem-solving as some of the capabilities most needed in the modern workplace.

At the same time, Microsoft’s 2024 Work Trend Index found that approximately three-quarters of knowledge workers are already using generative AI in their work. AI is no longer a technology we are preparing for. It is already shaping how people write, analyse information, solve problems and make decisions.

The question, therefore, is no longer whether professionals should use AI. That debate has largely been settled. The more important question is whether we are being sufficiently intentional about the capabilities we continue to develop ourselves.

I ask this question as someone who uses AI every day. As an entrepreneur and marketing executive, I depend on it to accelerate research, interrogate ideas, improve efficiency and eliminate repetitive work.

The productivity gains are real. My concern is not that AI is making people less intelligent. Rather, it is that we may gradually begin to outsource aspects of thinking that have traditionally been central to developing our expertise. That concern did not emerge from theory. It emerged from practice.

Recently, while preparing an important piece of writing, I instinctively opened ChatGPT before opening a blank document. Within minutes, I had a well-structured draft that significantly reduced the time I would ordinarily have spent writing. I published the piece and moved on with the rest of my workday. What stayed with me afterwards was not the quality of the technology, but my own reaction to it. I realised that I no longer felt I had permission to give an idea the depth of thought it required.

My concern is not that work is being completed quickly. It is that speed may gradually become more valuable than depth, even when the quality of the outcome depends on sustained thought.

For many professionals, efficiency has become synonymous with excellence. Time spent examining an argument, testing assumptions, rewriting or allowing an idea to develop can begin to feel difficult to justify because technology now offers a faster route to a finished product.

My concern is not that work is being completed quickly. It is that speed may gradually become more valuable than depth, even when the quality of the outcome depends on sustained thought.

Writing has always been one of the ways I clarify my thinking. I often begin with one opinion and end with another because the act of writing forces me to interrogate my assumptions, discard weak arguments and refine stronger ones. That intellectual work does not always happen quickly, nor should it. Some ideas require sustained attention before they become sound judgment.

This is why I believe the conversation about AI should extend beyond productivity. The issue is not whether AI can produce impressive outputs. It clearly can. The issue is whether we inadvertently begin to devalue the processes through which expertise is developed simply because those processes are slower than the technologies now available to us.

Educational research offers an interesting perspective on this. Cognitive psychologists Robert and Elizabeth Bjork have demonstrated that learning is often strengthened by what they describe as “desirable difficulties”, the kinds of effort that require retrieval, reflection and problem-solving rather than passive consumption. In other words, the struggle involved in learning is not necessarily an obstacle to understanding. It is often the mechanism through which understanding is built.

This resonates with my own observations of young professionals entering the marketing industry. Many use AI exceptionally well. They test ideas against it, interrogate its recommendations and use it to improve their own reasoning. Others, however, appear to rely on it before they have developed the underlying judgment required to evaluate its outputs. The result is work that is polished and technically competent on the surface, but becomes difficult to defend when deeper questions are asked.

The challenge is not that AI has produced poor work. The challenge is that impressive outputs can create the illusion of expertise before expertise has actually been developed.

This distinction matters because professional capability has never been defined solely by outputs. It has always been defined by judgment. Judgment is what enables a professional to recognise nuance, evaluate evidence, challenge assumptions and explain why one course of action is preferable to another. These are capabilities that develop over time through practice, reflection and, occasionally, frustration. They are difficult to cultivate if every moment of intellectual friction is immediately removed.

History reminds us that every transformative technology changes human behaviour in ways that are not immediately obvious. Calculators changed how we perform arithmetic. GPS changed how we navigate. Search engines changed how we access and remember information. Few would argue that society should abandon any of these technologies because their benefits are undeniable.

Yet each has also reduced the need to practise particular human skills. Artificial intelligence differs only in that it reaches into activities we have traditionally regarded as central to human cognition itself: writing, analysing, synthesising and evaluating.

None of this suggests that AI should be resisted. On the contrary, its potential to improve productivity, expand access to knowledge and support better decision-making is extraordinary.

The question is whether we can embrace those benefits while remaining intentional about the capabilities we choose to preserve. Technology has always extended human potential. The responsibility has always rested with us to ensure that, in extending our capabilities, we do not gradually abandon the habits that created them.

Perhaps the defining question of the AI era is not whether machines are becoming more intelligent. It is whether we continue to invest in the slow, often uncomfortable work of becoming more capable ourselves.

If AI allows us to produce more in less time, we should certainly celebrate that achievement. We should also ask whether we are using some of the time it gives back to deepen our judgment, strengthen our thinking and continue learning, or whether we are simply filling it with more work.

The future of work will undoubtedly be shaped by artificial intelligence. The future of human capability, however, will still be shaped by the choices we make about how we use it.