A few months ago, one of my team leads submitted a first draft of a client strategy document in under two hours. It was polished, well-structured and covered all the expected ground. It was also, on closer reading, almost entirely generic.
The AI had done its job. The thinking had not.
That moment sits with me, because it captures something the industry is not yet being honest enough about. Artificial intelligence has not simply made us more efficient. It has changed what efficiency means… and in doing so, it has created a new and under-appreciated risk: that we begin to mistake fluency for insight.
The productivity numbers are real. Research from MIT and Harvard Business School consistently shows that AI-assisted knowledge workers complete tasks 20% to 35% faster, often with measurable quality improvements.
Across the communications and marketing industry, output volumes have surged. Agencies that once needed teams to produce a content campaign can now do it with a fraction of the headcount. Clients are asking for more, faster, and at lower cost. The market is obliging.
Output inflation
However, here is the argument I want to make and I accept it may be unpopular in some boardrooms: the productivity gains from AI are real, but they are also creating a form of output inflation that we are not yet equipped to manage.
Output inflation works like this. As the cost of producing work drops, so does its perceived value. When content is abundant and cheap to generate, differentiation becomes harder. The premium shifts away from production capability and towards something far more difficult to automate: judgement, interpretation and the ability to navigate genuine complexity.
Yet the commercial pressure is moving in exactly the opposite direction. More deliverables. Faster turnaround. Shorter thinking cycles.
This is not a technology problem. It is a leadership problem.
Layer of complexity
Organisations embedding AI into their workflows are making implicit choices about what they value. If the metric is speed and volume, then depth and originality will be quietly deprioritised. Nobody announces this. It simply happens, gradually, as the incentive structure shifts.
Over time, it hollows out the very capability that justified the premium in the first place.
In South Africa, this dynamic carries an additional layer of complexity. AI adoption is uneven, not just across industries but within them. Some organisations are accelerating rapidly, deploying tools across research, content, and client service.
Others are still building foundational digital infrastructure. The result is a dual pressure: to catch up quickly, often without the governance frameworks or strategic clarity needed to do so responsibly.
Work difficult to defend
The risk of moving fast without that clarity is not only reputational, it is also structural. An organisation that uses AI to replace thinking, rather than to enhance it, is not becoming more competitive. It is becoming more fragile, dependent on tools it does not fully understand, producing work that is difficult to defend when it matters.
For the communications industry specifically, this should prompt some uncomfortable self-examination. Our value proposition has never been rooted in volume. It lies in the capacity to read a situation accurately, to shape a narrative under pressure, to exercise judgement when the facts are contested and the stakes are high.
These are not capabilities that can be automated. But they can be eroded through neglect, through underinvestment and through the slow substitution of speed for thought.
The organisations that will succeed in this next phase are not those that use AI most aggressively. They are those that are most deliberate about where it stops.
Protect time for thinking
That means protecting time for thinking, even when technology makes it possible to move faster. It means being explicit about where human judgement is non-negotiable and building that distinction into how work is structured, priced, and evaluated.
It means resisting the temptation to let a client brief become a prompt, and then mistake the output for a strategy.
AI has made work faster. Whether it makes work better depends entirely on the choices that sit around it: the questions we ask before we run the tool, the standards we apply when we review the output and the intellectual honesty to know the difference between something that looks good and something that is good.
Speed is not the test. Judgement is.
Bradly Howland is the CEO of Alkemi Collective and President of the Public Relations Institute of Southern Africa (PRISA).
