University of Kwazulu-Natal

How Ai Is Completely Rewriting The Rules Medium

Bonisiwe Shabane
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how ai is completely rewriting the rules medium

When a CEO tells his team, "AI is coming for your jobs, even mine," you pay attention. It is rare to hear that level of blunt honesty from any leader, let alone the head of one of the world's largest freelance platforms. Yet this is exactly how Fiverr co-founder and CEO Micha Kaufman has chosen to guide his company through the most significant technological shift of our lifetimes. His blunt assessment: AI is coming for everyone's jobs, and the only response is to get faster, more curious, and fundamentally better at being human. Kaufman doesn't apologize for his directness. As someone who's built four companies over 25 years and took Fiverr public seven years ago, he's developed a communication style that prioritizes authenticity over comfort.

When asked why he chose such a stark message, Kaufman explained, "If you stand in the middle of the road and you see a car coming to run you over, it's probably better to... His perspective stems from a fundamental belief about leadership. "You should have radical transparency. You should just say things for what they are," Kaufman told me. He acknowledges uncertainty about the future, noting that while he's confident in his views about AI's trajectory, he's not presumptuous enough to claim certainty about exactly how things will unfold. The message resonated beyond Fiverr.

Months after Kaufman's internal memo, Sam Altman gave an interview making a similar point, suggesting that AI would eventually surpass even the best CEOs alive today. The convergence of these warnings from leaders building and using AI systems suggests we're facing a genuine inflection point. Kaufman frames our current moment with AI through a compelling historical analogy. "What's happening with AI right now is in many ways similar to what happened in 1769 with the steam engine," he explains. When compact steam engines first appeared, the obvious solution was to attach them to horse carriages. It made perfect sense at the time, but it wasn't revolutionary.

The true transformation came later with the actual automobile. When people talk about AI in media, the conversation usually revolves around deepfakes, automated content, or ChatGPT taking jobs. But what if I told you that the most important AI-driven shift in media isn’t happening on the surface—it’s happening behind the scenes, reshaping influence, credibility, and control in ways few people are paying... Subscribe to AI & Communications Lab to keep reading this post and get 7 days of free access to the full post archives. For those of you that have spent a little time with me lately, will know that I’ve become obsessed with AI. Frankly, I’m blown away by the way it has changed the way I work.

Part of my obsession is thinking thru the impact of AI not only on my work, but also on the way I will navigate the world. One of my learning adventures brought me to Russell Ackoff, a former Wharton School professor. He created a Knowledge Pyramid that identifies levels of understanding. Since, I have been fascinated by how much it explains our current predicament with AI. Created in 1988, Ackoff identified four levels of knowledge: Here's what’s interesting—what was revolutionary in 1988 is being completely transformed by AI in ways that even Ackoff couldn't have imagined.

I've spent 20+ years watching technology evolve, but nothing has shifted our perspective quite like this. We're not just climbing the same old knowledge pyramid faster—we're rebuilding it entirely. And if you're like me, you're probably wondering what this means for how we lead, decide, and innovate. The New Knowledge Pyramid: AI as the Great Accelerator Consider this: While Ackoff's 1988 hierarchy remains foundational, AI is dramatically compressing the journey from data to wisdom. Today's AI systems aren't just processing data—they're reshaping how we ascend the knowledge pyramid:

The world of creativity is in flux. For years, the creative process meant intuition, iteration, and those elusive 10,000 hours of mastery. Then came AI, an accelerant that shattered the barrier between idea and execution. But in this acceleration, something deeper is happening. AI is changing how we create, but it is also redefining who gets to create and what creativity even means. Across industries, a new generation of innovators is blending human instinct with algorithmic speed.

In conversations with leaders in the AI space, a pattern emerged: AI does not replace the creative process, it reframes it. The challenge now is learning to work with the machine without letting it dominate the rhythm. Robert Leeks, Creative Director at Imagination, has spent nearly two decades pushing the boundaries of experiential design. For him, the biggest shift AI has introduced is not about replacing artists but about collapsing time. “AI has broken down that barrier from mind to page,” Leeks explains. “If I’ve got an idea for a storyboard, I can get a very good result out very quickly.

That immediacy has never been available before.” At Imagination, AI is not used to originate ideas but to pressure-test them. Teams write first, then use AI to sharpen language or visualize scenes, allowing creative intent to stay human while execution accelerates. “We’re doing the thinking,” says Leeks. “AI augments our thinking with suggestions that we may or may not take on board.” Still, he acknowledges the danger of creative homogeneity, what he calls the “internet eating itself.” When everyone feeds from the same models, the output begins to blend.

True creativity, then, becomes about reclaiming the imperfections, the brushstrokes AI cannot replicate. Artificial Intelligence (AI) is no longer a distant concept confined to science fiction or elite tech labs. It has moved from the periphery to the very heart of the modern economy, reshaping how we work, make decisions, and create value. With the rise of machine learning, natural language processing, and generative AI, intelligent systems are not only performing repetitive tasks—they're drafting legal memos, diagnosing medical conditions, designing marketing strategies, and even writing code. This transformation is not happening in isolation. AI is what economists call a General Purpose Technology (GPT)—a class of innovations like electricity or the internet that alter entire industries and societies.

But unlike its historical predecessors, AI rides on a pre-existing digital infrastructure. The diffusion is faster. The implications, deeper. Tools like ChatGPT amassed over 100 million users in mere months, collapsing the usual adoption timeline and triggering an accelerated reckoning for businesses, governments, and workers alike. The pace of AI’s evolution is amplifying both opportunity and disruption. On one hand, it holds the promise of productivity booms, creative empowerment, and new forms of work.

On the other, it threatens to automate away familiar roles, exacerbate inequality, and challenge our systems of accountability. The future it ushers in is neither fully utopian nor wholly dystopian—it’s malleable, shaped by the choices we make now. AI’s impact on the workplace is unfolding along two powerful vectors: automation and augmentation. These forces are fundamentally redefining roles, responsibilities, and the very nature of work. While automation replaces human involvement in tasks, augmentation enhances it—creating a dynamic and, at times, paradoxical transformation of labor. At its core, automation is about transferring work from human to machine.

AI excels at processing vast amounts of data, following rules, and making decisions faster and more accurately than humans. As a result, roles involving routine cognitive work—think data entry, scheduling, document processing—are increasingly being absorbed by software. Finance and HR departments use robotic process automation to handle payroll, onboarding, and compliance tasks with minimal human input. Customer service has been transformed by AI chatbots that resolve basic queries 24/7. In manufacturing and logistics, robots pick, pack, and ship products with algorithm-optimized precision.

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