Somewhere, surely, there must be an AI playbook. You know, a neat little manual telling executives when to trust the machine, overrule it, redesign jobs and reassure staff that an algorithm isn’t their new boss. But no such manual exists. People must make up the rules as they go along.
AI ranges from long-established machine learning and marketing algorithms to newer large language models such as ChatGPT and Claude that have made the current debate feel so urgent. These newer tools, as Milpark Business School’s Bernard Odendaal points out, are still in their infancy and are forcing companies and business schools to make sense of them in real time.
That means executive education is becoming less about handing leaders a finished framework and more about teaching them how to think and stay accountable while the framework is being built. Milpark director Frikkie Herbst says: “We’re building the aircraft while we’re in the air.”
Jon Foster-Pedley, dean and director of Henley Business School Africa, says: “Every generation of leaders meets a moment when the future turns up before the rulebook. AI is one of those moments. Nobody has a finished, proven blueprint for bringing human and machine intelligence together inside organisations. Anyone who says they do is usually selling something.”
Stanford University’s 2025 AI index reports that global corporate AI investment reached $252.3bn in 2024, while private investment in generative AI alone rose to $33.9bn. It also found that the proportion of organisations using AI jumped to 78% in 2024 from 55% the year before. McKinsey’s latest global AI survey shows 88% of respondents saying their organisations are using AI in at least one business function, up from 78% a year earlier.
Yet in many companies, AI is closer to a productivity tool than a redesigned operating model. It drafts e-mails, summarises documents and speeds up routine analysis. Useful, certainly, but not yet revolutionary.
The question is not whether executives can use AI but whether they can build organisations in which AI amplifies human capability rather than weakens it.
Regent Business School MD Ahmed Shaikh argues that business schools are in the space between enduring leadership principles and unprecedented change. The fundamentals have not become obsolete because AI has arrived. “If anything,” he says, “they may have become more important.”
But he says business schools should be humble about how much they know. “The reality is that many of us, business schools included, are learning in real time.” Regent’s role is not necessarily to provide all the answers, but to offer “a credible intellectual framework within which better questions can be asked”.
This is a useful way to understand the emerging pedagogy of AI leadership. Business schools are not simply adding ChatGPT workshops to executive programmes. They are being forced to revisit the assumptions beneath management itself: what counts as knowledge, how evidence is validated, where accountability sits and what leaders should never delegate.
The question is not whether executives can use AI but whether they can build organisations in which AI amplifies human capability rather than weakens it
For Regenesys Business School co-founder and director Penny Law, the answer lies in what the school calls conscious leadership. As AI becomes more capable, leaders need to become “more aware, not less”. The task is not simply to adopt smarter tools, but to understand the impact of decisions on people, organisations and society, while ensuring that technology remains aligned with human values and purpose.
That requires executives to become more deliberate about where AI belongs in the decision-making chain. Law says leaders are being guided to distinguish between decisions that should remain human-led, those that can be AI-assisted, and workflows where they can complement each other. “AI can process information and identify patterns at speed,” she says, “but it does not remove the need for human judgment, accountability and ethical oversight.”
The risk, in her view, is that leaders become dazzled by the ease with which AI can generate answers. That makes the human work of leadership more important, not less. “The leader’s value lies in asking better questions, managing ambiguity and ensuring that decisions remain grounded in organisational values,” Law says. “In a world where AI can generate answers instantly, conscious leadership becomes the capability that ensures those answers are used responsibly.”
Wits Business School (WBS) executive education director Leoni Grobler says no single formalised, proven framework for human-AI integration exists because the landscape is shifting too rapidly. WBS positions the classroom as “a real-time co-creation laboratory”, where executives and educators collaboratively develop adaptive strategies as new capabilities emerge.
The school’s approach, she says, is designed to teach leaders to ask critical questions, challenge assumptions and build cultures of responsible, AI-enabled decision-making rather than apply a static framework.
The emphasis on responsibility is not incidental. The most sophisticated AI systems can produce polished, plausible and often useful outputs. They can analyse data, draft strategy, generate options and simulate scenarios.
What they don’t do is carry the consequences of their output. “When should machine-generated insight be trusted? Where does data end and judgment begin?” asks Shaikh. “Most importantly, who remains accountable when decisions are shaped by increasingly interconnected human and machine systems?”
That question may define the next era of leadership. For more than a century, management has largely meant co-ordinating people, resources and processes. Foster-Pedley says leadership will increasingly mean co-ordinating “intelligence itself, some of it human and some of it not”. The trap, however, is to confuse access to AI with mastery of it.
“It is rather like owning the most advanced phone ever built and using it only to make calls,” Foster-Pedley says. Used well, AI can draft, analyse, argue back and “open doors you did not know were there”. Used badly, it can make people lazy. “That is the real choice in front of every leader and every team,” he says. “Not whether to adopt AI, but whether to let it do our thinking for us or use it to make us think harder.”
AI cannot determine what is worth valuing. It cannot decide what kind of society we wish to build, what trade-offs are acceptable, what responsibilities we owe one another, or what constitutes meaningful progress
— Ahmed Shaikh, Regent Business School
The “aerodynamics of leadership” have not changed, even if the tools have. Odendaal resists the idea that executives should stop thinking of themselves as managers of people and become only “orchestrators of parallel intelligence”. People still matter.
A field experiment by Harvard Business School and Boston Consulting Group involving 758 consultants found that on tasks within AI’s capability, consultants using GPT-4 completed 12.2% more tasks, worked 25.1% faster and produced significantly higher-quality work. But on a task outside the AI’s frontier, those using AI were 19 percentage points less likely to produce correct solutions than those without it.
Odendaal says this points to “verification discipline”: knowing which tasks can safely be delegated, building the habit of checking, resisting automation bias and applying critical reasoning to machine outputs.
This makes accountability one of the scarce skills of the AI age. “What we can teach students is something narrower and harder,” Odendaal says. “That is, how to own a decision when you cannot fully justify the data and to remain answerable for that afterwards.”
The question is no longer simply whether a student can create a plausible analysis, he says, but whether they can own and defend the judgment behind it. That cuts to the heart of hybrid leadership. The goal is not to make executives more machine-like. It is to make them more discerning about where machines belong.
Regenesys COO Indherani Reddy says an advantage of AI is its ability to “spit out data, replicate repetitive tasks and do very quick, informed analysis”. It allows leaders to escape “analysis paralysis” and use the time saved for more important tasks.
However, Foster-Pedley cautions: “Efficiency is seductive. It gives you measurable results, quick wins and a dashboard that looks reassuring. But efficiency only ever helps you do today’s business better. It does not help you find tomorrow’s.”
The World Economic Forum’s Future of Jobs Report 2025 found that employers expect 39% of workers’ key skills to change by 2030. It also found that 86% of employers expect AI and information-processing technologies to transform their businesses by then. If AI does more of the analytical heavy lifting, people may lose not only tasks. They may also lose parts of the work that gave them confidence and identity.
Odendaal warns that automating the interesting parts of a job can hurt morale far more than automating the boring parts. “People take meaning from the work that needs their judgment,” he says. “That’s the type of work AI is now encroaching on.”
He says leaders must be honest about redesigned roles, headcount implications and the hard parts of change. They also need to rebuild jobs around what people still bring that AI does not.
Grobler says executives must be trained to foster psychological safety and purpose by reminding teams why their work matters, celebrating human capabilities such as creativity and empathy, and creating safe spaces to speak up. The WBS curriculum, she says, stresses that human oversight is non-negotiable and that AI must be anchored in governance, ethics and strategy.
Machines can generate recommendations. They cannot assume responsibility for their consequences. “That remains a deeply human obligation,” Shaikh says. “AI cannot determine what is worth valuing. It cannot decide what kind of society we wish to build, what trade-offs are acceptable, what responsibilities we owe one another, or what constitutes meaningful progress.”
So, what should be automated? What should be augmented? What must remain human, even if a machine can imitate it?
Cobus Oosthuizen, chair of the South African Business Schools Association and dean of postgraduate studies at Boston City Campus, asks: “How do we ensure that AI strengthens our judgment rather than replaces it, or hide accountability behind a screen?
“AI might help leaders see things they would otherwise miss but it can never replace moral responsibility. It doesn’t understand dignity or consequence or lived experience in the South African workplace. You still need to ask if this decision is fair or lawful or human.”
Reddy, however, says leaders who understand AI will make it sustainable. “These are the people who use it ethically and responsibly,” she says. “AI is not just a partner to technology. It also helps us to tackle human challenges.”
There is no defining recipe yet. But the emerging consensus from business schools is that the leaders who thrive will not be those who merely use AI aggressively. They will be those who ask better questions of it, build stronger governance around it, and use it to expand rather than diminish human capability.
“The more capable AI becomes, the more it is worth being human,” says Foster-Pedley. Machines can process faster, see patterns humans miss and generate options at astonishing speed. “What they cannot do is care. They cannot be accountable. They cannot find moral courage when it costs something, and they cannot decide what kind of future is worth having.”
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