The “boring” part of AI training is the part that keeps you out of trouble

Leaders want the demos, but the real value starts with responsible AI, privacy, bias, and what the tech can’t do.

Article link: https://open.substack.com/pub/johanosteyn/p/the-boring-part-of-ai-training-is?r=73gqa&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

Video: https://youtu.be/KD9eUf2ZRZA

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I recently recorded a short video about something I’m seeing repeatedly in boardrooms and management teams: leaders are being asked to “adopt AI” before they truly understand what they are adopting. AI training is often treated like optional upskilling, or worse, like tool onboarding. But the moment you allow AI into decision-making, customer interactions, HR processes, classrooms, or compliance workflows, you’ve moved into governance territory.

This is not about becoming a data scientist. It is about building enough literacy to ask better questions, spot risk early, and set rules that protect people. And because children’s data and learning journeys are increasingly digitised, the consequences of weak AI literacy will land on the next generation long after today’s projects are forgotten.

CONTEXT AND BACKGROUND

The most common mistake I see is confusing capability with readiness. Organisations buy licences, run a few demos, and then assume value will follow. That mindset is starting to collide with a fast-changing policy environment. Reuters reported in late 2025 on the EU’s discussions to simplify and potentially delay parts of its digital rulebook, including aspects linked to AI governance, while still signalling that stricter expectations are coming. Whether deadlines shift or not, the direction is clear: regulators expect organisations to know what their systems do, how they behave, and what harms are foreseeable.

At the same time, the “people side” of AI is becoming unavoidable. ITWeb has highlighted how South Africa’s AI ambitions are inseparable from the hard work of implementation: building skills, improving infrastructure, and putting responsible governance into practice, not just making bold statements. In other words, training is not a box to tick. It is the foundation of execution.

INSIGHT AND ANALYSIS

AI training for leaders should start with an honest premise: you do not need to be technical, but you do need to be accountable. If your team uses AI to draft reports, summarise meetings, screen CVs, recommend interventions, or personalise learning, you are now responsible for the outcomes, including errors, bias, confidentiality breaches, and over-reliance. ChannelPro recently reported on how a wave of AI programmes are being pitched to businesses, yet many organisations still struggle to separate marketing language from operational reality. That gap is exactly where bad decisions thrive.

There’s another uncomfortable truth: many leaders are overly confident about what they know. Lifewire has highlighted a widening “training gap” in workplace AI: people are adopting tools like chatbots and copilots quickly, but far fewer organisations are providing structured guidance on safe use, verification, privacy, and policy.

The result is predictable: inconsistent judgement, over-trust in outputs, and avoidable risks that show up in real workflows, not in demo rooms. Overconfidence is not a personal flaw; it is a predictable human response to a fast-moving topic. But in a corporate setting, it becomes a risk multiplier.

Responsible AI also cannot be taught as a slide deck at the end of a course. It has to be baked into how leaders think: data minimisation, consent, fairness, security, auditability, and clear human responsibility. And when organisations say, “We’ll handle safety later,” it’s worth remembering that the AI industry itself is built on hidden human labour and trade-offs that many users never see. The Guardian’s reporting on the human workforce behind AI training is a reminder that these systems are not magic; they are socio-technical systems with real-world costs and blind spots.

IMPLICATIONS

For business leaders, AI training should be treated like financial literacy or basic risk management. You don’t outsource responsibility for budgets simply because you have accountants. In the same way, you can’t outsource judgement about AI simply because you have IT. A good leadership-level AI programme should cover: what AI is and is not, how it fails, where data flows, what “good governance” looks like, and how to write practical rules for teams.

For boards and executives, the question is not “Do we have an AI policy?” It is “Can our leaders explain how AI is used in our organisation, what could go wrong, and what controls exist?” If the answer is vague, your risk is already operational.

For parents and educators, the spillover matters. As schools adopt more digital tools, and as children engage with AI-driven platforms at home, adults need enough literacy to ask the right questions: What data is collected? What is stored? What is inferred? What is the escalation path when something feels wrong? Protecting children in an AI-rich world starts with adults who understand the basics well enough to set boundaries confidently.

CLOSING TAKEAWAY

AI is no longer a specialist topic parked in the IT department. It is becoming a general leadership competency. The organisations that will thrive are not the ones that chase every new tool, but the ones that train decision-makers to think clearly about capability, risk, responsibility, and impact. In South Africa, where inequality and opportunity are so tightly linked to education and skills, we cannot afford careless adoption dressed up as innovation. AI training done properly is not hype management. It is a duty of care to employees, customers, and especially to the children who will inherit the consequences of today’s shortcuts.

Author Bio: Johan Steyn is a prominent AI thought leader, speaker, and author with a deep understanding of artificial intelligence’s impact on business and society. He is passionate about ethical AI development and its role in shaping a better future. Find out more about Johan’s work at https://www.aiforbusiness.net