On artificial intelligence—not as novelty, but as the old failures of leadership and judgement conducted at unprecedented speed and expense.
38 essays
Part I of a IV part series: for nine years surveys have produced a remarkably similar finding: a small minority of organisations capture real financial value from AI; the great majority spend, signal, and pilot.
March’s essays converge on a simple truth: leadership is less about solving problems than managing enduring tensions. From strategy to governance, the task is not to choose sides, but to exercise judgement—resisting the drift toward process, theatre, and easy answers.
A quiet change has taken place in executive life, and it is not "AI" as such. It is the arrival of smoothness as a default condition. Language is
A practical method for how to turn AI into a thinking partner—surfacing assumptions, testing arguments, and strengthening decisions through disciplined cognitive friction.
AI makes language effortless—but thinking is done best when it is effortful. Thus, beware the “chat trap”: how casual use of generative AI can quietly soften judgement by replacing framing, definition, and trade-offs with fluent prose.
In an age of cheap text and AI-generated plausibility, leaders are not misled by too little information but by too much of the wrong kind. In this piece I explore why attention has become a governance risk—and why learning what to ignore now matters as much as what to know.
The em-dash has fallen under suspicion—treated as a tell-tale sign of artificial writing rather than what it has always been: a mark of care, rhythm, and thought in motion. It should return to good standing so we can recover linguistic standards we seem oddly eager to abandon.
A 2025 review of authority, trust, coherence and attention—plus a strategic outlook for 2026 on AI governance, provenance, regulation and decision quality. What to prioritise, what to ignore, and why clarity beats theatre.
A practical playbook for human-centred AI: redesigning workflows, building capability, governing judgment, and sustaining talent pipelines so AI amplifies human agency rather than hollowing out the organisation.
Most companies use AI, but few achieve real impact. In part I of this series I explore why people—not tools—determine AI maturity, and why the next serious organisations will dominate the space between pilots and profit.
In an age when machines can mimic thought, the real question is who stands behind the words. A reflection on authorship, judgement, and the human presence that gives writing its authority.
AI models mirror WEIRD cultural norms while claiming universality. Alignment methods reinforce this bias, projecting one community’s “common sense” as global truth. Recognising plurality through Wittgenstein’s language-games and Popper’s falsification reframes alignment as provisional and adaptive,
AI's fluency enchants, eroding the old signals of competence and authority. The danger is that trust becomes a machine illusion. Leaders must refuse the managerial shortcut and practise noble language—reasoned, responsible speech—to keep trust a human achievement.
AI is said to be reshaping organisational forms, rendering pyramids obsolete and obelisks ascendant. Yet the deeper truth is distortion rather than stability. The “Rhomboid Organisation” captures this skew—unstable, off-balance, authority flattened.
AI models often mirror our beliefs, rewarding us with agreeable but shallow answers. This sycophancy flatters rather than challenges, eroding judgment and candour. To gain true value, leaders must set incentives that favour truth over comfort, design prompts that demand trade-offs, and treat AI as a