Latest thinking
Ideas on AI, leadership, the future of work, and the human dimensions of technological change.
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Real-time fashion is here. It will eat your lunch if you are not watching.
Fashion went from made-to-order, to fast fashion, to real-time, where a brand makes 100 pieces, watches what sells, and reorders only the winners. The lesson runs far beyond clothes: the fastest feedback loop wins. Here is how to point that same speed at something better.
He gave a three-billion-dollar company to the planet. What are the rest of us building?
In 2022 Patagonia's founder gave the company away, and paid to hand it over so its mission could never be undone. It is the clearest proof that building for people and planet, not shareholders alone, is not soft. Over a long enough horizon, it wins.
AI is pushing every business to cut. Here is the case for building instead.
The default AI story is to cut: fewer people, lower cost, the same output. The evidence points the other way. Companies that build for all their stakeholders have outperformed the market for decades, and AI makes that better path more reachable, not less.
Your people fear AI will make them redundant. Used well, it makes them more capable.
The fear is that AI shrinks the human role. McKinsey's research finds the opposite is available: people amplified by AI, made more capable, not less needed. That superagency is real, and whether your people reach it is a leadership choice.
When budgets tighten, cutting AI feels smart. The recession winners do the opposite.
In a downturn the reflex is to cut AI as 'future spend'. The recession-winners research says that's the losers' move: only ~9% of firms emerge stronger, and they pair cost discipline with selective investment. AI is the rare lever that is both defensive and offensive.
Your team calls the AI a black box. So how do you trust what it decides?
The honest objection to trusting AI with a serious decision was always that no one could see the working. In 2026 that started to change. What a frontier lab found inside the model, and what it means for how you govern the calls you sign.
Almost everyone is using AI to run the old business faster. Only a third are building a new one.
Costs down, tasks faster, dashboard green, business unchanged: the efficiency trap. Deloitte 2026 finds only 34% are truly reimagining the business while 66% just bank efficiency gains. Efficiency is table stakes and gets competed away. The prize is redesign, and that's a leadership choice.
Sovereignty Is Not a Data Centre
Why the sovereign AI debate in Australia is being fought over buildings, what the June 2026 export controls revealed about AI vendor lock-in, and what open-weight models now make possible on hardware you own.
AI won't decide what it does to your workforce. Your deployment choices will.
AI's effect on your workforce isn't a forecast to brace for, it's a deployment choice. Brookings finds 30%+ of workers could see half their tasks disrupted, but the outcome isn't predetermined: the same tool can augment your people or hollow them out. Choose on purpose.
AI screens the candidates and translates the contract. Who answers when it is wrong?
AI can now screen candidates, translate contracts and rank markets. A 2024 University of the Sunshine Coast review is clear that it augments rather than replaces the one thing that cannot be delegated: human judgement and accountability.
Your company is filling with AI agents. Who is accountable when one acts?
AI agents are moving from pilot to production faster than the governance around them. Deloitte's 2026 data shows adoption racing ahead of oversight, and the edge belongs to the organisations that build the operating conditions first.
Your AI ethics policy is written and filed. So who is actually managing the decisions?
Most organisations have an AI ethics policy and almost none manage AI ethics. A 2021 framework, the Ethical Management of AI, reframes it as a daily leadership practice, not a document that sits on the intranet.