3 Things I Tell Leaders Worried About AI

If your only response to AI is a smaller headcount, you haven't done more with less. Here I break down the three things I tell leaders about AI at work. In this episode we cover: How one economic test reframes AI decisions Why AI rewrites what counts as rare When "everyone can" becomes your responsibility Resources referenced in this episode: So Good They Can't Ignore You by Cal Newport If you want to go further When we work with clients we gather evidence to serve one purpose: to support

If your organisation sees AI as a threat to inclusion, the real opportunity gets missed. Here I examine why AI helps the people who need it most. In this episode we cover: How AI creates absolute social mobility Why privilege loses its hiding places Why more with the same beats cutting people If you want to go further When we work with clients we gather evidence to serve one purpose: to support or undermine a claim, an assumption or a hypothesis. It stops you building work around unexamined

DEI was never a profession, it had no structural defence when the pressure came. Here I examine what went wrong. In this episode we cover: Why inclusion failed every test of professionalisation How occupational groups collapse under political pressure How to professionalise your own inclusion practice If you want to go further When we work with clients we gather evidence to serve one purpose: to support or undermine a claim, an assumption or a hypothesis. It stops you building work around u

If your inclusion work feels zero-sum to leadership, resistance is rational. Here I explain the economic test that eliminates it. In this episode we cover: How zero-sum thinking makes resistance rational Why Pareto improvements eliminate the inclusion objection How to test your interventions against the frontier If you want to go further When we work with clients we gather evidence to serve one purpose: to support or undermine a claim, an assumption or a hypothesis. It stops you building wo

Why should you care about inclusion? Here I explain how I approach this topic in the age of AI. In this episode we cover: Why people are tired of inclusion How we think about these issues Why you should make your own mind up If you want to go further When we work with clients we gather evidence to serve one purpose: to support or undermine a claim, an assumption or a hypothesis. It stops you building work around unexamined issues and keeps you grounded in evidence your colleagues trust. Her

If your professional advantage depends on skills AI can replicate, the compounding has stopped. Here I explain how AI broke the Matthew Effect. In this episode we cover: How scarcity drives the Matthew Effect Why repeatable expertise stopped compounding How to audit which skills still compound If you want to go further When we work with clients we gather evidence to serve one purpose: to support or undermine a claim, an assumption or a hypothesis. It stops you building work around unexamine