Most AI adoption plans are built around access — which tools, which licences, which training programme, which rollout timeline. These are the variables that appear in budget conversations and Board updates — but they are not the whole picture. What rarely makes it into the plan is friction. Not resistance, which gets plenty of attention and there are workshops for that, change management frameworks, and communications strategies designed to move people from sceptical to willi

I was the Emcee at PX Live last Friday and I intentionally held back from mentioning AI — and it came up anyway. When it did, it was through the familiar ‘tool lens’ — which from a room full of People Leaders, was slightly surprising — but, at the same time, not so surprising. That’s where most People Leaders are heading at the moment — the obsessive search for use cases, practical skills, and the latest frontier model functionality that will provide them with an army of agen

The cost of not trying is higher than the cost of trying and failing. That’s the tension sitting underneath every AI conversation I have with people in organisations right now — and most of them haven’t named it yet. Time is one of the most consistently cited blockers I hear when delivering AI training and workshops; whether it’s time to learn, initial set-up time, or a general sense of having no time to dedicate to learning, experimenting or exploring. Without dedicated time

I get asked three questions quite consistently about AI, and they all focus on one theme — “Will AI replace us?” The three questions are: 1. Which LLM is the best for the type of work I’m doing? 2. What AI course do you recommend? 3. Which jobs will be replaced by AI in the next 12 months? That last question is the one where I feel the most anxiety and tension emanating from the person asking it, and I understand why. Since ChatGPT launched in November 2022, entry-level job p

This is the eleventh post in a series I write for People Leaders who want clarity, not hype. My aim is always the same: to take the parts of the AI conversation that feel technical, abstract, or simply overwhelming, and translate them into something a people leader can actually use. This post is about a decision that has almost certainly already been made in your organisation, either with you or without you. It is about what that decision really commits your people to — and w

There is a growing narrative that “building AI agents” is the next step for progressive People teams, and that if you are not experimenting with agents you are somehow lagging behind. I’m hearing this in leadership conversations, it’s all over LinkedIn and it’s certainly filling vendors sales pipelines. I call this the Agent Illusion . The Agent Illusion is the belief that deploying AI agents will unlock productivity on its own, without redesigning workflows, cleaning up data

Why HR doesn’t have an AI tools problem, it has a judgement problem it cannot yet see. In a recent session with a Global Leadership team, I opened with a simple line: HR does not have an AI tools problem. HR has a capability visibility problem. The room went quiet, and not because it was controversial, but because it was uncomfortably accurate. Across enterprise and scaling People functions, AI adoption is now measurable. Dashboards exist, licences are activated, prompts are

Across multiple leadership and workforce studies, critical thinking consistently shows up as the skill that separates leaders who can use AI well from those who inadvertently outsource their judgement to it. In other words, AI isn’t replacing thinking - it’s exposing where it was weak all along. Combine this with most organisations rushing to build AI literacy without building critical literacy of AI – and we’re starting to surface a real problem. AI is exposing a thinking g

For years, organisations have treated change as something with a beginning, a middle, and an end. You’ve been there - a transformation programme is launched, a roadmap is created, people are trained, and eventually, the organisation is declared “ there ”. That mental model is now obsolete. Not because leaders are failing to manage change properly, but because the conditions that made episodic change viable no longer exist. AI has simply exposed what was already true: volatili

Most organisations are sprinting into AI adoption based on the AI-hype narrative. That leads to a flurry of experimentation without purpose, testing without clear success metrics, and all of it happening in silos that limit communication of outcomes. It looks productive. It feels progressive. In reality, it’s neither. Because AI isn’t failing due to lack of effort. It’s failing because no one’s translating what’s actually happening. Teams are building vertical capability with