One of the most common assumptions in business is that the organisations that win technology revolutions are the ones that move first. The opposite is usually true. Every major technology wave brings with it a familiar sense of urgency. The message is always the same: move early, get ahead, don't get left behind. With AI, that pressure has reached another level entirely. Every board wants to know the strategy. Every investor wants reassurance. Every leadership team feels comp

One of the reasons so many organisations struggle to define an AI strategy is that they start by treating AI as a single thing. Leadership teams ask, "What's our AI strategy?" as though there is a single answer, a single roadmap, or a single investment decision that will determine success. The result is often a broad conversation that mixes together workforce productivity, technology platforms, product innovation, governance, and competitive positioning. Unsurprisingly, this

Few things unite the internet quite like mocking corporate language. People roll their eyes at phrases like "circle back", "align on priorities", "take this offline", or "let's socialise the deck". Entire LinkedIn careers have been built on translating corporate jargon into plain English and congratulating themselves for doing so. The assumption is that corporate language is dishonest. That it obscures meaning. That authentic people should reject it in favour of speaking exa

For decades, human augmentation belonged largely to the realm of science fiction. Neural implants, cybernetic limbs, genetically engineered humans and visions of transhumanism felt distant, speculative and, for most people, irrelevant. At the fringes of technology conferences, there were people who had implanted RFID chips beneath their skin, evangelising about a coming cyborg future. But it all felt less like the beginning of a societal transformation and more like a niche s

The Hidden Asset Inside Every Organisation One of the least discussed risks in AI-led transformation is not technical. It is organisational. Much of today's AI conversation focuses on automation. How do we reduce effort? How do we accelerate decisions? How do we eliminate friction from processes that have traditionally relied on human intervention? These are important questions, but they often obscure a more fundamental one: what happens to organisational judgement when decis

One of the dominant narratives surrounding AI is that it acts as a force multiplier. Faster decisions. Better insight. Lower costs. Greater productivity. And in many cases, that narrative is entirely justified. Organisations are already using AI to accelerate content creation, automate routine work, improve customer experiences and support decision-making at a scale that would have been difficult to imagine only a few years ago. But beneath the excitement sits a less discuss

The Modern Equivalent of a Strongly Worded Letter The other day, while walking back from the local garage after being informed (for the second time in as many months) that one of my wheels had cracked after encountering one of the many potholes decorating our rapidly disintegrating roads, I did what any reasonable person would do. I rage coded (think vibe coding, but angrier). Within twenty minutes I had built a working prototype of an application designed to crowdsource poth

The pharmaceutical industry has traditionally been built around a relatively simple proposition: identify an illness, develop a treatment, communicate the health benefits, and improve patient outcomes. GLP-1 medications challenge that model. While these medicines deliver significant clinical benefits, including weight loss and reductions in the risk of numerous obesity-related conditions, their cultural impact extends far beyond healthcare. They occupy a space somewhere betwe

Why enterprise design has to come before the model is trained AI is an office full of ghosts. Most AI models are trained on the past and the present.On historical data.On legacy systems.On the observed behaviours of today’s employees and customers. In other words, they learn how things have been done — not how they should be done, and certainly not how they could be done if we were starting again today. That’s the paradox. For a technology we describe as futuristic, AI doesn’

Most transformative innovations follow the same quiet underlying pattern. A straight line becomes a triangle. Then the triangle collapses back into a line. Originally, a commercial relationship looks simple: company ↔ customer. Customer service agents are critical to maintaining that relationship, but they are experienced as part of the company, not as a separate node. It’s only when that internal component is recognised as a distinct element - with its own constraints, incen

“History never repeats itself, but it does often rhyme.” Probably Mark Twain If my LinkedIn feed is anything to go by, we may already be at -or just past - peak ChatGPT. If so, I’m probably late to the party. I’m not a technical expert on large language models. I can’t tell you whether GPT-4 is one release away from escaping onto the internet and going full Skynet, or whether the proposed AI “moratorium” from Elon Musk and friends is really just excellent tech PR—designed to

I grew up in the mid-Hampshire countryside, in a small village, and attended the local Church of England primary school in the late 1980s. It wasn’t an exceptional start to an education and probably lacked much in the way of cosmopolitan outlook, but after nearly twenty years living in a capital city, I find myself looking back on it with increasing fondness. One long-running school tradition was the Friday morning assembly. All the classes would gather in the main hall to be