Thinking on AI from our team
Practical perspectives on AI strategy, implementation, and leadership — for the executives and teams doing the real work.
Why most AI strategies fail before they start
The single biggest mistake companies make when approaching AI isn't technical — it's starting with the technology instead of the problem. Here's how to get the order right.
Read article →The hidden cost of not automating
Every manual process that could be automated carries a cost far beyond headcount — in quality, speed, and the opportunity cost of your best people.
How to evaluate an AI vendor without a technical team
Choosing an AI partner is one of the most consequential decisions a business leader will make. A practical framework for getting it right.
LLMs in the enterprise: what actually works in production
After deploying large language models across a dozen enterprise environments, here's what we've learned about what holds up and what collapses under real load.
The AI roadmap mistake every executive makes
Most AI roadmaps are technology roadmaps dressed up as business strategy. The difference matters enormously when it comes to execution and ROI.
Why your AI pilot succeeded and your rollout failed
The pilot-to-production gap is where most enterprise AI projects die. It's not a technology problem — it's an organisational one.
Measuring AI ROI: a framework that actually works
Most AI ROI calculations are wrong. Not because the math is hard — because the wrong things are being measured. Here's a framework that ties AI to business outcomes.