by Wayne Pales | May 24, 2026
Everyone warned me that AI would expose our data problems. That prediction turned out to be true and, in the way it usually gets discussed, completely misleading. Yes, when we pointed AI tools at parts of our data, the cracks showed. Inconsistent records, duplicated...
by Wayne Pales | May 17, 2026
I learned that people in my organisation were using AI to help write performance and development documents. My reaction split cleanly down the middle: thrilled, and worried, in equal measure. Thrilled, because this is exactly the maturity we’d been building...
by Wayne Pales | May 10, 2026
We are use case led. Almost every organisation says this about AI now, and it sounds like discipline. Increasingly I think it’s where discipline goes to hide. Here’s the pattern I’ve watched, in our organisation and others. The call goes out for AI...
by Wayne Pales | May 3, 2026
We declared early that AI was everyone’s job. It sounded right, it went on slides, and heads nodded everywhere it was said. Months later I noticed what the phrase had actually produced: warm agreement and thin accountability. Use cases waited for someone to...
by Wayne Pales | Apr 26, 2026
Early in our AI journey, I made a well-intentioned decision that nearly stalled us. I opened the conversation to everyone. It felt right, and in a culture sense it was. People across the organisation had views about AI, hopes and worries both, and inviting them in...
by Wayne Pales | Apr 19, 2026
Three plain words have defused more anxiety in our AI program than any risk framework we’ve produced: learning before scaling. I stumbled onto the phrase in a tense meeting. Stakeholders were worried we were moving too fast, others that we were moving too slow,...
