Insights Capacity Building
Capacity Building
Turning a leadership decision into something a workforce can actually execute, day to day, inside their own workflow.
-
"Looks good to me" — three words I'm still trying to unlearn
As more of the workforce shifts from generating AI output to judging it, the missing skill is writing down what success means before you've seen the answer.
-
Half my AIGP class didn't want to be there. That taught me more than the syllabus did.
AI governance certification is having a moment across Singapore and Malaysia. A frontline account of why it sticks for learners with a live case, and slides off everyone else.
-
The first time someone told me about shadow AI, I reported it. I wouldn't now.
Why treating unsanctioned staff AI use as a discipline problem teaches people to stop disclosing it, and what changes when it's read instead as a training needs analysis delivered for free.
-
Why change management for AI adoption keeps failing, and what actually works instead
Licences activated, training completed, dashboards green, and nothing about how people actually work has changed. The fix isn't more training. It's admitting AI adoption doesn't behave like the change your change management was built for.
-
I taught agentic AI in the wrong order, and I suspect I'm not the only one
A candid account of teaching multi-agent orchestration to a room that hadn't yet learned to trust one AI with one task, and the single-agent exercise that fixed it.
-
Everyone in my class can prompt now. Checking the answer is another matter.
Prompting has become easy enough that checking the output quietly became optional. A field note on why capacity building now needs to train the habit of catching a plausible-but-wrong answer, not more prompt literacy.
-
Change management ROI: what skipping the people side actually costs
There's no universal dollar figure for change management ROI. What's consistent across the evidence is the gap between organisations that fund the human side of an AI rollout properly, and the ones paying for the shortfall in turnover, absenteeism and burnout instead.
-
Checkbox adoption: what happens when you mandate AI without managing the change
Seventy-four percent of companies have yet to show tangible value from their AI investments. BCG's own diagnosis is that the gap is people and process, not technology, and most mandatory rollouts fund that ratio backwards.
-
Psychological safety: the secret engine of AI adoption
Training's done, licences are active, and adoption is stalling anyway. The reason usually isn't the technology or the budget. It's that employees don't feel safe enough to actually use what they were given.