When I wrote the first version of this, a year ago, I’d just started in a team at EY, and AI came up in every meeting as the answer to whatever we were discussing. Better insights, faster output, smarter workflows. The more tools we added, the noisier it got.
What I didn’t write then, and should have, is that the whole business runs on having answers. A consultancy sells the expert in the room: the person who’s seen it before, has the framework, and can tell you what to do by Friday. The day rate pays for that certainty.
The manager who always knew
I worked with a manager there who was the purest version of that. Endlessly optimistic, always in control, and always certain of the outcome before the work had started. Every plan was going to land, every timeline would hold, and the answer was there before you’d finished asking the question. There wasn’t any room for doubt in those meetings; saying “I’m not sure this works” felt a bit like disloyalty.
I don’t think they were a bad person (they were good at what the job rewarded). But I watched what that certainty did to a team. People stopped saying what they actually thought, the risks went under the table, and the problems showed up later, at the client, where they cost a lot more. A room where nobody’s allowed to doubt is a room where nobody learns anything.
Answers got cheap

Now anyone can get a dozen confident answers out of a chat window in a minute. Many of them are wrong in ways that take an expert to spot, and a lot of the work built on them has to be redone. The Guardian called it ‘workslop’ last October and put the blame on employers who roll out the tools without time, context or guardrails.1
That’s a problem for any business whose product is the answer. If the deck can be generated, what’s the client paying for? The big firms’ reply so far has been more of the same: AI practices, AI frameworks, AI maturity assessments, sold by the head, with the same certainty they sold the last wave with. My old manager would’ve loved it.
What I’d pay for instead
The people I’ve seen lead well through this are the opposite of that manager. They say “I don’t know yet, let’s find out”, they listen before they decide, and they make room for a team to try things and get them wrong. McKinsey (of all places) wrote about leadership moving from the expert to someone who helps a group learn.2 The WEF put it more bluntly: technology without a workforce that’s ready for it turns into an expensive experiment.3
Humility is a hard thing to put on an invoice, which is maybe why the big firms don’t sell it. And it’s why I think the model where an outside expert hands you the answer has run its course. What’s worth paying for now is someone who sits next to your team, says what they don’t know, and builds the thing with you.
I still don’t have the answers (I’m not sure anyone does right now), and I’m getting more comfortable saying so. Is that a weakness in someone you’d hire, or the thing you’d want? 🌈
Read more
- AI workslop: why the buck stops with the boss, The Guardian
- The inside-out leadership journey, McKinsey
- Closing the intelligence gap: scaling AI with strategy, data and workforce readiness, World Economic Forum
