About Marcin

Marcin Dakowski is an executive coach and advisor to C-level leaders, drawing on leadership roles at Allegro and Olex Group plus consulting stints at McKinsey and Kearney. He works with executives on the human side of AI — identity anxiety, team engagement, cognitive overload, and how to roll out tools without destroying trust. Marcin argues efficiency gains only help if leaders address what people feel, not just what they can automate.

What we talked about

Algorithmic anxiety is real — AI threatens not just jobs but identity; after 20 years as an expert, a $20 Claude account can do your work — and self-esteem often ties to what we do.

AI brain fry — Productivity tools promised free time for reflection; instead many leaders run faster, juggling more — engagement globally sits around 20%, down sharply for managers.

Productivity vs busyness — Companies confuse being busy with being productive; AI can automate rubbish work or just add more headless chickens to the office.

The expectation gap — Bosses expect teams to deliver in two days what took two weeks because AI exists — without rethinking workload or giving space to think.

Talk to people, not playbooks — No universal AI rollout recipe; ask teams what frightens them, why adoption lags, and what would help — psychological safety beats five-step slide decks.

AI can make better leaders — Employees can fact-check the boss with Claude in the corridor; authority based on being the smartest person in the room is eroding.

Sharpest moments

On AI and identity:

you were doing something for the last 20 years or so. And you finished graduated from studies and you know, you're an expert in something and now you just buy $20 Claude account and is doing it all for you

On busyness vs productivity:

People believe that when they're busy, they're productive. That's not true.

On the headless chicken problem:

We should have 10 people more. So there will be 10 more headless chickens running around.

On rolling out AI:

why don't you ask them

On addressing the change:

We should address this change. We shouldn't behave like it's not that.

Key takeaways

• AI efficiency tools often create more work, not more time — leaders must deliberately reinvest gains into reflection and team alignment.
• Global employee engagement is already low (~20%); ignoring AI anxiety will push it lower even if adoption metrics rise.
• Managers promoted for specialist speed need new skills — focus, prioritization, and conversation — not just more output.
• Rolling out AI by threatening job loss destroys adoption; understanding individual fears is the actual management job.
• Capitalism's pressure to squeeze AI harder fuels brain fry — but some leaders are using freed hours to walk, dictate, and work from the forest.
• There is no silver bullet for AI change — it is a weekly marathon of checking how the team feels and adjusting, sprint by sprint.