What are we doing? I mean apart from back-to-back meetings and emails...

Your job title sounds impressive, but what do you actually do all day?

Most knowledge workers have impressive job titles. Strategy Lead. Innovation Manager. Digital Transformation Consultant.

Sounds impactful, right? But what do these people actually do all day?

• Sit in endless meetings
• Drown in emails
• Chase approvals
• Keep up with Teams, Slack and another dozen apps that act like Tamagotchis who desperately seek our attention

None of this is in anyone’s job description. But somehow, this is the job now.

And instead of fixing the root problem, we’re throwing AI at it.

• AI to summarize meetings we probably didn’t need in the first place
• AI to transcribe calls that could’ve been an email
• AI to write emails no one really needs to read

We call this “progress”. But are we really winning anything?

We’re not solving the problem. We’re just making our inefficiencies more efficient.

How do we fix this?

AI isn’t the solution, work design is

1. Fewer, better meetings

   • No agenda? No attenda.
   • Default to async over sync
   • Cap meetings at 20 minutes. No, for real. In case you can’t decide within that timeframe, it means that the participants aren’t prepared.

2. Kill the email addiction

   • Reduce reply expectations
   • Use structured communication (Teams threads > Email chaos)
   • Automate low-value responses, but eliminate unnecessary emails entirely

3. Measure actual outcomes, not just activity

   • Focus on impact, not hours logged
   • Reduce performative “busyness”
   • Give teams deep work time, not just AI-powered admin tools

4. Leverage AI for what actually matters

   • AI should augment creative, strategic, and decision-making work—not just clean up our mess
   • Use AI to eliminate low-value tasks, not make them easier to tolerate

If you need an AI-powered chatbot today to find the right document, you soon need an AI-powered chatbot to find the right chatbot, to find the right document…

In short: Do your homework first before you employ Copilot. Otherwise, the results will be disappointing (but then you get the chance to blame Copilot 🤡).

I am not saying that there are not good genAI use cases, but please stop this nonsense. We don’t need AI to be better at running in circles. We need to break the cycle entirely. Let’s stop optimizing inefficiency and start designing work that actually works.

Thoughts? What’s the worst example of “fake productivity” you’ve seen?