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Workslop: the reality

Most of us don’t work to check boxes or hit shallow KPIs. We’re here to do meaningful work that creates a better future.

And AI can be a huge aid in increasing our "​Impact Per Hour​."

But AI usage doesn't equal value, and “abdicated thinking” AI activity can erode collaboration and increase rework.

We therefore need to measure and manage the downstream burden of AI.

“AI-first” rhetoric without workflow-level decisions creates a strategy–execution gap. The recent viral MIT paper arguing that ​95% of AI pilots fail​ highlighted this.

As we did in the workshop mentioned above, AI should move existing KPIs across departments and strategic initiatives.

To do this, we need both large-scale company projects and individual AI mastery (​join us tomorrow​ to go beyond the surface of AI.)

At Zapier, as CHRO Brandon Sammut ​told us​ in a ​Lead with AI PRO​ Masterclass, there are clearly defined levels of AI fluency, ranging from unacceptable to transformative.

In company-wide AI training, encourage experimentation with AI writing while distinguishing between drafts and decision-ready work, and making clear that the sender owns quality at handoff.

Beyond catching ​hallucinations​, senders should review AI outputs through the lens of the downstream cost of workslop.

Like many AI initiatives, this is 90% culture and 10% technology. Would you forward a Wikipedia or HBR article repackaged as your own? Then don’t do it with AI-generated content.

This is how we avoid behaviors like the two examples ​Brian Elliott​ referenced in his newsletter on this topic:

• Managing up: A colleague who “very clearly puts any question into ChatGPT and pastes the response without reading it” is “loathed by everyone else on the team, but our boss loves him because he answers quickly — even though he’s often wrong and we have to clean it up.”
• Managing down: A CFO who takes marketing presentations, feeds campaign highlights into ChatGPT, and sends back “better ideas” — often lacking crucial context about target customers or market realities.

A Lesson to Include

For most of you who are at the leading edge of AI, hearing about workslop is a good reminder that not everyone is well-versed yet.

Share the article with your leaders and remind them to be mindful of team members who may be (inadvertently) shortcutting work with AI in ways that don’t benefit them or the company. (Without damaging the psychological safety needed to have a culture of experimentation!)

If you already have an AI training program, then here’s a short lesson to include:

1. Start with Tasks, not Tools.

• Know when to tap AI. Typically, this is when it accelerates idea generation, transformation (summarize/translate/rewrite), or validation (compare/checklists).
• Avoid AI as the source of record for new decisions or domains you’re unfamiliar with.

2. Label Drafts & Own the Handoff

• Every AI output is a draft until you, the creator, make it decision-ready. Never forward raw model output without edits.
• Red-team the output: check for hallucinations and read the content as the receiver, does it make sense? Does it raise further questions?
• Our cultural norm is that the sender owns the downstream effort. If the receiver needs to pay a ‘rework tax,’ the work isn’t done.

3. Lightweight Feedback Loop

• For non-routine outputs, track signals like the rework rate (when works get sent back) or ask for feedback on AI-assisted documents

Having this as a simple lesson drives good hygiene in when and how to use AI.

The Bottom Line: Impact Per Hour

No one needs more work.

Retain a culture where the quality of work delivered, whether by a human or human-AI hybrid, is high, as it’s created to make an impact.

Using AI should be a compliment, not an insult, but avoid the slippery slope of abdicating thinking. Prompt well, go back and forth with AI, and offload the part of writing that AI is better at, review, and send.

Move from AI as shortcut to AI as collaborator and reap the rewards, individually and as an organization.

See you next week,

- ​Daan

Exclusive for PRO Members: Identity In The World Of AI

In this Lead with AI PRO LIVE session, we’re excited to welcome ​Dr. Tracy Brower​, global best-selling author and Vice President of Workplace Insights at ​Steelcase​, to lead our next Masterclass on Identity in the World of AI on October 9th at 4PM London / 5PM Amsterdam / 8AM Pacific Time / 11AM Eastern Time.

As AI changes the way we live and work, what does this mean for who we are and who we want or need to become?

If you’ve been wondering:

• How is AI reshaping our sense of identity at work and beyond?
• What aspects of identity do we need to protect in a digital-first world?
• How can leaders foster creativity, curiosity, and connection even as routine tasks shift to machines?
• What role do proximity, trust, and human presence play in shaping who we are in hybrid and AI-powered environments?
• How can we create clarity and confidence while navigating this transformation?

This Masterclass is for you.

With a deep focus on the future of work, identity, and how we thrive amid change, Tracy will share practical, research-backed perspectives on what it means to be human as AI transforms the way we live and work.

Members, the invite is on your calendar.

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