AI Play/Pause Days

AI Play/Pause is a two-day team experiment designed to answer a few seemingly simple questions: Where does AI actually help your team? Where does it get in the way? And where would human thinking be better?

Here's how the Play works:

Your team picks two back-to-back workdays. On AI Play Day, everyone uses AI for as much of their work as they can: drafting, summarizing, meeting prep, brainstorming, you name it. On AI Pause Day, they do similar work without any AI tools.

Then the team comes together to compare notes. What worked better and felt better with and without AI? Where had AI become the default choice, but human judgment would be better?

The magic is in the contrast. Experiencing both extremes back-to-back – and then talking about it as a team – is what creates real, shared insight into how AI fits (and doesn't fit) into your team's work.

Because most teams don't realize how automatic their AI use has become or whether it's actually paying off.

When Atlassian's Teamwork Lab ran this experiment, over 80% of participants felt the urge to "just ask AI" on Pause Day, and nearly 1 in 4 reached for it without even thinking.

At the same time, AI Play Day wasn't all upside. Nearly half of reflections flagged how much effort it took to check and correct AI output. AI often shifts the work rather than eliminating it.

The biggest impact came from talking about it as a team. After comparing notes, 89% of participants said their team had a clearer, shared understanding of when to use AI.

The best times to run this Play are:

• When your team has adopted AI tools but hasn't really talked about them. People might be using AI every day without any shared sense of what works, what doesn't, or what the team's norms should be. This Play starts that conversation.
• When you suspect over-reliance or under-use. Maybe some folks on your team are all-in on AI, and others haven't touched it. Or perhaps everyone's using it, but nobody's sure if it's actually saving time. The two-day contrast surfaces these patterns fast.
• When you're onboarding to new AI tools. Instead of guessing where a new tool will help, let your team try it under real conditions and see what sticks.
• When you want to build shared norms, not just individual habits. Atlassian’s internal experiment showed that individual AI gains don't automatically become team gains. Structured reflection is what bridges the gap.
• After a major rollout or change. If your org just launched a new AI tool or updated its AI policies, this is an easy way to ground adoption in actual experience rather than assumptions.

When Atlassian's Teamwork Lab ran this experiment with about 120 people, they found AI Play/Pause Days:

1. Reveal hidden habits. Over 80% of participants felt the urge to "just ask AI" on Pause Day, and nearly 1 in 4 reached for it without even thinking. Most people don't realize how automatic their AI use has become until they try to stop. The experiment makes those invisible defaults visible.
2. Build real discernment. After experiencing both extremes, 92% of participants felt more confident about when not to use AI. That's the real outcome here: not more AI use, but better judgment about when it helps and when it doesn't.
3. Help create shared team norms. Here's a surprising finding: Dialing AI up or down didn't change how much teammates collaborated. Collaboration looked exactly the same on both days. What did produce a team-level shift was the structured reflection afterward. In fact, 89% of participants reported a clearer shared understanding of when to use AI. Individual experience created individual insight, and the deliberate conversation turned it into shared judgment.
4. Surface the “verification tax.” AI often makes work feel faster, but nearly half of Play Day reflections flagged the cost of reviewing, correcting, or rewriting AI output. That trade-off isn't always obvious in day-to-day work. The experiment brings it into focus so your team can decide where the trade pays off and where it doesn't.
5. Make work feel genuinely better. This isn't just about efficiency. On AI Play Day, people described their work as engaging (64%), satisfying (51%), and purposeful (47%). Priority work felt significantly easier, and stress was notably lower. When AI is applied with intention – to the right tasks, in the right ways – it doesn't just save time. It makes the work itself feel better.