Heuristic
Automate the part you can change without waiting for everyone else
A local tool can change your drafting today. It cannot unilaterally cancel everyone else's meetings.
When it fits
- AI adoption is stuck because the desired benefit depends on organization-wide coordination.
When to avoid it
- Local optimization can shift work to others; measure downstream burden before declaring the independent change a net gain.
Why it matters
Separate work changes you can make independently from those that require new team norms, approvals or shared workflows. Start AI experiments where one worker can change the process and measure the result. Treat coordination-dependent benefits as a separate organizational change problem rather than assuming tool access will create them.
An example
Use AI to reduce email drafting time now; do not count fewer meetings as an expected benefit unless meeting norms and decision processes also change.
Check your result
The experiment's expected benefit matches the level of coordination the intervention can actually influence.
Keep this limit in mind
- Local optimization can shift work to others; measure downstream burden before declaring the independent change a net gain.
Connected ideas
Useful withMeasure AI speed and quality as separate outcomes
Evidence and sources
A randomized field experiment with 6,000 workers found that AI access reduced time spent on email and appeared to speed document work, while meeting time did not significantly change.
The intervention and work environment were specific; organization-wide coordination effects should not be inferred from individual task savings.
Shifting Work Patterns with Generative AI · Abstract results
The 6,000-worker field experiment concluded that AI initially changed behaviors workers could modify independently more than behaviors requiring coordination with others.
This describes the studied deployment period and should not be treated as a permanent law of AI adoption.
Shifting Work Patterns with Generative AI · Abstract interpretation