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BOULDER COUNTY EMPLOYERS NEED A REWORK LEDGER BEFORE AI CHANGES JOBS
Originally sent on August 18, 2026
Tomorrow, Boulder County is holding a Future of Work workshop built around a blunt premise: many jobs will change, some will disappear, others will be created, and AI and automation will be part of the shift.
That is exactly the right conversation. But employers can make a costly mistake if they translate “AI can do this task faster” into “this job needs less human time.”
First-pass speed is not the same as total productivity. An AI tool may produce a draft, summary, schedule, customer response, estimate, or recommendation in seconds. Then someone has to verify the facts, correct the tone, handle an exception, restore missing context, answer a confused customer, or repair a bad handoff downstream.
Before Boulder County employers redesign roles around automation, they should make that hidden work visible.
For one recurring task, keep a 30-day rework ledger. Record how long the task took before AI. Then record the AI-assisted first-pass time, the minutes spent reviewing and correcting the result, any exceptions or escalations, and whether the final outcome actually solved the original problem. Add the name of the person who remains responsible for releasing the work.
The same ledger can reveal another risk: automating away the tasks where people learn judgment.
Starter responsibilities such as gathering information, drafting an initial response, checking a routine discrepancy, or sitting with a customer problem can look inefficient when a tool produces an answer faster. Yet those tasks often teach employees how the business works, where errors hide, and when a seemingly normal case is actually unusual.
If newer workers never practice those skills, the organization may gain speed today while weakening its ability to supervise automation tomorrow.
That does not mean preserving busywork. It means distinguishing low-value repetition from the hands-on work that develops judgment. AI can take the first pass while people still rotate through verification, exception review, customer recovery, and final accountability.
After 30 days, the decision becomes clearer. If total time falls and errors do not simply migrate to coworkers or customers, the workflow may be ready to scale. If review and repair erase the first-pass savings, redesign the process before changing staffing. If a task is important for training judgment, preserve that learning even if the tool can technically perform it.
The future of work will not be decided by whether businesses adopt AI. It will be shaped by whether they can tell the difference between work that disappeared and work that merely moved somewhere less visible.
Gleb Tsipursky, PhD, a behavioral scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026). https://disasteravoidanceexperts.com/aibook
[email protected]; 614-407-4016; 450 Wetmore Rd, Columbus, OH 43214
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