The Question Nobody Was Asking
AI may save an employee half an hour. The unsettled part is what happens next. That question arrived at a panel session at OutSystems One. Stijn Stabel, VP of Data and AI at TVH asked something deceptively simple: if someone is half an hour faster, where are they spending that half hour?
Ian Thomas, writing for diginomica, argues that the answer tells you everything about an organization. Vision statements, values decks, and executive town halls cannot match it.
Words Versus Behavior
The source's core argument is blunt. Executives routinely say AI will augment workers, make work more meaningful, and protect jobs. Language is slippery; behavior is solid. The half-hour is behavior.
Thomas identifies three extractive patterns. First: every saved minute crammed with another task means augmentation just means working harder. Second: saved minutes gathered to justify headcount reduction means employees become collateral damage. Third: time spent supervising unreliable AI turns workers into a miserable accountability sink for every error the system makes.
Contrast those with the expansive pattern. If some time is given back to make better decisions or deliver better service, employees become part of the solution rather than part of the problem.
The Ambition Test
The source goes further. How a company allocates the half-hour also measures executive imagination.
Choosing to do the same work with fewer people is a tacit admission that leadership cannot see where new value might come from.
Thomas notes that layoff announcements enabled by AI are frequently met with a stock-price bump. He calls this a short-term sugar rush. If every company uses similar technology to make existing work cheaper, they lower the cost of competing in the same market without creating advantage. A race to the bottom follows.
The alternative: use the half-hour to reduce the cost of operating what is, and free up capacity for what can be. New products, new markets, segments previously too marginal to serve.
What Leaders Deploying AI Should Do Now
This is a single columnist's argument from one panel moment, not a measured study. The framing is compelling, but the evidence base is thin. That limitation matters.
Still, the diagnostic question is actionable. Before the next AI deployment goes to production, leaders should answer three things explicitly.
One: what is the named use for recovered time, written down, not implied? Two: who owns accountability when that commitment conflicts with a quarterly cost target? Three: which group will see the reinvestment first, and on what timeline?
If those answers do not exist, the rollout is not a strategy. It is an efficiency experiment with no declared destination. The half-hour will be spent regardless. The only question is whether someone decided how, or whether the organization simply let pressure decide for them.