I work at SymphonyAI, an enterprise software company whose entire identity is built around artificial intelligence.
That context makes what is happening internally almost absurd.
Leadership has acknowledged that the company was caught flat-footed by how quickly AI changed the software market. At the same time, employees are being told that ordinary productivity gains are no longer enough. The expectation being discussed is two to three times the productivity through AI.
Think about the double standard embedded in that.
Leadership can be late to the AI transition. Employees cannot be slow.
Leadership can build an organization that no longer fits the economics of the business. Employees have to prove the same work can be done with fewer people.
Growth disappoints, churn becomes severe, products need modernization, margins come under pressure, and somehow the recurring solution is “workforce transformation.”
That phrase deserves scrutiny.
Contractors disappear. Positions are not necessarily backfilled. Support functions shrink. Teams absorb more responsibility. Work gets pushed deeper into already-stretched organizations. Employees learn AI tools, automate work, cover vacancies and somehow keep customers supported.
Management then looks at the fact that the work is still getting done and concludes that perhaps fewer people were needed all along.
That creates an incredibly destructive incentive inside a company supposedly trying to make employees embrace AI.
The lesson becomes: if you prove AI makes you more productive, you may simply prove management can remove another person.
And every reduction comes wrapped in inspirational language. Fewer resources becomes “agility.” More responsibility becomes “empowerment.” Not replacing people becomes “AI productivity.” Cost reduction becomes “transformation.”
Employees are not stupid. We know what austerity looks like even when someone puts “AI first” on the slide.
The part I find hardest to accept is the direction of accountability.
Employees are expected to know their market, know their products, explain their performance, defend their decisions and hit increasingly aggressive expectations. Yet when leadership misjudges a major market shift, builds too much complexity, allows churn to become a serious problem or fails to create sufficient growth, the consequences seem to land several levels below the people who made those decisions.
At some point workforce transformation needs to include the people responsible for making the workforce transformation necessary.
Before SymphonyAI asks employees for three times the productivity, there is a simpler question leadership should answer:
How did an AI company end up needing its workforce to rescue it from the consequences of moving too slowly on AI?
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