this post was submitted on 29 Dec 2025
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[–] panda_abyss@lemmy.ca 112 points 1 day ago (3 children)

Salesforce has now begun reframing its AI strategy, shifting away from the language of replacement toward what executives call “rebalancing.” Rather than eliminating roles outright, the company says future AI deployments will emphasize augmentation, with humans retained in decision-critical and customer-facing positions.

This was so obviously the solution that should hav been tried first

Salesforce’s reversal has become a reference point in ongoing debates about AI and employment. While automation remains a central pillar of the company’s long-term strategy, its experience has underscored a growing consensus among executives and analysts: AI can reduce workloads, but replacing skilled workers too quickly carries real operational risk.

I don't get why boards don't dump these CEOs. I'm sure they're happy with the reduced costs from firing half the employees, but to not consider the potential issues and actually vet the quality was such a bad decision. The facts are there was zero advantage to being the first to do AI customer support, but firing half your employees is irreversible.

[–] Feyd@programming.dev 50 points 22 hours ago

The CEO is the face. The board is involved in decisions of this magnitude.

[–] Kirp123@lemmy.world 17 points 17 hours ago* (last edited 16 hours ago)

A lot of these companies chase short term gains to look good on their quarterly report. These CEOs were most likely lauded when they presented the lowered costs on that quarterly and most likely got some fat bonuses out of it too. Now that the chickens have come to roost they are scrambling but they can still get away by blaming it on other shit. Even if they do get removed they already made their money through those bonuses and they can find a different position where to fail upwards.

[–] NikkiDimes@lemmy.world 10 points 20 hours ago

I’m sure they’re happy with the reduced costs from firing half the employees, but to not consider the potential issues and actually vet the quality was such a bad decision

Kind of becomes irrelevant when the initial reduced costs were probably decimated by secondary costs they hadn't even considered, for example, time wasted by remaining employees now burdened with correcting the AI's mistakes.