Two Companies, One Week, Neither One Blamed AI for the Layoffs

Monday.com cut 630 people this week. That's one in five of everyone who worked there a month ago.

Visa followed two days later. Same earnings-week window companies often use to fold a headcount cut inside a quarterly report. 2,600 jobs. 7% of staff. Announced the same morning as its results. CEO Ryan McInerney told investors that artificial intelligence is "accelerating the evolution" of the work. Monday.com pointed to its new AI Work Platform and a leaner operating model. Neither company said an AI system replaced a specific set of people. Bloomberg reported that automation was not the sole or primary factor behind Visa's decision.

Someone at Monday.com is scrolling that Slack channel right now, searching for their manager's name among who's still there. Was it me. Was it my role. Was it the algorithm. Nobody in that channel gets a straight answer. Even the companies making these calls are not fully sure how much is AI and how much is an org chart they already wanted leaner.

That gap deserves a name. I spent 20 years inside Cisco, building a $1.1B innovation portfolio. I sat in enough budget reviews to know how a headcount slide gets built. AI has become the word a board reaches for when it wants a cost cut to read as strategy instead of a retreat. "We are becoming an AI company" survives a headline better than "we are choosing to spend less on people." Companies have made that second decision in every downturn for a century. Only the label on the slide has changed.

This earnings season, 78% of companies citing layoffs pointed to some AI refocus as the reason, on top of the 122,000 tech roles already cut this year. A few names have said the quiet part out loud. Block cut about 4,000 jobs in February, and CEO Jack Dorsey attributed those cuts directly to AI productivity gains. Visa and Monday.com chose softer language. The size of the cut tells you less than the size of the hedge. For the fuller pattern of AI-attributed cuts across 2026, see the running tally of AI job-loss data I keep updated monthly.

History has a slower version of this same story. Paul David's research on electrification found that American factories owned electric motors for decades before productivity actually moved. The work still had to be redesigned around the new tool, not just plugged into the old one. The same lag is showing up now. A company can install an AI platform and announce a smaller org chart in the same news cycle. Rebuilding the actual work around that tool takes years. A press release takes a day.

This is where the relevance cliff gets misread as a slope. Most people picture their skills eroding line by line until they fall behind. The 630 people at Monday.com did not slide down a skills curve. Their cliff arrived as one decision, made in one boardroom, in one quarter. Their name landed on the wrong side of a slide regardless of how current their skills actually were. The relevance cliff measures more than what you know. It measures whether this quarter's story has a place for you in it.

Multiply this across every company reaching for the same script this earnings season, and the labor market ends up running two documents at once. One is the official reason for a cut. The other is the real one. Workers are left planning their careers off the version written for the press.

A slide with AI's name on it makes a headcount cut easier to announce than a slide that just says fewer people, more margin.

If you're the one refreshing your inbox after a round like this, the useful question isn't whether AI took your job. Two companies just showed you that even they aren't sure of that answer yet. The useful question is what you can point to that a slide deck can't erase: a decision you made, a problem only you caught, a result with your name actually on it. That record is worth building before you need it, not after.

If you sit on a board, or run a team, ask the harder question before your own next headcount slide goes out. Are you actually redesigning the work around the tool. Or are you renaming a decision you already made. Your people can tell the difference. Your investors usually cannot. This is the exact audit I walk leadership teams through before a message like this goes out to their own people. I'm easy to find if you want to work through the answer before that meeting.

Alex helps enterprise leaders find the real reason behind a workforce decision, not the version written for investors. Then he helps them build a plan that matches the actual problem.

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