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Faida Workforce · AI that Works AI that Works →

Big Tech’s Layoffs Are a Turning Point. What Small and Mid-Sized Employers Should Check Before Copying Them

Microsoft announced it would cut 4,800 jobs. That news landed oddly for many observers, because the company had just reported net income of $31.8 billion last quarter, up 23% year over year. The source article frames this as the reality of business in 2026: profitable public companies cut thousands of jobs, affecting thousands of real people, to justify large AI investments to Wall Street. If you run a small or mid-sized business, this is not just a headline about someone else. It is a signal about where workplace culture is now being built, and about the assumptions you may be importing into your own planning.

What actually changed

The source article makes a structural argument, not a moral one. It says large corporations can no longer serve as the cultural leaders for American businesses, and that they are structurally incapable of doing so. That is a shift from the recent past, when big companies set the template. The article describes how, fifty years ago, Milton Friedman published his doctrine that the sole social responsibility of business is to maximize profits for shareholders. That idea reshaped business schools, boardrooms, and eventually the personality of corporate America itself.

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Over the last year, the article says, that idea has been taken to an extreme. It lists a series of cuts: Amazon cut 16,000 corporate jobs in January, in addition to 14,000 jobs cut in 2025. Block cut nearly half its workforce in February. Since then, several other American giants, including Salesforce, Intuit, Oracle, GitLab, Meta, and Cisco, have laid off several thousand employees as well. The article describes these companies as justifying reductions under the push for AI modernization and efficiency.

The cultural markers the article points to are fading. The Detroit auto companies that mirrored their employees’ lifelong loyalty are gone. IBM’s paternalistic career culture is gone. Google’s once fabled cafeterias and its 20% time rules are steadily eroding. The article’s point is not nostalgia. It is that the playbook smaller companies once copied is being dismantled by the companies that wrote it.

The AI excuse, and the number that undercuts it

The most useful fact in the source article for anyone making an AI decision is this: according to SHRM, only 6% of jobs are both highly automatable and free from the practical barriers that would actually let AI displace them. The article’s conclusion is direct: AI is transforming jobs, not eliminating them. Which means external conditions are not forcing these cuts; company leadership is choosing them.

That distinction matters for your own planning. If you are a small or mid-sized employer, you are probably under pressure to show that you are “doing AI.” The temptation is to treat headcount as the visible proof of that effort. The source article suggests that the largest companies are doing exactly that, and that the automation case is much narrower than the rhetoric implies. Before you restructure a team around an AI tool, it is worth asking whether the work is genuinely automatable and free of the practical barriers the SHRM figure refers to. If it is not, you may be copying a decision that was made for market reasons, not operational ones.

What small and mid-sized employers did instead

The source article draws a contrast. While large companies were announcing what it calls unavoidable layoffs, small and mid-sized businesses largely avoided mass layoffs. Instead, the article says, they used AI to change what their teams could do, invested in flexible talent, and emerged more resilient. It also reports that nearly half of SMB leaders reported maintaining high confidence throughout 2025’s economic shocks.

Employees have noticed. The article cites employee happiness data showing companies with fewer than 25 employees scoring an average net promoter score of 51, while companies with more than 500 score 34. That gap, the article says, has been widening since 2021.

The article is careful about why. It says this is not happening because private business owners are morally superior people who have transformation figured out. It is because they are structurally free. Without the obligation to translate every decision into a story that will move stock, private business owners can afford to think in years, not quarters. The article gives two examples: a multinational apparel company like Patagonia can dedicate 100% of its profits to fighting climate change, while a manufacturing technology company like Barry-Wehmiller can refuse layoffs, even with their backs against the wall.

That is the practical takeaway. The advantage is not virtue. It is the absence of a quarterly narrative requirement. You can decide that a person is worth more than a nominal point of margin, and decide for yourself what corporate culture should look like.

What to check before you act

If you are weighing AI-driven changes to your workforce, the source article suggests a short list of checks. None of them require you to be a certain size or sector.

  • Separate the automation case from the market story. Ask whether a role is both highly automatable and free of practical barriers, the two conditions in the SHRM figure. If only one is true, the decision is a choice, not a necessity.
  • Check your time horizon. The article’s core structural point is that private and smaller companies can think in years rather than quarters. If your planning cycle has quietly shortened to match public-company reporting, that is worth noticing before it drives a headcount decision.
  • Look at what you are copying. The article describes a period when smaller companies idolized public companies, copied org charts, and cribbed perk playbooks. Some of those templates are now being abandoned by their authors. It is worth asking which of your practices came from that playbook and whether they still fit.
  • Treat flexible talent as a real option. The article reports that small and mid-sized businesses invested in flexible talent rather than cutting. That is a different way to absorb change, and it preserves the ability to reverse course.
  • Watch the culture signal. The net promoter score gap the article cites, 51 for companies under 25 employees versus 34 for companies over 500, has been widening since 2021. If you are competing for the same people as larger employers, that gap is part of your pitch whether you mention it or not.

What this means for your business

The source article’s argument is that the cultural leadership of American business is shifting toward small and mid-sized businesses and private companies. It also says public companies may continue to lead in infrastructure, capital markets, and scale. Those are not contradictory. The point is that the template for how work feels, and how decisions about people get made, no longer has to come from the largest employers.

For a business reader deciding what to do about AI at work, the practical version is this. AI is changing what teams can do. That part is real and worth investing in. The claim that it forces mass layoffs is not supported by the automation numbers in the source article, and the companies making the loudest cuts are doing so while profitable. You are not required to follow that pattern. You can use AI to expand what your existing team can do, bring in flexible talent where it fits, and keep your planning horizon long enough to make decisions you can defend in a year.

Faida Workforce works with employers on workforce planning and flexible talent, so we have a commercial interest in this topic. We are noting that plainly. The checks above stand on their own, and you can run them without us.

Sources

By Faida Workforce Editorial. AI tools assist in production; a human editor is accountable for the published piece.

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Written by
Editorial Workforce Desk

The Faida Workforce editorial team: practitioners who deploy AI employees in production, and write about what actually works. Every article is reviewed by a named human editor before publication.

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