You Can't Fire Your Way to an AI-Ready Workforce
Why the AI layoffs are a reskilling problem in disguise, and what the translation gap really costs.
For two years, AI has been the boogeyman of every conversation about work, and for once the fear has receipts. In a 2026 ResumeBuilder.com survey of 866 US business leaders, 26 percent said they had laid off workers and 54 percent had cut compensation to help fund AI investment (ResumeBuilder.com, 2026). Even the safest credential is no longer safe: computer science graduates, who a decade ago walked into six-figure offers, now face roughly 6 percent unemployment, with entry-level software postings down about 65 percent since the start of 2022 (CNN Business).
The fear is real. Pretending otherwise would be insulting. But here is the part the panic misses, and it is the part that matters most if you run an L&D or talent function.
The boomerang nobody is planning for
Many of these cuts are already reversing. Challenger, Gray and Christmas counted nearly 55,000 US layoffs in 2025 that cited AI (Challenger), and a lot of those decisions are not holding. Forrester predicts that over half of layoffs attributed to AI will be quietly reversed as companies confront the operational reality of cutting human talent prematurely (Forrester, January 2026). In recent survey data, more than half of HR leaders said they had already rehired for eliminated roles within six months (HR Director). The pattern is sharpest in customer service, where Gartner predicts that by 2027 half of the companies that cut staff citing AI will rehire for similar roles, often under new job titles (Gartner, February 2026).
The same organizations announcing cuts to fund AI are, by their own analysts' projections, about to need many of those capabilities back. And the roles they will be hiring for are often not the old roles at all. They are new, AI-shaped versions that did not exist in 2022, the year before AI fluency became one of the most requested skills on a job posting.
So the actual problem is not a labor surplus. It is a sorting failure. Companies are shedding human capability on one side of the building while preparing to pay a premium to buy it back on the other, often for roles they have no proven way to train for yet. It is no surprise that 63 percent of employers name skills gaps as the single biggest barrier to transforming their business between now and 2030 (WEF Future of Jobs Report 2025).
What is the translation gap?
Underneath all of this is a blind spot worth naming. Call it the translation gap: the distance between what your people can actually do and what your organization is able to recognize they can do.
The classic version is mundane. You have a role open for five months and you are paying a recruiter, while the person who could do 70 percent of it today is sitting two teams over with the wrong job title on their badge. Your support lead already handles most of what an implementation specialist does, but the title hides it, so you hire a stranger instead. That choice is expensive: SHRM puts the average cost per hire at over $4,000 and the median time to fill at 44 days (SHRM).
Reskilling the person you already have is the cheaper path by a wide margin. Research from the Financial Services Skills Commission found it costs roughly 2.5 times less than making someone redundant and hiring a replacement, a saving of up to £49,100 per employee in UK financial services (FSSC and PwC UK).
AI widens that gap into a chasm. Now it is not only that your people's skills are hard to see. The roles you most need to fill are so new that no off-the-shelf training exists for them at all. The translation gap stops being a visibility problem and becomes a build problem, and that second half is the one that quietly defeats good intentions.
How to build an AI-ready workforce from the inside
Start with the most reassuring fact in this whole story: your people are overwhelmingly developable. The World Economic Forum estimates that of every 100 workers, only about 11 are likely to be left behind for lack of training by 2030. Of the 59 who will need training, 29 can be upskilled in their current roles and 19 reskilled and redeployed elsewhere in the organization (WEF Future of Jobs Report 2025). The people are reskillable. The only question is whether you can build the training fast enough.
That used to be the hard part. Turning your own expertise into real training meant a months-long production cycle, and by the time the course shipped, the AI tool it taught had already changed. That constraint is gone. Honen takes the material your team already has, the handbooks, the recorded calls, the walkthroughs from your best people, or even just a topic, and turns it into a real, structured course in minutes, with hands-on practice and a tutor that teaches only from your approved content.
How fast is "in minutes"? On a recent 30-minute call with a partner, Ryan Trattner, co-founder and CTO of StudyFetch (Honen's parent company), built several complete courses before the call was over. The bridge that used to take a quarter can now be built while you are still talking through the problem, and updated the moment the work changes.
That is what makes the alternative to the layoff-and-rehire loop practical instead of aspirational. You keep the person who already understands your business, your customers and your systems, and you build them the new, AI-shaped skill faster than a recruiter could schedule a second interview.
What it takes to get ahead
You cannot fire your way to an AI-ready workforce. The math does not work, and your own analysts will tell you so when they project the rehiring. The companies that come out of this era ahead will be the ones that got good at building the missing skill into the people they already had.
The skills are there, or they are learnable by the people who already know your business. What is missing is the path. Forrester's own forecast makes the point bluntly: AI will augment about one in five jobs over the next five years, which is why the firm urges companies to invest in their people rather than replace them (Forrester).
Frequently asked questions
Why can't you fire your way to an AI-ready workforce?
Because many of the roles being cut are already being refilled. Forrester predicts more than half of AI-attributed layoffs will be quietly reversed, and over half of HR leaders have already rehired within six months. Reskilling the people who already understand your business is faster and cheaper than cutting and rehiring.
What is the translation gap?
The translation gap is the distance between what your people can actually do and what your organization is able to recognize they can do. It is why a role can sit open for months while someone two teams over could already do most of it.
Is it cheaper to reskill an employee or hire a new one?
Research from the Financial Services Skills Commission found reskilling an existing employee can cost roughly 2.5 times less than making them redundant and hiring a replacement, a saving of up to £49,100 per person in UK financial services.
Can most employees actually be reskilled for AI roles?
Yes. The World Economic Forum estimates that of the workers who need training by 2030, the large majority can be upskilled in place or reskilled and redeployed, and only about 11 in 100 are likely to be left behind.
See the alternative to the layoff-and-rehire loop in action.
By StudyFetch Staff. Honen turns the materials your team already has into real courses they'll actually finish, built in minutes and measured by mastery.
