Before You RIF: 7 Alternatives to Layoffs in the Age of AI
In the past two years, more than 500,000 workers have been laid off across industries by companies simultaneously declaring that AI is transforming how they work. Read that again. The very transformation those companies are betting their future on is being funded, at least in part, by cutting the people who will need to carry it out.
Yes, CEOs are scrutinizing headcount. Boards want to see AI's promise reflected in OPEX. And HR is being asked to be the, sometimes blunt, instrument of that accounting. A RIF is a visible, fast answer. But is it always the best one?
What follows are seven alternatives worth trying first, drawn from research, from practice, and some late-night thoughts about toy boxes and telegraph operators.
The Hidden Cost of Layoffs
There's a version of a quote from the 1930’s political philosopher Antonio GramsciOpens in a new tab that you might know. Written from a prison cell in fascist Italy, it loosely reads: "The old world is dying, and the new world struggles to be born: now is the time of monsters."
The conventional reading is that the monsters are the resisters – the people clinging to old models, old hierarchies, old metrics, who can't or won't let go of a world that's already leaving them behind. And yes. Those monsters are real, and HR professionals encounter them regularly.
But I've been thinking about the other monster that comes from change. Haste.
We are making a breathtaking transition in how we live and work – and that comes with uncertainty and pressure There is a very human impulse to do something decisive when the pressure is on, even when decisive is the wrong gear for the road. I’m guessing you may be feeling a lot of pressure from leadership right now.
But this is worth thinking through, because what's at stake is the culture and trust and human infrastructure that you’ve spent years, sometimes decades, painstakingly building.
And here's the thing about RIFs that rarely makes it into the spreadsheet: the people who survive them don't feel lucky. They feel watched. They feel guilty and uncertain. They wonder who's next. This is not a lean team raring to take on innovation. These are battered survivors.
According to our Gallup and Workhuman research, employees who don't feel recognized at work are already 8x more likely to be actively disengaged and 4x more likely to be actively looking for another job – and that's in stable times. Layer a layoff on top of that fraying sense of belonging and you've often triggered exactly the talent exodus you were trying to avoid, just on a delay.
So yeah, layoff cuts save OPEX. But at what cost to transformation?
I've been lingering on the fringes HR and workforce strategy long enough to know that the pressure to demonstrate AI's efficiency promise is real, and I'm not here to pretend it isn't. The mandate is coming from boards, from CFOs, from CEOs who read the same McKinsey reports everyone else is reading. HR is being asked to show up with a number.
I think what I'm arguing is that the number doesn't have to come from headcount cuts – or at least, not first from headcount cuts. There are smart, human, and in many cases more durable ways to realize those efficiencies. Ways that don't burn down the culture to save the budget. Ways that actually build the organizational capability you're going to need to make AI transformation work in the first place.
Here are ten things that might be worth trying before you reach for the RIF.
7 Alternatives to Layoffs to Consider
Alternatives to Layoffs #1. Slow-Roll the Backfill and Let Attrition Work for You
A few months ago, one of my team members left. My first instinct – and probably yours too – was backfilling. That's the reflex. The seat is warm, the work is real, you post the role.
For reasons outside my control, there was a delay. And wow, did I learn something. I didn’t actually need that headcount!
The work got absorbed –distributed across a team that, with a bit of AI augmentation in the mix, had more capacity than any of us had really noticed. We'd been reflexively filling seats without ever checking whether we actually needed them filled. I gave the headcount away. The work goes on. And the company benefits.
It reminded me of something I used to do when my daughter was small. We lived in a tiny apartment – her bedroom was barely big enough for her bunkbed, the top level of which doubled as our attic. She's an only grandchild, which meant a serious space-to-toys imbalance. But I couldn't bear to throw away things she might still love. So, I developed a system: bag up the toys I suspected she'd outgrown, label the bag, put it in the closet. If she didn't ask for any of it in six months, it was safe to donate.
She never once missed what she never once remembered.
Roles can be like that. You don't always know what you actually need until you've lived without it for a while.
The data supports a more patient approach here than most organizations allow themselves. Knowledge worker attrition, depending on the sector, runs between 10 and 15 percent annually. A managed, intentional hiring pause – not a panicked freeze, but a deliberate let's see what we actually need – can achieve meaningful workforce rightsizing over 12 to 18 months without a single involuntary departure, and without the trust damage, survivor guilt, and talent flight that follow a RIF. The discipline required isn't cutting. It's resisting the deeply ingrained institutional impulse to refill every seat the moment it empties.
Alternatives to Layoffs #2. Make Every Job Requisition Earn Its Place
In addition to the slow roll, this is a technique for HR teams to consider. Before a manager can post a new req, stop. They may need the help, but ask them to think a little harder about the role itself. What is changing?
I think every hiring manager opening a requisition should be required to rewrite their job description from scratch – not a cosmetic refresh of whatever was in the system the last three times someone filled this role, but a genuine rethinking of it through the lens of how work is actually changing.
What tasks in this role will AI handle in the next 18 months? What does the human bring to this seat that a well-prompted model genuinely cannot? What does the ideal human-AI partnership actually look like here, and are we hiring for the human half of it?
This sounds like extra process, and it is. That's the point.
Most organizations have discovered that simply adding deliberate gates to the hiring pipeline required second-order justification, an explicit conversation about whether this is a net-new add, or an opportunity to reshape – reduces unnecessary headcount by somewhere between 15 and 20 percent without any mandate and without anyone feeling cut. Leaders who are forced to articulate why a human is the right solution for a given problem often discover, in the act of articulating it, that they're not entirely sure.
There's one more thing I'd add to the gate: before a role gets approved, ask the hiring manager to look at the recognition data for the team they're hiring into. What skills are being recognized? What's visibly missing? What's being carried entirely by one person who will become a single point of failure if they leave? Your recognition feed is already a real-time, peer-witnessed team skills map.
Most hiring managers have never thought to consult recognition before writing a job description. They should.
Alternatives to Layoffs #3. This Isn't a Jobpocalypse — Spot the Roles That Are Forming
I want to make the historical case for a moment, because I think it matters enormously for how HR leaders frame this internally when they're being pressured to cut.
MIT economist Daron Acemoglu and Boston University's Pascual Restrepo have spent years studyingOpens in a new tab what they call the "displacement effect" versus the "reinstatement effect" of technological change. Their framework is worth knowing: automation shifts work away from human labor, yes – but those effects are counterbalanced by the creation of entirely new tasks in which human labor has a comparative advantage. New technology doesn't just eliminate jobs. It creates new categories of them.
The canonical example, and one I find myself returning to a lot lately, is the telegraph operator. Telephonists and telegraph operators thrived for roughly a century – their numbers rose dramatically across that period – until automated switchboards and eventually mobile telephony arrived and shrank the sector to near-nothing.
Sounds like a jobpocalypse, right? (If you were really attached to the telegraph, I guess it was.)
But where a machine replaces a human, the longer arc consistently bends toward economic growth and rising employment, in sectors and roles that didn't exist before the disruption.
The crucial caveat from Acemoglu's more recent workOpens in a new tab is that it isn't automatic and needs to be sheperded. "There is nothing that says technology is all bad for workers," he's written. "It is the choice we make about the direction to develop technology that is critical."
The same is true at the organizational level. The new roles don't appear by themselves. They need someone watching for them – someone willing to name what's forming before it has a title. And as the “People People,” that someone is you.
You’re not on your own. If you have a strong recognition program, you can leverage it here as a powerful workforce intelligence tool. Tag ‘AI transformation’ as a Topic in Workhuman’s recognition platform, for example, and then simply watch the feed, you'll start to see people being recognized for things that don't have job titles yet.
These are proto-roles. They're the future org chart assembling itself in plain sight – but only if you're looking, and only if the culture is recognizing and rewarding that kind of pioneering behavior explicitly enough to make it visible.
The data is really striking on this point: our research shows that people who are recognized for innovation are more likely to be recognized for innovation again. And people frequently recognized by patent award winners are 9.5x more likely to earn patents themselves.
Recognition records a culture of transformation. It also creates it.
Alternatives to Layoffs #4. Redeploy Before You Reduce — Leverage Your Internal Talent Marketplace
I've been spending time lately with the data from our forthcoming 2026 Humans at Work Barometer, and it’s not a spoiler to say that employees, overwhelmingly, want to stay and grow in place.
They're not looking for the door. They're looking for a leader who will create the conditions for them to become something more than they currently are – through lateral moves, stretch assignments, new challenges in a familiar context.
So before you search externally for the skills the AI era requires, look inside. Seriously look – not at the org chart, not at job titles, not at who's been here the longest. Look at the peer-witnessed, real-time evidence of what your people are actually doing and who is stepping up.
Most organizations have a significant hidden talent problem, and it's not the kind you'd expect.
The problem isn't that the talent isn't there. It's that they can't see it.
This is another place recognition data is invaluable. Résumés are what people say about themselves. Performance reviews are what managers say about people, once a year, under time pressure and survivorship bias.
Recognition is what peers say about each other, in the moment, as work happens – and it's an entirely different and more complete picture. You can see who your emerging leaders are, where skills are concentrating, and who is already operating well beyond the bounds of their job description and waiting to be given room to prove it.
Which means you're not just finding people for roles – you're finding the right people for roles, which is a different and more valuable thing entirely.
Alternatives to Layoffs #5. Make Reskilling More Visible, Rewarded, and Recognized
When employees develop new skills, what do you think is the most common response from their company?
This is another spoiler alert from our forthcoming Barometer data, but one I have to preview here because it is so counter intuitive.
In a world where companies are increasingly calling themselves “Skills-based organizations,” where we are doing “skills hiring” and we all acknowledge the need for reskilling and upskilling to see us through this huge groundshift in work…
The most common response to people expanding their skills is: to give them more work.
Not a promotion. Not additional compensation. Not even a public acknowledgment. Just more work. And for individual contributors – the people on the front lines of whatever AI transformation you're trying to run – the most common response is nothing at all.
Think about that.
If you are asking your workforce to reinvent how they work – to learn new tools, develop new capabilities, take on unfamiliar tasks – and your answer to "what do I get for doing that?" is more responsibility and nothing else, you have a big problem brewing.
You're treating your most adaptable employees as a renewable resource rather than a strategic investment, and I’m afraid they know it.
The fix is both simpler and harder than it sounds. You have to recognize and reward reskilling – explicitly, visibly, in the same channels where you recognize everything else. That means more work, but the promotions that go with it. It also means just acknowledging and thanking employees for taking the steps to help your organization see those gains it’s looking for. Recognition creates culture, and culture creates behavior. If people see their colleagues being genuinely celebrated for developing new capabilities and diving into AI transformation, that behavior proliferates. If they see it ignored, they'll rationally conclude it isn't worth the effort.
The neuroscience here is really clear: every recognition and reward experience is targeted reinforcement. It influences individual and collective behavior. It isn't soft. It's brain science. Done well and done publicly, recognition of reskilling does three things at once: it rewards the individual, it teaches the team, and it signals to the whole organization what the company actually values.
Further Reading: Upskill or Stand Still: AI Isn't Going to Wait for You
Alternatives to Layoffs #6. Ask Before You Assume — Lean in on Flexibility and Investment
Here's a thought experiment. If AI genuinely absorbs 20 percent of a role's output – and for many knowledge worker roles, that number is already conservative – why is the first conversation always a layoff instead of: would you like to work differently?
Voluntary reduced-hour arrangements, job sharing, compressed weeks – these options exist in most HR policy frameworks and are almost never actually offered. They carry a strange stigma, as if choosing to work 80 percent for 80 percent pay is somehow an admission of insufficiency rather than a reasonable human choice. But a lot of people, given a genuine and non-stigmatized option, would say yes. People with caregiving responsibilities. People managing health issues. People who would trade some income for time without a second thought. The math often works for companies. And the message it sends – that the organization considers the human being before it considers the org chart – is one that travels.
In a similar spirit: voluntary sabbaticals tied to a defined learning outcome do several things at once. They reduce near-term payroll cost without a permanent headcount decision. They give employees something meaningful and unusual – time, trust, and a signal that their development is worth investing in. And they build the capabilities you're going to need on the other side of this transition, delivered by people who already know your culture and context. Companies that have tried this – particularly in tech – often find it dramatically reduces attrition among their most stretched, highest-value people. The ones who haven't said anything yet but are quietly wondering whether they're building a future here or just running out the clock.
Both of these approaches – flexibility and sabbaticals – only work if the people who take them don't feel culturally sidelined in the process. If your reduced-hours employee quietly disappears from the recognition feed, stops being looped into the important projects, gets the message that they've opted out of visibility along with hours – the policy becomes a trap rather than a genuine choice. Recognition is what keeps people seen. It's what signals to the person on the arrangement, and to everyone watching, that contribution still counts regardless of how or how much someone works. Done right, it also makes the return from a sabbatical something worth celebrating publicly – naming what the person built, what they're bringing back, why it matters.
That message reverberates far beyond the individual.
Alternatives to Layoffs #7. Stop Making Workforce Decisions From a Stale Map
Most workforce decisions are made from a map drawn years ago. Org charts, job titles, headcount by department all tell you what work was supposed to look like when someone drew the boxes. They tell you almost nothing about how work is actually getting done right now, who is carrying what, and what it's becoming.
This gap has always existed. But AI transformation is widening it fast. Tasks that used to require a full-time role are being handled in a few hours. Cross-functional collaboration is happening in ways the org chart never anticipated. Managers who were supposed to be managing are doing individual contributor work because their job descriptions haven't caught up. And here's the uncomfortable irony: according to a 2025 MIT studyOpens in a new tab, a $30-40 billion annual investment into GenAI is showing zero P&L impact for 95% of organizations.
The study's conclusion? The problem isn't the AI. It's brittle workflows, lack of contextual learning, and misalignment with how work actually happens day to day.
In other words, companies are trying to fit AI into an old map of work — and failing.
The solution isn't more dashboards. As our own Chief Human Experience Officer KeyAnna Schmiedl puts it: "Dashboards are a great rear-view mirror. But I want foglights — live, people-driven signals that cut through the mist and reveal skills, influence, and risk so managers can coach, recognize, and act before the moment is gone."
Recognition is exactly those foglights. When you look at who is recognizing whom, for what, across which teams and initiatives, you can see the actual network of how work flows and move people to where they need to be. Across and up, not out. That's the territory, not the map.
Before you decide what to cut, be sure you have the signals to understand what you actually have. It may surprise you.
Further Reading: How Work Gets Done (Now): Rearchitecting People Data as Signals for the Modern Workplace
The Choice That Defines This Moment for HR
The new world is struggling to be born. And the monsters aren't only in the boardroom, or in the employees who resist.
They're in the gap – between what we know AI can do, and what we haven't yet figured out how to do with the humans alongside it. That gap is where most organizations are living right now. It's uncomfortable. It's genuinely uncertain. And it creates real pressure to do something that looks decisive, even when decisive is the wrong gear for the road.
We're not saying any of this is simple.
But we are saying if you and your team explore these solutions before RIFs, something else may become possible.
You become the kind of organization that could make a public commitment to its people: we will not use AI efficiency as a reason to cut headcount, as long as employees engage with us in building what comes next. A handful of companies have made pledges like this, and the trust and loyalty they've generated is real.
HR might be being asked to cut headcount, but it's job in this moment is to steward a transition. To make sure that when the new world finally arrives, it still has people at the center of it.
Acemoglu's conclusion, after all those years studying what technology does to workers, is that it’s not all doom and gloomOpens in a new tab. "There is nothing that says technology is all bad for workers," he has said. "It is the choice we make about the direction to develop technology that is critical."
The old world is dying. That part is true. But what the new one looks like, and whether the humans who built your organization get to be part of what it becomes – that part is still a choice.
Let’s make it a good one.
About the author
Darcy Jacobsen
Darcy is a passionate storyteller and champion of workforce transformation, human connection, and recognition-driven culture. As an author on the Workhuman Live Blog, she loves to connect deep research insights with modern workplace dynamics to uncover what really drives engagement, belonging, and happiness at work. With a background in communications and a master's in medieval history, she brings a unique perspective to her writing, taking deep dives into all topics around organizational psychology and the science of gratitude.