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Key Takeaways
- Layoffs may reduce costs quickly, but companies that simply rehire into the same org chart risk recreating the inefficiencies that created the crisis in the first place.
- Rebuilding successfully requires real-time workforce data and managers equipped to make better hiring, compensation, promotion and team-design decisions.
AI-related layoffs tend to generate headlines, and they’re rarely flattering.
Just ask Amazon, which drew fire for eliminating thousands of corporate positions while doubling down on generative AI investments. Or Klarna, which was skewered for firing 700 customer support agents, only to hire them back when AI proved unready to fill the void.
Behind the headlines, though, the picture is more complicated.
Slashing jobs has a human cost and is never pleasant. But the reality is that companies rarely make these deep cuts on a whim. Often, they’re the board’s response to soaring burn rates or existential threats to the business. Think of it as corporate shock therapy: painful, disruptive and intended to stabilize the patient.
For companies in the throes of such a crisis, the most important — and often overlooked — step is what comes next. How can they rebuild better?
A business-as-usual approach to rehiring risks repeating the same boom-and-bust cycle. Instead, companies need to use the disruption as an opportunity to rethink how work gets done.
A blueprint for rebuilding better
First, it’s worth remembering that even amid the AI transformation, layoffs needn’t be inevitable.
Ideally, organizations practice continuous strategic workforce planning to stay healthy and agile. For comparison, by eating well, taking vitamins and exercising regularly, someone can avoid ending up in the ER. Likewise, businesses that constantly reassess their workforce needs can course-correct before overhiring or misallocated talent becomes a crisis.
That means moving away from static annual headcounts and toward dynamic workforce intelligence, which gives leaders the holistic picture they need to align talent strategy with changing business conditions.
But when a company reaches the point where mass layoffs are necessary, recovery requires more than simply rehiring into the old org chart. That’s especially true in the age of AI, which is rapidly changing the nature of work, including which roles are still needed and which aren’t.
Here are three steps companies can take to rebuild their workforce stronger than before.
Step 1: Understand your workforce today
For companies that want to rebuild, the first step is getting a detailed picture of their people and how they impact business outcomes. This sounds like it should be table stakes, but rarely is.
At many organizations, for instance, overlapping responsibilities hide in plain sight. Take “enablement,” the support teams that now exist inside most departments. Sales, marketing and customer success often each run their own version of enablement, covering largely the same ground.
Here, AI can actually help. Where headcount was formerly buried across separate HR, finance and business-unit spreadsheets, new AI-powered tools unify and standardize data. Suddenly, those three enablement teams sit side by side, and the overlap is obvious.
The same visibility that surfaces a redundant enablement team can also connect people and initiatives to business outcomes like sales and customer retention. Which teams should we consolidate? Where will headcount investment do the most good? By connecting people with impact, what used to be guesswork becomes a calculation.
Step 2: Plan for tomorrow’s workforce
Once a company has a clear, detailed picture of its workforce today, it can start redesigning how work gets done. Doing this right requires more than merely projecting how many people are needed for which roles. Right now, it demands a wholesale re-evaluation of work, rethinking the nature of roles, teams, and even outcomes.
That’s because AI chips away at individual tasks rather than erasing entire jobs. So the unit of analysis has to shrink from job title to task: sorting out which parts of a role lean on human judgment, empathy, creativity, or relationships, and which can be supported or replaced by a machine.
Redesigning work also means rethinking span of control. A manager who once had four or five direct reports may be able to oversee a much larger team, once the company knows which tasks AI can handle or support.
Designing this kind of future workforce goes beyond the limits of annual planning exercises and human resources business partners (HRBPs). It requires continuous modeling and scenario planning.
Here, too, AI is starting to fill the gap. AI-powered platforms now enable leaders to stand up several different versions of the org side by side. What happens to cost and skills coverage if a manager’s span of control moves from 1:5 to 1:20, or a layer gets flattened? Insights that used to take analysts weeks can now be surfaced in minutes.
Real-time planning means that as hiring and attrition shift from week to week, projections stay current, automatically keeping headcount and budget in sync.
Step 3: Activate your managers to execute
Having a workforce plan is one thing. But you need frontline managers to put it into action. For companies hoping to rebuild stronger, closing the “last-mile” gap is critical.
Most managers, for instance, are still flying blind, with no clear view of their team or how it impacts the company. What’s missing is real-time intel: who’s a flight risk, who’s ready for promotion, and what an unfilled role is costing the team.
AI holds promise to bridge that gap, but with a caveat: even the best tools are useless without deeper context.
AI that just knows the title, tenure, and last year’s review score will miss the employee who carried their entire team through a rough quarter. Real context pulls in signals from wherever the work happens, like sales pipelines, project timelines, IT tickets and delivery metrics, so it can tell a low performer from someone who’s stretched thin.
Today’s managers face another challenge in reengineering teams and rebuilding talent: time. I see companies now expecting each manager to oversee 10 people instead of five, for instance. The workload can easily become overwhelming.
Take compensation discussions and merit reviews. Promotions and raises are still generally given based on a combination of rough HR guidelines, anecdote, and instinct. Putting in the time to truly crunch the numbers and assess performance can take weeks.
The better approach: leverage agentic AI to equip managers with the background they need to make effective decisions in minutes, not weeks. The right programs can offer detailed comp recommendations based on everything from performance and flight risk to pay equity and other factors.
Anyone can cut jobs. Rebuilding is the hard part
Layoffs can be a useful wake-up call, the jolt that keeps a company from boiling like the proverbial frog. Cutting headcount is only half the job, though.
Businesses that slash their workforce and don’t hire back might think they’re pulling off a lean transformation. But without a data-driven plan to rebuild, they risk hastening their own decline. In the AI era, the companies that thrive will be the ones that redesign work the smartest.
Key Takeaways
- Layoffs may reduce costs quickly, but companies that simply rehire into the same org chart risk recreating the inefficiencies that created the crisis in the first place.
- Rebuilding successfully requires real-time workforce data and managers equipped to make better hiring, compensation, promotion and team-design decisions.
AI-related layoffs tend to generate headlines, and they’re rarely flattering.
Just ask Amazon, which drew fire for eliminating thousands of corporate positions while doubling down on generative AI investments. Or Klarna, which was skewered for firing 700 customer support agents, only to hire them back when AI proved unready to fill the void.
Behind the headlines, though, the picture is more complicated.