The AI Boomerang: Why Organizations Are Rehiring Humans, and What It Means for Group Coaching in Organizations

For the past few years, the story about AI and work has mostly moved in one direction: automate the task, cut the role, bank the savings. A new cover story from Korn Ferry suggests that the story is more complicated than many had assumed.

In Help Wanted: Humans (Korn Ferry Briefings Magazine, Issue 76, September 2026), Russell Pearlman describes what he calls a shocking reversal: organizations are quietly rehiring the people AI was supposed to replace. For L&D leaders, coaching leaders, and internal coaches, I believe this is a signal about which capabilities organizations need to develop next, and how.

The AI boomerang is real

The numbers in the article are striking. A 2026 survey of 2,000 hiring managers by Robert Half found that 32% had eliminated a role primarily because of AI, only to rehire someone for the same or a similar position. A 2025 survey by software firm Orgvue found that 39% of business leaders had made employees redundant as a result of deploying AI, and 55% of those leaders said some of those decisions turned out to be wrong.

Aaron Strout, author of Wired for Purpose: Why Humanity Is the Biggest Differentiator in a Digital World, calls this "the AI boomerang effect." In one case he cites, for every dollar a company saved by laying off 350 employees, it paid $1.27 to rehire them.

The article offers a simple example. When a copywriter left Cubic Promote, CEO Charles Liu let AI do the work instead. The drafts came fast, but every piece still needed to be edited, fact-checked, formatted, and prepared before anyone could use it. Liu ended up hiring someone to manage, improve, and complete the work AI started.

Pearlman points to two main causes. First, AI got more expensive, with major platforms raising prices by 20% to 40%. Second, and more important, leaders overestimated how much work AI could actually do.

What AI still can't do

According to the article, AI performs well on drafting, data analysis, and processing. Give it a situation that requires judgment, negotiation, or relationship building, and it sputters. Korn Ferry's own scoreboard puts it plainly: in marketing, AI is better at drafting presentations and analyzing market research, while humans are better at understanding client sentiment and building client relationships.

Petr Chocholka of the Korn Ferry Institute explains that people still prefer to speak to another human in certain moments, because trust, familiarity, and accountability feel different when a person is involved. Bryan Ackermann, Korn Ferry's head of AI strategy and transformation, sums up where we are: "We're getting our first experience, at scale, of what AI can and can't do."

This is a development question

In my opinion, the most concerning part for talent leaders is that the article notes that many companies stopped hiring entry-level employees, assuming AI agents could handle the basic tasks young professionals usually learn through. Yet the article also observes that even junior employees often outperform AI in situations that call for judgment and relationships.

Those human capabilities are built through practice, feedback, reflection, and relationships. If organizations are rediscovering that humans are essential, they also need a way to grow the skills that make humans essential, at scale.

Korn Ferry's experts recommend four adjustments for balancing AI and people:

• Redesign roles with AI in mind, freeing people for higher-value tasks
• Never let AI-created work go out the door without human review
• Use AI first on "invisible" tasks that require minimal human interaction
• Give people freedom to experiment, and share best practices across the organization

Each of these is, at its core, a human behavior change challenge and that is where group coaching programs come in.

Where group coaching in organizations fits

1. A structured space to redesign roles together

Redesigning a role happens when people make sense of what their work now looks like. A cohort of managers can explore which parts of their role AI can take over, what they will do with the time it frees up, and how to lead teams through the shift. Hearing how peers in other functions are answering the same questions widens everyone's view.

2. Building the judgment to check AI's work

"Keep a human in the loop" only works if that human has the confidence and discernment to question an output. In our view, this is a judgment skill, and judgment grows through reflection. Group coaching invites participants to examine real decisions, surface assumptions, and hear how others would approach the same situation.

3. Practicing trust and relationship skills

If trust, familiarity, and accountability are what humans uniquely bring, then those are the capabilities to invest in. In group coaching, participants practice them in each and every session, and in-between too: listening deeply, asking powerful questions, offering perspective, and holding each other accountable. They also learn coaching skills they take back to their teams, which reinforces a coaching culture across the organization.

4. Turning experimentation into shared learning

Korn Ferry encourages leaders to reward experimentation and share best practices across the organization. A cross-functional group coaching cohort is a natural vehicle for this. Participants bring what they tried with AI, what worked, and what didn't, and the group turns individual experiments into collective learning.

Getting the balance right

The article notes that experts say firms realize within six to 18 months of a full AI rollout whether they got the AI/human balance right. That feels like a pretty long time to wait for an answer. Leaders really need to notice earlier when the balance is off.

Group coaching programs offer exactly that rhythm. In Group Coaching HQ's 2026 landscape study, active programs commonly converge around cohorts of 5 to 8 participants meeting monthly for 90 minutes over four to six months. That cadence fits well within the window when AI decisions are being tested, adjusted, and, sometimes, reversed.

If you are making the case internally, here is where we suggest starting:

• Choose a population at the center of AI change. New managers, leaders driving AI adoption, and teams navigating restructuring are strong candidates.
• Anchor sessions in real work. Participants will bring live challenges, not hypothetical ones.
• Invest in trained group coaches. Holding psychological safety, managing group dynamics, and inviting challenge requires specific skills that differ from 1:1 coaching or workshop facilitation.
• Measure what matters. Track behavior change, application on the job, engagement, and retention signals, alongside stories of impact.

The human advantage is a development strategy

One of our clients summed it up perfectly. As part of their leadership development strategy, they hold a year-long program for a chosen group of leaders. Many of them are leading change and supporting their team members through AI adoption. “We need the humans to speak to the humans!”.

I really think that the organizations that thrive will be the ones that stop treating AI and people as an either/or decision and start deliberately developing the human capabilities that AI makes more valuable. Group coaching in organizations is one of the most scalable, relational ways to do exactly that.

How is your organization balancing AI and human development? We would love to hear what you are seeing.

Sources

Pearlman, R. (2026). Help Wanted: Humans. Korn Ferry Briefings Magazine, Issue 76.

Robert Half survey of US hiring managers, as reported in AI Layoffs Backfire as 32% of Bosses Rehire Roles They Thought Robots Could Do, International Business Times UK (2026).

Orgvue (2025) survey of business leaders, as cited in Pearlman (2026).

Group Coaching HQ. Group Coaching in Organizations Landscape Study Report 2026.

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