Editorial
Recent headlines would have you believe that AI is decimating jobs at scale and accelerating a race to the bottom. And yet, when you look past the noise, a more complex and nuanced picture emerges.
According to EY’s latest AI Pulse Survey (Wave 4), among organizations investing in AI and experiencing AI-driven productivity gains, only 17% report that those gains led to reduced headcount. Most organizations are not using AI primarily as a blunt cost-cutting tool. They are reinvesting.
I recently interviewed Jonathan Sears, global technology leader for People Consulting at EY, to explore what this research signals for leaders navigating the current moment. Our conversation revealed that the real divide in today’s AI era is not between companies with more advanced technology, but between leaders who approach AI as a short-term efficiency lever and those who see it as a long-term engine for growth, capability and trust.
Table of Contents
- AI Is a Convenient Fall Guy
- Two Paths Emerge for Leaders
- Trust as the Enabler of AI Value
- AI Fluency Is Becoming Financial Fluency
- The CHRO’s Central Role
- A Test of Dignity When Layoffs Do Happen
- What Will Separate the Leaders Who Win
AI Is a Convenient Fall Guy
Many of the layoffs making headlines today are being framed as “AI-driven.” From my vantage point, that framing oversimplifies what is happening. A significant share of workforce reductions reflect broader forces like post-pandemic normalization, corrections resulting from ZIRP-era overhiring, shifts in capital markets, or changes in organizational priorities. AI becomes a convenient explanation because it feels inevitable and impersonal.
Sears did not speculate on those macro dynamics. Instead, he pointed back to the data. His message was straightforward: the evidence does not support the idea that AI is driving headcount reduction. EY’s survey shows that AI is far more often fueling reinvestment than reduction. Leaders are channeling productivity gains into expanding AI capabilities (42%), strengthening cybersecurity (41%), and upskilling and reskilling employees (38%).
That pattern directly challenges the dominant narrative. Rather than stripping organizations down, AI is being used to build them up (when leaders choose to do so). This distinction matters. AI may be the visible change agent, but leadership intent determines whether productivity gains are extracted or reinvested.
Two Paths Emerge for Leaders
The survey reveals a clear fork in the road. Only 17% of organizations reinvest AI-driven gains into headcount reduction. Far more direct those gains back into the business (technology, skills and resilience). That divergence reflects two fundamentally different leadership orientations.
The first is an extraction mindset: deploy AI to automate, shrink costs and harvest short-term savings. The second is a reinvestment mindset: use AI-driven productivity as fuel for growth, resilience and future capability. As Sears put it, the organizations that manage reinvestment well have strategic patience. They are willing to trade near-term savings for longer-term advantage.
Reinvestment is harder to explain and harder to defend in the short term. It requires leaders to justify why productivity gains are being redirected into training, new platforms or security rather than flowing straight to the bottom line. But this is where long-term advantage is built. Organizations that reinvest AI gains create momentum. They strengthen their talent base, modernize their operating model and expand their ability to absorb future waves of change. Organizations that extract gains too quickly often stall once the easiest efficiencies are exhausted.
This dynamic shows up repeatedly in large scale transformations, and AI is no different. The early gains are easy to measure. The compounding benefits only emerge when leaders resist the urge to cash out too early.
Trust as the Enabler of AI Value
The survey shows that as leaders invest in AI, they are placing growing emphasis on ethics, responsible AI training and transparency, i.e., the foundational behaviors that build organizational trust and support sustainable AI adoption. AI productivity gains do not automatically translate into sustained performance; they do so when employees believe that AI is being deployed with their interests in mind.
To that end, Sears emphasized that trust and transparency are foundational, particularly at a time when workers are inundated with alarming headlines. Leaders who remain vague about AI’s role or talk only in abstractions, inadvertently amplify anxiety. Employees fill those information vacuums with fear.
By contrast, leaders who clearly communicate where AI gains are going (e.g., into training, new capabilities, stronger security) reframe AI from a threat into an opportunity. Reinvestment is more than a financial act; it’s a strategic and cultural signal. In that sense, trust is a form of infrastructure, and without it, AI value leaks.
AI Fluency Is Becoming Financial Fluency
Another strong signal emerging from EY’s data is that AI is no longer an innovation metric. AI is creating tangible financial value that shows up on the P&L. Among respondents who report positive ROI from AI investments, 56% say those gains have already translated into significant, measurable improvements in overall financial performance. At the same time, in my own work, I'm seeing organizations are increasingly emphasizing AI fluency for senior leaders.
Sears described this as an inflection point where “AI fluency is becoming a core requirement for modern leadership.” Leaders will increasingly be assessed not on whether they “support AI,” but on whether they can:
- Translate AI into business performance.
- Measure outcomes credibly.
- Align technology, talent and capital allocation and
- Build and tap into the collective capabilities of human-AI teams.
AI fluency is fast becoming financial fluency. Executives who can move beyond automation toward genuine business reimagination will differentiate themselves and their organizations.
The CHRO’s Central Role
This evolution elevates the CHRO role in important ways. Sears described CHROs as central to keeping AI transformations grounded in people. They help establish guardrails for responsible AI in hiring, learning and workforce decisions. They shift planning away from static job models toward skills and career pathways. They ensure privacy, quality and fairness as genAI becomes embedded in HR processes.
Equally important, CHROs help translate AI productivity gains into tangible support for employees via training, feedback channels, and internal mobility. In doing so, they reinforce the message that AI is being used to expand opportunity.
A Test of Dignity When Layoffs Do Happen
While the data show that AI is not broadly driving headcount reduction, it would be disingenuous to suggest that displacement will never occur. Some roles will change faster than others, and some reductions will happen. This is where leadership choices matter most.
How an organization treats departing employees sends a powerful signal to those who remain. AI transformations depend on an engaged workforce, and engagement erodes quickly when people believe their colleagues are being treated as collateral damage. Workers watch closely. Fairness, transparency and respect are operational and ethical considerations. Organizations that preserve the humanity and dignity of those who are exiting are far more likely to maintain trust, commitment and momentum after the fact.
Sears echoed this orientation, noting that leading organizations see AI as a reshaper of jobs rather than a replacer of people and anchor transformation efforts in purpose.
What Will Separate the Leaders Who Win
The AI era is not dividing organizations solely on technological capability. It is separating leaders based on how they respond to the value AI creates. Some will extract; others will reinvest.
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The leaders who pull ahead will be those who take the harder path of reinvesting productivity gains, communicating clearly and building trust deliberately. They will recognize that AI creates possibility, but leadership determines whether that possibility turns into progress.
AI will shape the future of work. Leadership intent will decide who thrives in it.
Editor's Note: Catch up on other emerging trends in AI adoption below:
- How Internal Communications Helps Overcome AI Adoption Challenges — One of the biggest barriers to AI adoption has nothing to do with technology: it's poor internal communications.
- 3 Ways Companies Can Close the AI Gender Gap — AI is now a workplace requirement, yet women lag in use and confidence. Here’s how the AI gender gap slows adoption — and how to close it.
- Why Nobody Agrees on AI Productivity Metrics — As AI reshapes work, companies want new productivity metrics. The problem? Nobody can clearly define or fairly measure the alternatives.
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