Artificial intelligence is no longer just an experiment inside the enterprise, it’s becoming the backbone of how work gets done. As technology leaders navigate tighter budgets and growing performance pressure, AI is reshaping workforce strategy in profound ways. ETR’s Fall 2025 Macro Views Survey found that 72% of leaders now view AI as a key driver of workforce productivity, while one in four (25%) are already using it to limit future headcount growth. In this second installment of ETR’s Fall Macro Views Series, we explore how the evolution of AI, from pilot projects to operational necessity, is redefining the balance between innovation, efficiency, and talent across global enterprises.

From Curiosity to Core Strategy

In April, more than half (51%) of enterprise leaders described their AI approach as “measured,” balancing adoption with regulatory and privacy caution. Six months later, that caution has given way to confidence. AI is now embedded in how companies manage operations, develop software, and deliver value.

“I think the conversation around AI has evolved to the point where AI is now more of a tool that we have to factor into our normal strategy,” said one CIO during ETR’s Macro Views panel. “It’s a pretty powerful tool, but it’s really caused us to focus more energy and effort on where we can find efficiencies, and where we can find better ways to support our customers through this very strange time that we find ourselves in.”

This shift reflects how enterprise leaders now view AI as fundamental to their resilience strategy—something that improves output and adaptability, not just automation.

The Build vs. Buy Divide

Our findings reveals a clear split in AI deployment strategies. Enterprises are evenly divided between those who build custom models (29%) and those who use vendor-embedded AI (29%), while another 21% balance both approaches.

In data engineering, organizations lean toward direct model use (31%), valuing control and flexibility, while in security, most rely on embedded vendor offerings (36%) for consistency and compliance.

The trade-offs are familiar: building allows for competitive differentiation and data sovereignty, but buying accelerates time to value and reduces maintenance costs. Yet the most sophisticated firms blend both.

ROI Still Forming, but the Picture Is Clearer

Despite rapid progress, only 13% of enterprises report measurable ROI at scale from in-house AI initiatives. However, that number rises to 19% among Fortune 100 firms, suggesting that scale, data maturity, and in-house capabilities are crucial for success.

For Global 2000 enterprises, developing in-house models appears to deliver higher ROI than relying solely on vendors—17% versus 11% reporting measurable results at scale. That reflects both technical depth and long-term control: internal models build institutional knowledge, while vendor tools often remain black boxes.

Panel Perspective: The Human Equation

In ETR’s latest Macro Views Data Feedback Panel, technology leaders discussed AI’s impact on people as much as on process.

“We don’t see gen AI as a replacement, we see it as a supplement,” said a global CISO during a Macro Views Panel. "It’s in addition that helps you do what you do on a daily basis. You can review things faster, you can get the executive summaries, and you can craft an e-mail much quicker. I didn’t go to the kind of cool things that AI is able to do from a day-to-day perspective. And of course, it depends on what business you’re in as well."

Others echoed that sentiment. A director of IT added, “...but I don’t think that we’re at a point where I can say that AI is simply going to just replace people. I think that AI is going to supplement what people actually do, and allow the remaining staff to do more with less.”

Still, the efficiencies are real. Larger enterprises, with more redundancy across departments, are leading the charge. Nearly 36% of Fortune 100 organizations report using AI to limit future headcount growth, almost double the enterprise average.

That balancing act—augmenting talent while trimming costs—is reshaping what “productivity” means inside the enterprise. AI-driven automation is now seen as a workforce multiplier, not just a headcount reducer.

The Next Imperative: Governance and Trust

The path to 2026 will hinge on how effectively organizations operationalize governance and trust frameworks. Enterprises are under increasing regulatory scrutiny as generative AI scales across workflows, from customer engagement to employee support.

To stay ahead, leading firms are defining internal AI usage policies, tightening model monitoring, and centralizing oversight under data ethics committees. The goal is not just compliance; it’s confidence. As trust frameworks mature, the same organizations that invested early in governance are the ones unlocking sustainable ROI.

What Comes Next

The enterprise AI story has moved beyond pilots and hype. It is now a question of how quickly organizations can industrialize AI responsibly, linking it directly to measurable outcomes in productivity, workforce strategy, and innovation.

The lesson from ETR’s 2025 Macro Views data is clear: AI’s biggest disruption isn’t job loss—it’s job redesign.

Get deeper insights into how enterprise leaders are evolving AI strategies and workforce models.
Download the Fall 2025 Macro Views Survey Findings Summary to access the full report and watch the findings webinar.