The past year of the AI era looked like every gold rush: a surge of activity, tools and ambition at full throttle. But was it? The latest EY AI Pulse Survey polling 500 US senior leaders across a diverse range of industries shows the real value isn’t in the rush; it’s in what comes after. Ninety-six percent of AI-investing organizations now report AI-driven productivity gains over the past year, and more than half (57% ) are seeing significant AI-driven productivity gains. Those currently investing $10 million or more in AI are far more likely to see significant AI-driven productivity gain (71% vs. 52% for those investing less than $10 million), suggesting a link between scale and results. What separates leaders now is not the number of tools but the discipline of enterprise-wide integration. Successful businesses will move from isolated experiments to enterprise transformation, weaving AI into how the business runs and embedding responsibility from the jump. Everyone rushed into AI in the past few years. But now comes the real test: who can turn that frenzy into actual, lasting value?
The early promise of AI is no longer speculative. Across industries, organizations are reporting tangible results. Significant productivity gains, big improvements in finances, quality of operations, and greater innovation, are all leading to competitive advantage. It sounds like a vision of the AI-driven future from eager consultants — but it is now today’s reality for many organizations across sectors.
The real breakthrough isn’t automation—it’s amplification. Leading companies are using AI to scale human capacity at a pace we’ve never seen before, which is why executives are plowing productivity gains right back into more AI tools and more talented people.
Colm Sparks-Austin, EY Americas Technology Consulting Leader
In this AI gold rush, scale is the difference between striking luck and building legacy. Senior leaders at organizations currently investing $10 million or more in AI across all business units/teams (71%) are more likely than those investing less than $10 million (52%) to say their organization has seen significant AI-driven productivity gains over the past year.
Productivity gains are usually framed around what is removed: hours of tasks and money saved. For many managers, it’s easier to first drive AI adoption, which is crucial and easier to measure. We must challenge ourselves to consider what is added — the value-added activities, the innovation, the outcomes that were always discussed as a possibility off on the horizon that never seemed to arrive until now.
Dan Diasio, EY Global Consulting AI Leader
Senior leaders tell us that they are doubling down on AI investments, but their past predictions on spending from a year ago show gaps between ambitions and reality. Among senior leaders whose organizations are investing in AI, only about a quarter (24%) say that 25% or more of their total budget goes toward AI investments. Looking ahead to next year, twice as many (48%) anticipate 25% or more of their total budget going toward AI investments.
2024 predictions do not align with 2025 realities: While a year ago 65% of senior leaders whose organization is investing in AI expected their organization to invest at least $1 million into AI the following year, today only 58% say their organization actually does. A similar picture emerges among those investing $10 million or more: while a year ago 34% of senior leaders whose organization is investing in AI said their organization will spend $10 million or more on AI investments the following year, today only 23% actually do.
As noted, those organizations who are devoting more of their budgets to AI are reporting better results. For example, compared to last year, senior leaders whose organization is investing in AI and whose current budget for AI investments is 25% or more of their total budget say they are seeing a significant increase in positive ROI from their AI investments, particularly in product innovation (86% today vs. 76% last year). Strangely, or perhaps evidence of shifting priorities as their AI journey advances, few are seeing operational efficiencies compared to six months ago (77% today vs. 88% six months ago), although the overall rate remains high.
Leaders are signaling a deeper commitment to AI, but the divergence between forecasted and actual spend tells an important story: ambition is outpacing execution. As organizations move from pilots to scaled transformation, the winners will be those who pair their bold strategic business goals with their AI investment goals and go deep to reimagine processes and business models.
Traci Gusher, EY Americas AI and Data Leader
AI surfaces in many high-profile news articles about layoffs, perhaps raising expectations for executives to deliver the alleged productivity gains that other companies are achieving. AI can be a convenient mask for over-hiring during the “great resignation”, or headcount reductions could be serving as a short-term solution for funding significant tech expenditures. The true power of AI is not as a jobs-killer but as a strategic enabler that keeps humans — and their strengths — at the center and focuses more on growth than on AI replacing jobs. However, the pressure to deliver is enormous. Among senior leaders whose organization has seen AI-driven productivity gains over the past year, 88% say it is a key metric leaders at their organization are evaluated on, yet 65% say their organization struggles to tie certain productivity gains directly to adoption of the technology. And just as many (63%) at AI-investing organizations say other senior leaders at their organization do not always attribute productivity gains to AI. Metrics persist as a tripwire for managers. For senior leaders at AI-investing organizations, 92% openly agree that there needs to be more training on how to report on AI-driven productivity gains to show the value of AI. It’s another wrinkle demonstrating how managers need to reevaluate what they do and how they lead in the AI era, building off findings in the EY Agentic AI Workplace Survey. These showed that half of people managers doubt their ability to lead AI-augmented teams, and most expect management to become harder, not easier.
Building on trends from earlier waves of the EY AI Pulse Survey, this latest data shows a maturing commitment to responsible and transparent AI. Leaders are acting on the goals they set. Most organizations continue to invest in helping employees use AI responsibly, both now and in the future. Sixty percent of senior leaders whose organizations are investing in AI say the time spent on Responsible AI training for employees has increased over the past year, and about two-thirds (64%) expect that time spent on training employees on how to use AI responsibly will grow in the year ahead. This follow-through matches what senior leaders promised a year ago, when 59% said they would spend more time on Responsible AI training for employees — and they did.
That consistency extends beyond training. Organizations are strengthening their focus on the ethical operation of AI to unlock opportunities it introduces in business operations. Sixty-eight percent of senior leaders whose organizations are investing in AI say their organization’s focus on ensuring AI operates ethically will increase over the next year (up from 60% in a year ago), while 60% expect their focus to AI-related risks to rise as well (up from 51% a year ago). Transparency is also gaining ground. Compared to last year, even more leaders say their organization will increase transparency with customers about AI use in the year ahead (63%, up from 55%).
In contrast to other areas where ambition has outpaced actual investment, Responsible AI showed meaningful follow-through. Leaders are turning commitments into practice through deeper investment in training, governance, and transparency. That progress underscores how essential Responsible AI has become to scaling technology with confidence to preserve trust.
Kapish K Vanvaria, EY Global and Americas Risk Consulting Leader
As AI moves from experimentation to execution, leaders face a defining moment: translating massive potential into measurable impact. The AI race may feel like a gold rush — but the real value isn’t in the rush itself, it’s in building the systems that best target where to find the gold and stay committed to mining it.
The full report explores these questions with data and insights specific to your industry to guide where to focus next.