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There’s no shortage of capital flowing into artificial intelligence right now. The latest and fourth EY US AI Pulse survey finds 23% of senior leaders whose organisations are investing in the technology say they’ve spent $10 million or more today (up from 16% just a year and a half ago) while 40% anticipate spending $10 million or more in the next year.
These numbers underline the growing sense of enthusiasm, investment, and urgency for AI, with the majority of companies surveyed also reporting a positive return on their investment. Yet at the same time, the scale of that return often remains modest or disjointed, leaving many business leaders asking the same fundamental question: Where is the big release of enterprise value?
Let’s start with where the impact is being seen. For all the buzz around generative AI and agentic systems, the most measurable benefits companies are reporting still come from traditional AI, mainly the machine learning models used to create recommender systems, anomaly detection, predictions, and beyond. These have been powering business operations for decades and continue to be an area worth investing in.
In some ways, this is good news. These investments are well understood and embedded and therefore easily maintained on the balance sheet. But at the same time, this should be a wake-up call for leaders. You are not behind because you haven’t fully deployed the latest iterations of AI but if you continue to wait, you soon will be.
Of course, it’s still important to innovate and the third EY US AI Pulse survey proves that companies aren’t starved for ideas. In fact, 86% of senior leaders report their organizations are currently using agentic AI for assisting/managing key processes, including (among other tasks) enhancing customer support and improving IT efficiency and cybersecurity.
However, what they often lack is intentionality and methodology. Many leaders admit that while AI pilot programs have spread into many corners of their enterprise, it’s rarely in a way that adds up to more than the sum of their parts. When AI use is scattered across departments or functions without coherence it limits business impact and it won’t unlock the next wave of competitive edge. Experimentation needs to give way to a serious, strategic approach.
My advice to leaders is not to view AI in a vacuum but as part of a lasting business strategy that drives transformation. When companies unlock value, it’s because they tie the technology directly to business outcomes in areas like improving operational efficiency, driving innovation, delivering enhanced customer benefits, and increasing market share.
They also ask the right questions:
The key is not getting stuck in the old approaches used for automation over the last decade. In these processes, companies focused on taking well-documented processes and ideating where automation could be interjected. This approach worked fine for the days of Robotic Process Automation but is outdated with the level of maturity in AI today.
Instead, companies need to embrace complete process reinvention. Forget the process you have today, focus on your inputs and your desired outcomes and build an entirely new AI-first process.
A chief operating officer and chief financial officer at a major U.S. food manufacturer recently told me that shifting their viewpoints toward an investor-driven, enterprise-led approach was a turning point for their organisation. They realised that although they weren’t missing out on hidden pools of value today, without a deliberate strategy, they would fail to make the next leap forward tomorrow.
This type of shift in strategy isn’t the product of a technical deep dive; it is the result of a business-first framework in which companies assess their market position, map AI opportunities against their value chain, and then focus on the two or three cross-functional areas in which the impact would be greatest.
This is where the next generation of AI solutions, whether generative, agentic, or physical, can truly make a difference. Not as isolated experiments, but as force multipliers aligned to key growth drivers and core sources of competitive advantage.
One more thing about our AI research: The results highlight a notable paradox. On one hand, senior business leaders are bullish about AI, determined not to miss the boat on its potential. On the other, they remain cautious about adoption.
This tension reflects both the promise and complexity of the moment. Leaders know AI is creating value. They overwhelmingly recognise that responsible, risk-mitigated use requires intrinsic human oversight and they plan to elevate reskilling and training programs to reflect that.
What they don’t yet have—but very much need—is a roadmap for scaling value as the technology moves forward. Of course, this starts with recognising AI as an unprecedented engine for reinvention. But it also means understanding that its deployment is not an enterprise outcome in itself.
At this undeniable inflexion point for every sector and industry, companies that double down on the business case (not the technology) and on humans (not machines) will lead.
Whitt Butler is EY Americas consulting vice chair.