Fifth wave of EY US AI Pulse Survey reveals the majority of senior leaders are reconsidering their approach due to token costs, and many are developing custom in-house software

NEW YORK, July 28, 2026 /PRNewswire/ — After years of prioritizing rapid AI adoption and widespread experimentation, senior executives are shifting their strategies. The latest research from EY reveals that senior leaders are pivoting to sharply balance cost against value, driven by mounting operational expenses and the rise of autonomous agentic workflows.

The new EY US AI Pulse Survey, the fifth in a series of polls of at least 500 US-employed decision-makers (senior vice presidents and above) from a broad range of sectors, uncovers the impacts of agentic vibe coding on organizations, with 82% of senior leaders whose organization is investing in AI saying their organization is concerned about AI token usage (units of data AI models use to process the amount of inputs and generate outputs) and related costs. Furthermore, an overwhelming 98% of those investing in AI and using tools that require AI tokens say AI token usage and related costs have caused their organization to reconsider their approach. Despite these concerns, only 64% of senior leaders whose organization is investing in AI report that their organization actively monitors AI token usage and has clear budgetary guardrails in place for how much they spend. 

“‘AI saves time’ is no longer a sufficient business case when the costs are mounting and difficult to ascertain over the long run,” said Dan Diasio, EY Global AI Consulting Leader. “Companies are showing signs of reckoning with setting priorities rather than merely driving adoption. And those priorities must be focused on doing different things, not the same things differently.”

Nonetheless, more organizations are hitting the accelerator than the brakes. Among senior leaders whose organization is investing in AI and using tools that require AI tokens, 37% say their organization’s AI token usage and related costs have caused their organization to reconsider the scope of their organization’s AI rollout by expanding it compared with 15% considering reducing it, while 29% are speeding up the pace of their organization’s AI rollout compared with the 15% that are slowing it down.

Disruption of Traditional SaaS & the Rise of Enterprise Vibe Coding
This fiscal consciousness is driving a shift away from commercial, off-the-shelf enterprise software solutions. In fact, about three-quarters (76%) of senior leaders whose organization is investing in AI say that “off-the-shelf” software solutions no longer meet their organization’s specific needs.

To de-risk their reliance on traditional enterprise software vendors, 91% of senior leaders whose organization is investing in AI say their organization views in-house, AI-built software development for internal organizational use as critical. This view is deeply embedded across the business landscape, with 87% of senior leaders whose organization is investing in AI saying they have either fully deployed or are piloting programs to develop in-house, AI-built software for internal organizational use. Acceleration is a primary driver, as 94% of these senior leaders state that AI enables their organization to build software faster than traditional development methods.

This migration toward custom applications signals severe headwinds for traditional enterprise software providers. Looking ahead five years, 95% of senior leaders whose organization is investing in AI project that their organization’s relationship with traditional software vendors will change, and 82% anticipate that the traditional enterprise per-seat Software-as-a-Service (SaaS) pricing model will become less relevant in their industry.

The AI Spending Reality Check
The push toward bespoke, in-house applications reflects a broader fiscal recalibration across the enterprise. Despite consecutive years of aggressive budget projections, actual enterprise AI spending has not matched projections, highlighting a disconnect between early hype and current fiscal reality. While last year 35% of senior leaders whose organizations are investing in AI anticipated spending $10 million or more on AI by this point, only 23% actually report spending at that level today. Similarly, while a year ago 18% planned to commit 50% or more of their total budget to AI by this point, only 3% have done so today.

Yet, despite AI spending falling short of initial projections, value realization remains remarkably high. Fully 98% of senior leaders whose organization is investing in AI say they have seen a positive return on investment (ROI) from their AI initiatives. On top of this, senior leaders at organizations that commit 25% or more of their total budget toward AI investments are more likely than those spending at lower levels to say their organization experienced significant positive ROI in cybersecurity (45% vs. 32%) and customer satisfaction (41% vs. 31%).

The Growing Mandate for AI Governance
The rapid expansion of internal AI development is creating urgent new demands for governance. As organizations push beyond experimentation and into large-scale deployment, leaders are recognizing that sustainable growth requires stronger financial controls, risk management, and accountability. In fact:

• 72% of senior leaders whose organization is investing in AI say their organization is facing challenges with in-house, AI-built software that is slowing progress, hitting a wall where cost, talent and trust intersect.
• Increased risk of shadow IT (34%) was cited as one of the top barriers when developing in-house, AI-built software for internal organizational use, closely accompanied by regulatory compliance and governance concerns (33%) and increased vulnerability/cybersecurity risks (32%) among other barriers.

Consequently, 93% of senior leaders whose organization is investing in AI say that organizations need to have the proper governance framework to safely allow employees to develop in-house, AI-built software for internal organizational use.

“Unlocking the value of AI at scale requires a robust governance framework which operates at machine speed in order to build internal confidence and stakeholder trust,” said George Haggar, EY Americas Risk Consulting Leader. “Those guardrails serve as a catalyst for organizations to safely accelerate, confidently reimagine their future and truly drive enterprise value.”

Methodology
EY US to Ernst & Young LLP (EY US) commissioned a third-party vendor to conduct the Fifth Wave of the EY AI Pulse Survey. The online survey was conducted among n=534 senior business leaders defined as US employed decision makers (SVP+) in the health, life sciences, energy, technology media and telecommunications (TMT), government and public sector, consumer products & retail, advanced manufacturing and mobility (AMM), financial services, private equity, and real estate, hospitality and construction (RHC) industries. This fifth wave was fielded between April 24 and May 17, 2026. The margin of error (MOE) at a 95% confidence interval for the total sample is +/- 4 percentage points.

The first wave of the EY US AI Pulse Survey was fielded April 29–May 6, 2024, the second wave was fielded September 24-October 4, 2024, the third wave was fielded April 17-30, 2025, and the fourth wave was fielded between September 19-October 16, 2025. For data integrity and comparison purposes, tracking questions and audience definitions remained unchanged wave over wave. The margin of error (MOE) for the total sample per wave is +/- 4 percentage points at the 95% confidence interval.

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SOURCE Ernst & Young LLP