Half of UK CEOs credit AI with boosting productivity, yet lack ROI visibility

Half of chief executive officers in the United Kingdom attribute recent productivity improvements to artificial intelligence, according to a new report from Ernst & Young. These leaders rank AI higher than traditional efficiency measures such as process redesign or workforce reskilling, signaling a major shift in how organizations view technological adoption.

Despite this broad acknowledgment of AI’s impact, most executives struggle to quantify the financial benefits. The EY study reveals that only 14% of UK CEOs have complete real-time visibility into their AI costs. Consequently, one in three leaders cannot properly assess the return on investment, creating uncertainty about whether these tools are delivering tangible business value.

Visibility and Measurement Challenges

The disconnect between perceived productivity gains and measurable financial outcomes is a central theme in the report. Silvia Rindone, the UK and Ireland managing partner at EY, noted that CEOs now demand clear evidence that their investments are driving stronger productivity. This demand highlights a growing need for greater transparency across AI spending and its operational impacts.

Without precise data on costs and outputs, businesses find it difficult to link AI initiatives to revenue growth. The inability to assess ROI accurately means that many organizations are operating without a clear understanding of their strategic position. This lack of clarity complicates long-term planning and budget allocation for future technology projects.

Implementation Barriers and Skills Gaps

Beyond measurement issues, structural obstacles continue to hinder widespread AI adoption. The EY report identifies legacy systems as a major blocker for 34% of respondents. Organizational complexity is cited by 29% of leaders as another significant impediment, four years after generative AI entered the mainstream with the launch of ChatGPT.

Skills shortages present an even more pressing challenge. Three in four UK CEOs anticipate that talent gaps will worsen over the next three years. This expectation surpasses concerns about access to capital, suggesting that financial resources alone cannot resolve the difficulties associated with deploying advanced technologies. These persistent issues require disciplined execution and clear strategic choices to overcome.

What should you do?

Security and technology professionals should monitor how their organizations track AI-related expenditures and productivity metrics. Ensuring that leadership has access to accurate data can help bridge the gap between adoption and measurable value. Teams should also evaluate existing legacy systems for compatibility with new AI tools to reduce implementation friction.

Background: Generative AI

Generative AI creates content from prompts. Agentic AI performs actions using tools. The former outputs text or code; the latter changes system states. Understanding this distinction is critical for security architecture, as agentic systems introduce execution risks that pure generation models do not possess.

Read the full guide: Generative AI vs Agentic AI: Architectural Differences and Security Risks

What to do and how to stay safe: AI

• Audit current AI spending to establish baseline costs and improve visibility into operational expenses.
• Assess existing legacy infrastructure to identify compatibility issues that may hinder AI integration.
• Develop clear metrics for measuring AI-driven productivity gains to facilitate accurate ROI calculations.
• Review workforce skill sets to identify gaps that could impede future technology deployments.

Step-by-step guide: Prompt Injection Warning Signs: How to Spot AI Manipulation

General security guidance from the Threat Times newsroom. It is not confirmed advice from the organisations named in this story.

Frequently asked questions

How many UK CEOs credit AI with boosting productivity?

According to the EY report, 50% of UK CEOs have credited AI as one of the three biggest contributors to productivity improvements over the past year.

What is the main challenge in assessing AI ROI?

The primary challenge is a lack of visibility, with only 14% of CEOs having full real-time oversight of AI costs, making accurate ROI assessment difficult for one in three leaders.

What are the biggest barriers to AI adoption?

Legacy systems and organizational complexity are major blockers, while skills shortages are expected to worsen, affecting three in four UK CEOs over the next three years.