EPAM: AI Gap Challenges Turned to Enterprise Success

A substantial disconnect exists between how enterprises perceive AI capabilities and actual implementation success, according to research by EPAM Systems.

The study, From Hype to Impact: How Enterprises Can Unlock Real Business Value with AI, surveyed 7,300 participants across nine countries and eight industries.

It found that while 49% of respondents rated their companies as “advanced” in AI implementation, only 26% of those self-identified leaders have successfully delivered AI use cases to market.

This delivery gap highlights the challenges organisations face in moving from experimentation to practical applications that generate measurable returns on investment.

“Following the release of ChatGPT and throughout 2023 and 2024, we witnessed companies across industries experiment with AI and develop proofs of concept, primarily targeting immediate gains in productivity improvements and operational efficiencies,” says Elaina Shekhter, Chief Marketing and Strategy Officer at EPAM.

“This new research clearly shows that we're now entering a new phase where success depends on identifying high-value use cases and prioritising them strategically to achieve broad organisational impact.”

Investment trends for enterprise AI adoption

EPAM reveals that companies plan to increase AI spending by 14% year-over-year in 2025, demonstrating continued commitment to AI-driven initiatives despite implementation challenges.

For organisations at the forefront of AI adoption – which EPAM classifies as “disruptors” in its research – the financial stakes are significant.

These market leaders attribute 53% of their expected 2025 profits to AI investments, demonstrating a quantifiable impact on their financial performance.

Meanwhile, the labour market continues to reflect growing AI demand, with 43% of surveyed companies planning to hire for AI-related roles throughout 2025.

Machine learning engineers and AI researchers also represent the most sought-after positions, highlighting the continued need for specialised technical expertise.

Dmitry Tovpeko, Vice President of Engineering at EPAM, says: “Improved productivity and operational efficiency are universal goals, but true transformation lies in bridging the gap between tech teams and the business.

“As AI reshapes the enterprise, developers are evolving from task-oriented users to strategic experts, responsibly harnessing AI for end-to-end scenarios.

“Success hinges not on tech stacks or cloud infrastructure, but on aligning tech teams with business objectives to solve real-world customer problems.”

Governance frameworks as significant enterprise obstacle

EPAM highlights governance as a particular challenge for organisations implementing AI at scale.

While 75% of advanced companies claim to have established clear AI strategies, only 4% of disruptors report having developed comprehensive governance frameworks.

This governance gap exists despite recognition of its importance, with businesses anticipating a minimum of 18 months to implement effective AI governance models.

This timeline reflects the complexity of aligning AI practices with rapidly evolving regulatory requirements across different markets.

Furthermore, technology modernisation represents another barrier to AI adoption, with 31% of executives identifying outdated technology infrastructure as an impediment.

However, EPAM's analysis suggests the core issue lies in the alignment between business objectives and technical implementation rather than purely technical limitations.

Security concerns also persist across organisations implementing AI, with 35% of businesses citing their lack of sophisticated security programmes as their primary modernisation challenge.

These concerns encompass data protection, data quality and cloud security.

The research additionally examined organisational readiness factors, finding that 65% of disruptors understand the necessary skills for AI adoption, highlighting the importance of talent strategy in successful implementation.

Nir Kaldero, Chief AI Officer at EPAM NEORIS, a digital transformation consultancy acquired by EPAM, says: “The next phase of AI is not just experimentation but deployment at scale – focusing on enterprise-wide, high-impact use cases while continuing the effort to align people and culture, data and cloud and new processes to unlock true exponential business value.”

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