What Is Holding Up AI Adoption for Businesses? New EPAM Study Reveals Key Findings
From modernizing outdated technology to implementing responsible AI governance, report examines the key factors driving enterprise AI success in 2025 and beyond

The study reveals a notable disconnect between perception and reality in enterprise AI adoption among respondents from the
"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," said
Key findings from the report include:
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Acceleration of AI investments: Companies plan to increase their AI spending by 14% year-over-year in 2025, signalling a continued commitment to AI-driven growth.
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Scaling AI remains a challenge: While 30% of technology-advanced companies have successfully implemented AI at scale, many organizations struggle to bridge the gap between experimentation and enterprise-wide deployment.
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AI's direct impact on business: Disruptors attribute 53% of their expected 2025 profits to AI investments, which demonstrates a tangible financial impact for the market leaders.
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Governance and security trail AI growth: Businesses anticipate a minimum of 18 months to implement effective AI governance models, highlighting the complexity of aligning AI with the rapidly evolving regulatory landscape.
- AI talent remains a priority: 43% of all companies surveyed plan to hire AI-related roles throughout 2025, with machine learning engineers and AI researchers being the most in-demand positions.
"Improved productivity and operational efficiency are universal goals, but true transformation lies in bridging the gap between tech teams and the business," said
To realize the full potential of AI, the report highlights the importance of aligning people, data and technology to unlock real business value and identifies four critical areas for the successful adoption of AI:
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People, processes and culture: Effective AI implementation requires strong executive leadership that clearly articulates priorities and focus areas. In fact, the data reveals that 65% of disruptors understand the necessary skills for AI adoption.
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Business and technology modernization: While 31% of executives see outdated technology as a barrier to AI adoption, the real challenge is the lack of alignment between business and technical teams. Once a clear organizational purpose is established and communicated, engineering teams can then map out a modernization strategy.
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Security: Security remains a universal priority for senior executives and engineering teams, particularly regarding data protection, data quality and cloud security, with 35% of businesses saying their top challenge to achieving modernization is their lack of sophisticated security programs.
- Governance and responsible AI: While 75% of advanced companies claim to have established clear AI strategies, only 4% of disruptors say they have developed comprehensive governance frameworks even with the understanding that effective governance is typically 18 months away.
According to Forrester, in its Predictions 2025: Artificial Intelligence report, 2025 will bring a renewed focus on strategy, deepened partnerships between business and IT, a pivot back to predictive AI, and new technologies and architectures as enterprises govern data and AI together.
"In 2023, the race to harness AI saw many experimenting, but a select group of pioneers emerged, transforming bold ideas into scalable realities," said Nir Kaldero, Chief
The report concludes that organizations must now align AI with their business objectives rather than adapting business goals to fit AI capabilities. Success in this new phase requires companies to evolve beyond implementing AI solely for productivity gains and operational efficiencies. To gain a competitive advantage, forward-thinking enterprises must leverage AI strategically across their entire value chain to drive revenue growth and enhance customer experience.
The full report includes detailed insights and practical recommendations for enterprises at different stages of their AI journey.
To read the full 2025 Artificial Intelligence Report, visit: www.epam.com/ai-report-2025.
Methodology
The data published in this report is based on a survey of 7,300 respondents from enterprises with headcounts of 10,000+ evenly split across the C-Suite and Vice President level as well as engineers and developers spanning nine countries (the
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Forward-Looking Statements
This press release includes estimates and statements which may constitute forward-looking statements made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, the accuracy of which are necessarily subject to risks, uncertainties, and assumptions as to future events that may not prove to be accurate. Our estimates and forward-looking statements are mainly based on our current expectations and estimates of future events and trends, which affect or may affect our business and operations. These statements may include words such as "may," "will," "should," "believe," "expect," "anticipate," "intend," "plan," "estimate" or similar expressions. Those future events and trends may relate to, among other things, developments relating to the war in

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