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Top Barriers to AI ROI
Reasons why enterprise AI initiatives fail to deliver expected business value.
Primary Sources
Nearly 80% of Enterprises Say AI Is Held Back by Data Access Challenges ...
Cloudera’s Data Readiness Index reveals a growing “AI readiness illusion,” where widespread adoption outpaces the data foundations required to deliver real business impact. SANTA CLARA, Calif., - April 14, 2026: Cloudera, the only company bringing AI to data anywhere, today released its latest global survey, The Data Readiness Index: Understanding the Foundations for Successful AI, examining how prepared enterprises are to support AI at scale. Surveying nearly 1,300 global IT leaders, the report finds that while AI adoption is growing, most organizations still lack the data foundation needed for success. The findings highlight a striking paradox: while 96% of organizations report integrating AI into core business processes and 85% say they have a clear data strategy, nearly 4 out of 5 (~80%) admit their AI and data initiatives are still constrained by limited data access across environments. This gap highlights an emerging “AI readiness illusion”: the belief that organizations are prepared to scale AI even as critical data challenges remain unresolved. “Enterprises aren’t struggling to adopt AI, they’re struggling to operationalize it beyond experiments,” said Sergio Gago, Chief Technology Officer at Cloudera. “AI is only as effective as the data that fuels it. Without seamless access to all their data, organizations limit the accuracy, trust, and business value that AI can deliver.You can’t do AI without data.” AI Adoption is High, but ROI Remains Elusive AI is now embedded across the enterprise, but achieving consistent returns on investment remains difficult. When asked why AI initiatives fall short, respondents cited several key challenges: data quality (22%), cost overruns (16%), and poor integration into existing workflows (15%). These barriers highlight the ongoing complexity of translating AI investments into measurable business outcomes. Infrastructure limitations further compound the issue. Nearly three-quarters (73%) of respondents report that performance constraints have hindered operational initiatives, reflecting the difficulty of scaling AI across fragmented environments. The Data Gap: Access, Governance, and Visibility At the core of these challenges is a lack of complete data access and control. 84% of respondents felt confident in the accuracy, completeness, and alignment of their organization’s data. However, this optimism often masks deeper issues, including persistent silos, inconsistent data quality, and limited accessibility. Data th...
Rethinking AI sovereignty: pathways to competitiveness through ...
With AI investment concentrated in a few economies and infrastructure constrained by energy, land, and grid capacity, governments are rethinking how to build competitive AI systems. The World Economic Forum's report 'Rethinking AI Sovereignty: Pathways to Competitiveness through Strategic Investments' examines investment patterns, AI infrastructure, and AI development models, highlighting ...
Artificial Intelligence Insights | Bain & Company
Explore Bain's artificial intelligence insights, offering expert analysis and research on AI trends, applications, and strategies to drive business success.
The Annual AI Adoption Report 2026: Who's Leading, Who's ... - LinkedIn
AI adoption has surged globally in 2025-2026, with generative AI tools now used by 16.3% of the world's population—roughly one in six people—but stark regional divides persist, driven by ...
