A global Informatica study finds rapid AI adoption is outpacing data governance, reliability, and workforce literacy—putting trust and ROI at risk.
Informatica, now part of Salesforce, has released a new global study warning that while organizations are accelerating their use of artificial intelligence, many lack the data foundations needed to realize its full value.
The report, CDO Insights 2026: Data governance and the trust paradox of data and AI literacy take center stage, draws on a survey of 600 senior data leaders across the United States, the United Kingdom and Europe, and the Asia-Pacific region. It finds that AI adoption is rising rapidly—but governance, data quality, and workforce readiness are failing to keep pace.
According to the study, 69 percent of organizations have now integrated generative AI into their business practices, up sharply from 48 percent a year earlier. Nearly half, 47 percent, report that they have already adopted agentic AI. Yet this rapid uptake is outstripping the frameworks required for responsible, secure, and effective use.
Poor data quality remains a central obstacle. Fifty-seven percent of respondents cited data reliability as a key barrier to moving AI initiatives from pilot to production, and half said it is the top challenge in deploying agentic AI. Despite these concerns, 65 percent of data leaders believe that most or nearly all employees trust the data being used for AI—a disconnect the report characterizes as a “trust paradox.”
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Governance gaps are equally pronounced. More than three-quarters of respondents, 76 percent, said their organization’s AI governance does not fully keep pace with how employees are using AI tools, increasing exposure to risks related to privacy, security, ethics, and regulatory compliance.
The workforce challenge is acute. Seventy-five percent of data leaders said employees need stronger data literacy skills, while 74 percent said more AI literacy training is required to ensure responsible day-to-day use.
In response, 86 percent of organizations plan to increase investment in data management in 2026. The leading priorities cited were improving data privacy and security, enhancing data and AI governance, and upskilling employees to improve data and AI fluency.
“This report highlights the risks of accelerating AI adoption without strong data governance and literacy,” said Amanda Fitzsimmons, senior director of customer data at RS Group. She said her organization embeds governance and accountability into how it evaluates and scales AI initiatives to ensure innovation advances responsibly and delivers measurable value.
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Krish Vitaldevara, Informatica’s chief product officer, said the findings underscore a growing confidence gap. “The promise of AI is immense, but so are the risks if you don’t have confidence in a reliable data foundation,” he said. While employees may trust the data they use, he added, many lack the data and AI literacy skills—and organizations lack the governance structures—needed to achieve responsible and ethical outcomes.
For AI to deliver meaningful returns, Vitaldevara said, organizations must prioritize data reliability, invest in rigorous governance, and upskill their workforce so AI-driven decisions are based on trusted, high-quality data used responsibly across the enterprise.
The report also examines regional differences, shifting data management priorities, and the AI-powered use cases organizations are prioritizing as adoption accelerates.
