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ZDNET’s key takeaways

• Half of agentic AI adopters cite data quality and retrieval issues as deployment barriers.
• 76% of data leaders report that governance has not kept pace with the rise in AI use.
• 86% plan to increase investment in data management to support AI growth.

A new survey of 600 chief data officers (CDOs) found that 69% of companies with revenues of $500M+ are using generative AI in their operations, up from 48% in 2025. Although AI adoption is increasing, the report found that data and AI literacy are a concern. Of the CDOs surveyed, 75% believe their workforce needs upskilling in data literacy, and 74% in AI literacy to responsibly use AI or AI outputs in day-to-day operations. Improved data and AI literacy will increase AI adoption in business.   

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The report, from Informatica, Wakefield Research, and Deloitte, noted that although skill set is a challenge, trust in the data used to operate AI models is growing: 65% of data leaders believe their employees trust the data they are using for AI. That said, without proper AI literacy, employees may not be able to recognize potential data shortcomings or poor quality. 

Governance is also a potential obstacle to scaling AI adoption in business, with nearly three-quarters of data leaders acknowledging that their companies’ visibility and governance have not kept pace with employees’ use of AI.

Here are some key findings from the survey conducted by Informatica, a Salesforce company.

The current state of AI

Adoption of AI has reached 69% of businesses with revenues of $500M+, up from 48% in 2025 and 45% in 2024. In addition, 47% of companies have adopted agentic AI. This signals greater confidence in data quality and access, with 61% of CDOs noting that better data makes it easier to adopt AI.

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Data literacy and AI literacy are challenges for businesses, with 50% of companies planning to use agentic AI citing data quality and access as major challenges to AI agent adoption. In addition, the vast majority of businesses have not kept pace with visibility and governance regarding their employees’ use of AI. 

More companies will invest in data management, with 86% of CDOs reporting increased investments in 2026-2027. The greater need for investments in data quality and management includes improving data privacy and security (43%), improving data and AI governance (41%), and improving data and AI literacy (39%). 

Scaling adoption of generative and agentic AI 

The CDO survey found that agentic AI adoption has reached 47% with an additional 31% of companies planning to adopt in the next 12 months. Of larger companies, 54% have already adopted agentic AI, versus 44% of smaller companies (less than 5,000 employees). The top challenges for adoption of agentic AI are data quality (50%), security concerns (43%), and lack of agentic AI expertise (42%). 

The primary benefits of adopting agentic AI in business include enhanced customer experience (29%), improved business intelligence, analytics, and decision-making (28%), compliance with regulatory standards (27%), and enhanced employee collaboration and workflows (26%).

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Scaling adoption of agentic AI from pilot to production is all about confidence in data. Better data is a critical factor for AI success. A lack of data reliability can be a barrier to moving initiatives from pilot to production for organizations that have already adopted or plan to adopt AI. Fifty-seven percent view data reliability as a key barrier to moving more projects from pilot to production. Data leaders are taking the following steps to improve the reliability of the data used for AI: 

• Improving workflows around data and AI
• Increasing investments in improving data quality 
• Investing in data and metadata collection and management

Employee trust is key to the adoption and scaling of AI 

A majority of data leaders (65%) believe that their employees trust the data that they have and are using for AI. For companies using agentic AI, confidence in the data is even higher: 74% believe most or all of their organization trusts the data they use for AI efforts.

The more you use AI solutions, the more likely you are to improve both data quality and access. But if data and AI literacy are a challenge and risk for businesses, should we be comfortable with our employees’ high degree of trust in the data they use? Should a high level of trust be a cause for concern? Can an employee recognize poor quality or untrustworthy data? 

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CDOs believe their employees need both data literacy (75%) and AI literacy (74%) upskilling to responsibly use AI or its outputs. So some of that high trust in AI may stem from a lack of understanding of what constitutes high-quality data in the first place.

Data leaders will invest more in ensuring they have quality data for AI. Data leaders (41%) will increase their investments in data management in 2026, improving data and AI governance as a top need. Nearly half of data leaders are adapting existing tools for AI governance, with 30% investing in discrete tools and 22% developing new tools. The majority of data leaders (75%) at companies expanding their existing governance tools have already adopted generative AI solutions, compared with 65% of companies developing new governance tools.

Investing in data management is nearly universally a priority for data leaders — 86% plan to increase their investments in 2026. Investments in data management are driven by the fact that data challenges threaten the successful adoption of AI, including data privacy and protection, data quality, regulatory compliance, and the governance of unstructured data. 

Data leaders are also looking for their technology business partners and vendors to help them improve data readiness for AI. Data leaders believe they’ll need multiple vendor partners to meet their data and AI goals — the average number of vendor partners in 2026 was seven for data management and eight for AI management. The balancing act for data leaders is recognizing that using more vendor partners will add complexity and slow scalability. 

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Last year was a turning point for AI adoption, and 2026 will be the year of scaling generative and agentic AI solutions in business. Trust must be the number one core value for businesses becoming agentic businesses. Successful AI adoption and scale require reliable, high-quality data and strong governance for privacy and security of the data. Data leaders also urgently remind us that data and AI literacy is a key area of investment, ensuring their employees are able to use AI most effectively while maintaining the highest level of trustworthiness and positive outcomes for all stakeholders. 

To learn more about the CDO Insights 2026 report, you can visit here.