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ZDNET Highlights
- 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 increase in AI use.
- 86% plan to increase investment in data management to support AI development.
A new survey 600 Chief Data Officers (CDOs) found that 69% of companies with more than $500 million in revenue 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 remains a concern. 75% of CDOs surveyed believe their workforce needs increased skills in data literacy, and 74% need increased AI literacy to responsibly use AI or AI outputs in day-to-day operations. Better data and AI literacy will increase AI adoption in business.
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report, from information ScienceWakefield Research and Deloitte note that although the skill set is a challenge, trust in the data used to drive AI models is growing: 65% of data leaders believe their employees trust the data being used for AI. Without proper AI literacy, employees may not be able to recognize potential data deficiencies or poor quality, he said.
Governance is also a potential barrier to increasing AI adoption in business, with nearly three-quarters of data leaders admitting that their companies’ visibility and governance has not kept pace with employees’ use of AI.
Here are some of the key findings from the survey conducted by Informatica sales force Company.
Current state of AI
AI adoption has reached 69% of businesses with revenues of more than $500 million, up from 48% in 2025 and 45% in 2024. Additionally, 47% of companies have adopted agentic AI. This indicates greater confidence in data quality and accessibility, 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 key challenges to AI agent adoption. Furthermore, most businesses have not kept pace with visibility and governance regarding the use of AI by their employees.
More companies will invest in data management, with 86% of CDOs reporting increased investments in 2026-2027. Those most in need of investment in data quality and management include improving data privacy and security (43%), improving data and AI governance (41%), and improving data and AI literacy (39%).
Embracing Generative and Agentic AI
The CDO survey found that adoption of agentic AI has reached 47% and an additional 31% of companies plan to adopt it in the next 12 months. 54% of large companies have already adopted agentic AI, while 44% of small companies (fewer than 5,000 employees) have already adopted it. The top challenges to adopting 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 improved customer experience (29%), improved business intelligence, analytics, and decision-making capabilities (28%), compliance with regulatory standards (27%), and improved employee collaboration and workflow (26%).
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Taking agentic AI from pilot to production is about trust in the data. Better data is a key factor for AI success. Lack of data reliability can hinder initiatives from pilot to production for organizations that have already adopted or plan to adopt AI. Fifty-seven percent see data reliability as a major barrier to moving more projects from pilot to production. Data leaders are taking the following steps to improve the trustworthiness of data used for AI:
- Improving workflows around data and AI
- Increasing investment in improving data quality
- Investing in data and metadata collection and management
Employee trust is the key to AI adoption and scaling
The majority of data leaders (65%) believe that their employees trust the data they have and are using for AI. For companies using agentic AI, trust in data is even higher: 74% believe most or all of their organizations trust the data used for AI efforts.
The more you use AI solutions, the more likely you will improve both data quality and accessibility. But if data and AI literacy is a challenge and risk for businesses, should we be comfortable with a high level of trust on the data our employees use? Should high levels of trust be a cause for concern? Can an employee recognize poor quality or unreliable data?
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CDOs believe their employees need to increase both data literacy (75%) and AI literacy (74%) to use AI or its outputs responsibly. So some degree of high trust in AI may be due to a lack of understanding of what constitutes high quality data in the first place.
Data leaders will invest more to ensure they have quality data for AI. Data leaders (41%) will increase their investment in data management in 2026, with improvements in data and AI governance as a top need. Nearly half of data leaders are adopting existing tools for AI governance, 30% are investing in different tools, and 22% are developing new tools. The majority of data leaders (75%) of companies looking to expand their existing governance tools have already adopted generative AI solutions, while 65% of companies are developing new governance tools.
Investing in data management is almost universally a priority for data leaders – 86% plan to increase their investments in 2026. Investment in data management is driven by the fact that data challenges threaten the successful adoption of AI, including data privacy and security, data quality, regulatory compliance, and governance of unstructured data.
Data leaders are also looking to their technology business partners and vendors to help them improve data readiness for AI. Data leaders believe they will 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 increase complexity and slow scalability.
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Last year was a significant year for AI adoption, and 2026 will be the year of increasing generative and agentic AI solutions in business. Trust should be the number one core value for businesses looking to become an agent business. Successful AI adoption and scale requires reliable, high-quality data and strong governance for the privacy and security of that data. Data leaders are quick to 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 levels of credibility and positive outcomes for all stakeholders.
To learn more about the CDO Insights 2026 report, you can visit Here.
