Press releases
OpenText and Foundry Survey of IT Leaders Shows that AI Success Depends on Maturity, But Information Readiness is the Equalizer
Nearly 70% of mature AI users satisfied with ROAI; new adopters lag behind
Waterloo, ON - 2025-09-30 -OpenText™ (NASDAQ: OTEX) (TSX: OTEX), a global leader in secure information management for AI, today released new global research from Foundry, "AI Is Redefining the Role of the Knowledge Worker," revealing a sharp divide between new and mature AI adopters when realizing return on AI investment (ROAI). While enterprises are investing heavily in AI, many only achieve meaningful results when information management programs are mature enough to support AI initiatives.
The survey of 515 CIOs and other senior enterprise IT leaders shows that while nearly 70% of mature AI users are highly satisfied with their ROAI, only 42% of newer adopters felt the same. Satisfaction in ROAI is also closely tied to whether leaders trust their AI tools to handle information securely. This disconnect often leaves organizations struggling to balance AI ambition and risk.
A financial services CIO respondent described this challenge by stating, "Our business wants more AI and our security and IT are panicking because nobody knows how to secure it and run it in a well-governed way." A VP in healthcare echoed the same sentiment, noting that "AI success depends on better metadata management, stronger governance, and classification."
Maturity Drives ROAI
The research shows that the benefits of AI compound with experience. Organizations that have advanced further on AI invest more, measure success in more meaningful ways, and see stronger returns as a result.
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Mature users measure ROAI by problem-solving impact and risk reduction, while newer adopters focus more narrowly on efficiency gains.
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Enterprises allocate an average of $5.4 million annually toward generative AI tools, infrastructure, and talent, which also points to greater investment supporting satisfaction with results.
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Multi-agent AI is viewed as "game-changing" among mature users and seen as critical for tackling complex issues.
"AI's value does not appear overnight. Real returns come when enterprises move beyond surface-level automation to solve real problems. That takes secure, well-governed information. Without that foundation, ROAI is almost impossible to achieve," said Savinay Berry, Chief Product Officer and Chief Technology Officer at OpenText. "We give organizations that foundation by simplifying information complexity, strengthening governance, and ensuring information is ready for AI."
Information Readiness Is Essential
Despite different levels of maturity, nearly all enterprises agree that information readiness is essential to unlocking AI's full value.
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Security and compliance risk (44%) remains the top information management challenge.
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Less than half of organizations rate their governance as working "very well," highlighting a major barrier to scaling AI.
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When choosing partners, both new and mature adopters rank deep expertise in secure information management at the top (50% and 49%, respectively).
Additional Resources
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Read the full report on ROAI, adoption, investments, and challenges.
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Read more about the findings on our blog.
Survey Methodology
The survey, conducted by Foundry in June 2025, captured quantitative and verbatim insights from 515 senior IT leaders across North America (59%), APAC (20%), and Europe (21%). Respondents represented organizations with an average annual revenue of $5.4 billion across industries including financial services, healthcare, technology, manufacturing, and retail.
About OpenText
OpenText™ is a leading Cloud and AI company that provides organizations around the world with a comprehensive suite of Business AI, Business Clouds, and Business Technology. We help organizations grow, innovate, become more efficient and effective, and do so in a trusted and secure way - through Information Management. For more information about OpenText (NASDAQ/TSX: OTEX), please visit us at
https://www.opentext.com.
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Contact
Joel Hammond
OpenText