At this year’s Informatica World, one of the most relevant and forward-looking sessions I attended was the keynote titled “Accelerate GenAI Adoption with Data & AI Governance.” As part of the Informatica team, it was encouraging to see how directly the session addressed both the momentum and the challenges surrounding GenAI adoption in today’s enterprise landscape.

The keynote opened with a clear message: GenAI is no longer a niche innovation — it’s becoming a core part of enterprise strategy. Organizations are scaling AI across business units, and “Worldwide generative AI (GenAI) spending is expected to total $644 billion in 2025, an increase of 76.4% from 2024,” according to a forecast by Gartner®.¹ Business leaders are driving this shift and early adopters are already seeing measurable returns in revenue growth, cost savings and operational efficiency.

However, the session also acknowledged a critical reality that many GenAI initiatives are struggling to move beyond the pilot phase. Our recent CDO Insights survey, which included over 600 data leaders across industries and geographies, revealed that 92% of leaders surveyed are concerned about projects advancing without addressing foundational issues like data quality, privacy and responsible AI. Two-thirds of respondents reported difficulty transitioning even half of their pilots into production. “Gartner predicts 30% of generative AI projects will be abandoned after proof of concept by end of 2025."²

These challenges are not only technical; they also reflect wider organizational readiness. Data completeness, regulatory compliance and AI fluency are essential for success. Many organizations encounter a “last-mile” issue: developing a promising model in a controlled environment is one thing but effectively integrating it into real-world business processes at scale is another.

That's why the Informatica World keynote introduction of a four-step governance framework: Inventory, Control, Deliver and Observe was so timely. It’s a practical, scalable model designed to help organizations build trust, ensure compliance and accelerate GenAI outcomes. Each step plays a critical role.

• Inventory ensures organizations know what data and models they have
• Control puts the right policies and safeguards in place
• Deliver focuses on operationalizing AI responsibly
• Observe enables continuous monitoring and improvement

This framework aligns with business operations and outlines a clear path from experimentation to production. It focuses on establishing a foundation for sustainable and scalable success, rather than adding complexity.

At Informatica, we view governance not as a constraint, but as a catalyst. It enables innovation while managing risk. Governance ensures AI is not only powerful, but also reliable, fair and secure. And it helps organizations meet growing regulatory expectations, such as those outlined in the EU AI Act and other emerging frameworks and regulations.

The pace of GenAI adoption is unlike anything we’ve seen before. For organizations looking to lead, now is the time to act with clarity, with structure and with governance at the core. As emphasized in the keynote, those who build a strong foundation will be best positioned to fully realize the value of GenAI, while those who hesitate risk falling behind.

During the session, Ericsson’s Niklaus Kalberg discussed their data and AI journey. Kalberg’s story brought to life the real-world impact of strong governance and reinforced how critical it is to embed trust and transparency into every stage of AI adoption. Watching the full keynote and hearing directly from industry leaders like Ericsson clarified that the future of AI is not just about speed but also about responsibility.

If you would like to watch the full keynote, you can access it here: https://now.informatica.com/iw-greatest-hits.html