Unlocking AI Success: Why Unified, Trusted Data Is Your Foundation
I recently spoke with a CIO grappling with significant pressure from their CEO and board to rapidly deploy agentic AI. Their hesitation isn’t skepticism about AI—it’s rooted in the practical reality that 72% of enterprises face: fragmented data undermining AI’s effectiveness. In fact, according to Gartner, less than 54% of AI pilots ever make it to production, primarily due to inadequate data quality and integration.
This CIO’s concern highlights a universal truth: successful AI initiatives demand unified, trusted and real-time data. IDC reports that enterprises spend up to 80% of their AI project time just preparing data, severely limiting AI’s value. Without a cohesive data foundation, even the most advanced agentic AI will struggle to deliver meaningful, scalable outcomes.
The path forward is clear: addressing foundational data issues first. Organizations investing early in data governance typically achieve 30-40% greater ROI on their AI efforts, according to McKinsey.
The CIO’s caution isn’t resistance—it’s insight, pinpointing precisely where enterprises must act now to truly unlock the transformative potential of agentic AI.
Speaking of siloed data….
Recently, Salesforce announced its acquisition of Informatica—more than just another M&A headline, it’s a clear signal about where enterprise tech is headed. Salesforce recognizes what many of us have seen coming: enterprise applications are increasingly built around AI, and the new competitive advantage isn’t flashy features but the underlying data. To run powerful AI-driven tools and workflows, organizations need unified, real-time, context-rich data. By acquiring Informatica, Salesforce is doubling down on its data infrastructure, aiming to become the foundational hub for future AI-powered applications.
However, this kind of consolidation presents significant challenges. While the goal of a seamless “Customer 360 record” is appealing, integrating large legacy systems can be complex, slow, and often expensive. There’s also a bigger picture here: is Salesforce moving beyond customer data to become the central repository for all enterprise data? If so, what happens to openness, agility, and customer choice? Enterprises need flexibility, especially in the rapidly evolving AI landscape.
This consolidation became even more concerning with Salesforce quietly tightening access to Slack data, limiting bulk exports and restricting AI model training. It’s a clear reminder of why no organization should let critical data get trapped inside a single vendor’s ecosystem. At Reltio, we believe the opposite: enterprises need an open, interoperable data foundation—a “Switzerland” for data—that can genuinely support AI innovation without forcing vendor lock-in. Because in this new AI-driven world, your data strategy shouldn’t just support growth; it should actively drive it.
Beyond the Silos: The Power of Customer 360 in Life Science
Ansh Kanwar, CPO, explores why “good enough” data isn’t sufficient anymore in his article, “The Hidden Cost of ‘Good Enough’: Why CIOs Must Rethink Data Risk in the AI Era.” Ansh highlights the growing risks and hidden costs associated with settling for fragmented, outdated data infrastructure as AI becomes increasingly critical to enterprise strategy.
As we’ve seen time and again, unified, trusted data is the essential foundation for realizing the full potential of AI. Whether you’re navigating consolidation in enterprise tech or driving transformation in life sciences, how you manage and leverage your data truly matters. To dive even deeper into these topics and connect with other forward-thinking leaders, join us at DataDriven, our annual conference that brings together the industry’s top thinkers.
