The AI Paradox: Ambition Built on a Shaky Foundation
The enterprise mandate is clear: AI is the strategic objective. Boardrooms globally are betting their future on it, driving a surge in investment projected to push the Data Intelligence, Analytics, and Infrastructure (DIAI) market past $475 billion in 2025. Futurum primary research confirms this priority, with 52% of 800+ enterprise decision-makers stating that generative and
agentic AI tools will make up their top investments during the coming year.
However, a profound disconnect exists between this ambition and the operational reality. A joint study from Kearney and The Futurum Group, “Are CEOs Ready to Seize AI’s Potential?”, found that while 78% of CEOs feel confident in their ability to capture value from AI, a staggering 60% of executives with stalled AI initiatives cite fragmented data and outdated infrastructure as
the primary culprits. This isn’t a failure of AI models or AI tooling; it’s a failure of the underlying data fueling those models and tools. This is the great AI paradox.