This whitepaper highlights the gap between data and decision-making due to poor data quality and fragmented systems. It introduces Decision Intelligence to enable real-time, actionable decisions from enterprise data.
Over the last decade, there has been massive investment in analytics platforms, cloud data lakes, data visualization tools, and AI models by enterprises. However, empirical studies have continued to reveal a widening gap between the availability of data and the ability to act on it in business. Recent 2025 research highlights that despite continued investments in AI and analytics, only about 46% of executives trust their organization’s data, indicating a persistent trust deficit that limits effective decision-making (Gravina, 2025). Furthermore, studies show that only around 35% of executives fully trust organizational data, while nearly 62% continue to rely on intuition over data-driven insights, reinforcing the disconnect between data availability and decision confidence (Pangaea X, 2025).
This challenge is compounded by foundational data issues, as nearly 98% of organizations report that poor data quality remains a major barrier to successful AI adoption, despite increased spending on analytics initiatives (Gravina, 2025). In parallel, execution remains a critical bottleneck, with nearly three out of four analytics initiatives failing to translate into measurable business impact, demonstrating that insight generation continues to outpace actionable implementation (Pangaea X, 2025).
