AI Adoption Accelerates Despite Widespread Data Trust Issues

Event summary

  • 47% of 350+ finance and IT executives made major business decisions on faulty data in the past year.
  • 72% of executives report bad data cost their organization $500,000 or more, with 37% reporting damages over $1 million.
  • Executives who made decisions on bad data are four times more likely to use ten or more AI tools than their peers.
  • Only 19% of executives pull the majority of their AI inputs from a single, centralized enterprise system.
  • Organizations with complete alignment between Finance and IT are 5.5x more likely to report complete trust in their data.

The big picture

As AI spending surpasses $2 trillion in 2026, organizations are under pressure to deploy AI at scale. However, the study reveals a fundamental instability in the data foundation supporting AI adoption. The gap between AI ambition and data readiness highlights the need for strong governance and business context to prevent AI from amplifying errors. The structural disconnect between Finance and IT further complicates effective data governance, emphasizing the importance of alignment for AI-driven decision-making.

What we're watching

Governance Dynamics
How Finance and IT alignment will affect data trust and AI-driven decision-making.
AI Risks
Whether organizations can mitigate AI-related risks, including flawed decisions and financial misreporting.
Data Centralization
The pace at which companies will adopt centralized enterprise systems for AI inputs.