Larridin 2026 State of Enterprise AI Report reveals only 38% have a complete inventory of AI applications in use
As enterprises accelerate their AI investments, the new study from AI measurement and scaling platform Larridin exposes a paradox among the senior leaders surveyed.
The Larridin 2026 State of Enterprise AI Report surveyed over 350 senior leaders at companies of 1,000+ employees and reveals that even with 92% of C-suite executives expressing full confidence in AI impact, 58.2% of organizations cite unclear or fragmented ownership as their primary barrier to measuring AI performance. As a result, 62% lack a comprehensive inventory of applications in use, revealing a disconnect between executive confidence and operational reality.
The AI Reality
The enthusiasm at top-level management is driven mainly by early experiments and enthusiasm, but broader adoption is more fragmented, harder to govern, and increasingly difficult to measure at scale. While three-quarters of enterprise leaders expect AI to deliver ROI within six months, nearly half admit they don’t know who is using it or how. In addition, only 25% have fully implemented AI governance programs, demonstrating that executive optimism appears to be outpacing operational reality.
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According to the study, almost 80% say they use AI, licensing a broad mix of applications, with an average of 23 AI tools per organization. Most governance frameworks center on the major LLM platforms, such as OpenAI’s ChatGPT and Google Gemini, because they’re widely licensed and provide proprietary analytics for monitoring. However, with enterprises now operating across dozens of AI tools, this narrow focus leaves executives blind to peripheral and unlicensed AI use, limiting visibility while introducing both risk and unrealized value.
“We’re living the era of tremendous AI exuberance,” said Russ Fradin, CEO and co-founder of Larridin. “The C-suite believes AI is visible, valuable, and under control, while adoption is racing ahead of measurement and governance is inconsistent. Until enterprises can organize their efforts around real-time data, AI could be a strategic liability as well as a strategic asset.”
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Survey Highlights: High Confidence with Limited Clarity
The research reveals AI confidence is soaring, paired with persistent blind spots on actual usage and measurement:
- Over 75% of executives consider AI valuable, yet half don’t measure outcomes at all or rely on surveys instead of real-time data.
- 25% of organizations cannot reliably measure end-to-end AI adoption.
- 82% of respondents report faster project delivery; however, time savings for employees were low—under 10 hours/month for nearly 86%.
From Risk to AI Strategic Advantage
The study finds that the primary barriers to AI adoption and scale are structural, not technical. Unclear responsibility for measurement (30.5%) and fragmented ownership across teams (27.7%) emerge as the leading obstacles to turning AI enthusiasm into measurable value. This diffusion of responsibility allows AI initiatives to expand or falter without centralized governance, resulting in inconsistent metrics, duplicated investments, and increased security risk.
“Early success created momentum and optimism. But as AI becomes an integral part of daily workflows, organizations need clear AI ownership, ideally led by executives, to establish objectives, system-level measurement of who is using AI, how it’s being used, and what outcomes it actually drives,” added Fradin.