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Survey: Organizations Report Positive ROI on AI Investments, Yet Data Readiness and Oversight Lag Behind

  • By Sean Parker
  • 10/26/26

Key Takeaways

  • Just 5% of surveyed enterprise leaders in the United States believe their organization's data is largely ready for AI, according to new research from Further.
  • More than one-third reported pausing, scaling back, or abandoning an underperforming AI initiative in the past year, with data quality or availability the most cited reason among those respondents.
  • Although 77% reported positive returns on AI investment, only 3% said their organizations had a documented process for auditing AI.

According to a survey by data and AI services provider Further, enterprises are reporting benefits from artificial intelligence even as their data preparation and oversight processes remain incomplete.

The company's recent State of Enterprise AI Maturity research surveyed 515 U.S.-based AI decision-makers. Just 5% believed their organizations' data was largely ready for AI.

The findings suggest that gaining value from individual AI applications and preparing to operate them more broadly are separate challenges. Reported returns alone do not establish that an organization has the foundations to sustain or expand those results.

Data Problems Accompany Project Setbacks

Further found that 37% of respondents' organizations had paused, scaled back, or abandoned an underperforming AI initiative in the previous 12 months. Among that group, data quality or availability was the most frequently cited main reason, at 24%.

Meanwhile, 29% reported completing a formal data audit and remediation plan. The research also placed 69% of organizations in the exploring, experimenting, or implementing stages of adoption.

Further distinguishes data prepared for conventional reporting from data prepared for AI. Its explanation emphasizes data origins and documentation, along with access controls that support ongoing evaluation and governance.

For readers assessing their own readiness, the practical issue is whether data supports the requirements of a particular application. A collection suitable for a dashboard may need additional preparation before it can reliably support an AI system.

Reported Returns Do Not Establish Oversight

Seventy-seven percent reported a positive return on AI investment. However, only 3% said their organizations had a documented AI-audit process.

The findings measure different things: perceived financial benefit and the existence of a repeatable oversight process. Neither substitutes for the other.

"In reality, confidence without a documented process is exposure," said Kierra Dotson, associate director of AI strategy and governance at Further. "Closing that gap doesn't take new technology; it requires an auditable governance process."

For the full report, visit the Further site (registration required).

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