Only 5% of organisations say data is AI-ready

Further has published research showing that only 5% of organisations believe their data is largely ready for AI. The findings are based on a survey of 515 US-based AI decision-makers.

The report highlights a gap between spending on artificial intelligence and the condition of the data companies use to support it. While 29% of organisations had completed a formal data audit and remediation plan, only a small minority said their data was largely prepared for AI use.

Most respondents were still at an early or middle stage of adoption. The survey found that 69% of organisations investing in AI were still exploring, experimenting or implementing it, rather than operating at a more mature level.

That gap has practical consequences. More than a third of organisations, 37%, said they had paused, scaled back or abandoned an underperforming AI initiative in the past 12 months. Among that group, data quality or availability was the most commonly cited reason, identified by 24% of respondents.

The findings suggest many businesses are seeing immediate operational gains from AI but have yet to build the structures needed for broader returns. Cost savings were the most frequently cited early benefit, named by 36% of respondents, while 25% pointed to improvements in routine processes.

Governance gaps

The survey also highlighted weaknesses in oversight and accountability. While 83% of respondents said AI readiness represented at least a partial competitive advantage, only 3% said their organisation had a documented process for auditing AI.

Confidence in internal preparedness appeared mixed. Although 79% described their organisation as aligned on AI and 82% said they felt confident explaining AI outputs, 25% also said they struggle to explain or trust those outputs. Meanwhile, 36% identified a lack of internal expertise as their biggest challenge in implementation and operations.

Responsibility for AI decision-making was spread across the business. The survey found it was split almost evenly between IT and data teams, cited by 40% of respondents, and executive leadership, cited by 38%.

However, only 7% said leadership and technical teams were brought together in a cross-functional Centre of Excellence. That suggests limited use of formal structures to connect strategy, technical delivery and governance.

Spending pressure

The research comes as investment in AI continues to rise across the US economy. Further cited forecasts that AI investment in the US will exceed USD $1 trillion this year, increasing pressure on companies to show returns while managing operational risks.

Jason Tabeling, Head of Solutions at Further, said many businesses were investing without a clear long-term plan. "Nobody is slowing down on AI spending, but a lot of money is being spent out of fear of falling behind, without a roadmap for deriving long-term value," he said. "Right now, 83% of leaders see AI readiness as a competitive advantage, but only 3% have a documented process to audit it. That gap is where new AI advantages will be decided, and outcomes will move beyond cost savings."

The report argues that adopting AI tools is not the same as organisational maturity. Many companies may be able to launch projects or realise quick savings, but the findings indicate fewer have established the data standards, governance processes and organisational accountability needed to sustain those efforts.

Price Glomski, SVP of GTM at Further, linked project failures to earlier weaknesses in data management. "AI exposes every shortcut you've ever taken with your data. More than a third of organisations have pulled back on an AI initiative in the past year, and data quality is the reason they cite most," he said. "Investment in AI alone won't fix that. Building the governance and data infrastructure that AI depends on will."