Investment in AI continues to grow, but just one in 10 AI projects is fully deployed.
Artificial intelligence continues to gain popularity among IT leaders, and AI investments continue to rise. But greater spending is no guarantee of AI deployment success.
Just one in 10 AI projects has been fully deployed, according to a global survey of technology professionals. And despite 78% of polled organizations reporting that they upped their AI spend in the past year, many respondents believe their AI readiness is decreasing rather than increasing.
The 2025 State of AI Readiness for AIOps Report, released by Riverbed and conducted by Coleman Parkes Research in July 2025, polled 1,200 business decision-makers, IT leaders, and technical specialists across several countries (Australia, France, Germany, Saudi Arabia, Spain, the U.K., and the U.S.)
Roughly one-third (36%) of organizations said they are prepared to operationalize AI, down from 37% in last year’s study.
“Enterprises are betting big on AI, but most aren’t yet ready to operationalize it,” said Dave Donatelli, CEO of Riverbed, in a statement. “There’s a clear disconnect between investment and execution. This mismatch between investment and operationalization is creating an AI reality gap that enterprises must urgently address in order to capitalize on its transformative potential.”
The report also uncovered a disparity between the perception of AI readiness among business leaders and technical specialists. Forty-two percent of business leaders believe their organization is prepared for AI, compared with just 25% of technical specialists. Business leaders are also more confident (64%) in their company’s AI strategy in relation to IT operations and digital experience than their technical specialist peers (48%). The survey data illustrates the misalignment between goals and reality, according to Riverbed.
“Looking ahead, however, there is a broad consensus around future readiness. By 2028, 86% of respondents expect their organizations will be prepared to support AI at scale, with alignment between both businesses and technical stakeholders,” the report reads.
Another hurdle to AI success is data. The Riverbed study asked respondents to rate their data and its relative readiness for AI projects. While 88% of respondents agree that high-quality data is essential to AI success, the percentage of respondents who feel confident in their data varies. Fewer than half of organizations rate their data as excellent in the following areas:
- Relevance and suitability: 34%
- Consistency and standardization: 35%
- Security and protection: 37%
- Quality and completeness: 43%
- Accuracy and integrity: 46%
- Accessibility and usability: 49%
The report also revealed that network performance has emerged as a requirement of AI success. More than 90% of organizations stated that the moving and sharing of data is critical (33%) or very important (58%) to their AI strategy. Three-quarters of those polled said they plan to establish a dedicated AI data repository strategy by 2028, and 88% of enterprises are deploying OpenTelemetry to increase their AI readiness. And 94% of respondents said that OpenTelemetry will “underpin future initiatives such as AI-driven automation.”
“OpenTelemetry is fast becoming the backbone of AI readiness,” Donatelli added. “It provides the visibility and data standardization enterprises need to move from experimentation to execution. At Riverbed, we’re helping organizations bridge this readiness gap with observability, performance, and secure data acceleration so they can unlock AI’s full potential.”
