AI investment soars but only a tenth of projects are fully deployed

New research reveals that while organizations have nearly doubled their overall AI investment to $27 million (up from $14.7 million in 2024) and 87 percent report that the ROI on their AIOps initiatives has met or exceeded expectations, however, only 12 percent of AI projects have reached full enterprise-wide deployment.

The survey, of 1,200 business decision-makers, IT leaders, and technical specialists, from Riverbed shows organizations report facing several significant barriers to AI implementation. The majority are not fully prepared to roll out AI projects, with challenges including persistent issues with data quality and a gap between leadership optimism and the technical realities of implementation.

The IT marketplace is changing too as 93 percent of businesses consider switching vendors in order to consolidate tools. The new realities of today’s workplace mean that performance of unified communications has become critical and key focus with leaders and practitioners spending on average 42 percent of their work week using these tools.

“Companies are investing heavily in AI for IT because they understand the potential it has to transform operations in today’s working world,” says Jim Gargan, chief marketing officer, at Riverbed. “However, our research shows that enterprises face several significant challenges as they attempt to move from the early stages of implementation to practical AI solutions that deliver a strong return on investment. Across the globe, Riverbed is helping organizations to improve user experiences and IT operations with safe, secure, and accurate AI. We’re focusing on what our customers need: full support for AIOps; a solution to the data gap with observability across all of IT; and fast, agile, secure AI data acceleration.”

Organizations face significant challenges in data quality, a foundational issue for AI success. While 88 percent agree that data quality is important, only 46 percent are fully confident in the accuracy and completeness of their data as they prepare to implement AI. In reality, most enterprises admit their data isn’t ready, with just 34 percent rating their data as excellent for relevance and suitability, 35 percent for consistency and standardization, 37 percent for security and protection.

Leaders are more optimistic than technical specialists, with 42 percent of leaders but only 25 percent of specialists saying their organization is fully prepared to implement AI projects today.

Despite deploying an average of 13 observability tools supplied by nine vendors organizations lack visibility into system performance and data. Consequently 96 percent of organizations are consolidating the number of tools and vendors they utilize across ITOps and 93 percent say that a unified platform would make it easier to identify and resolve operational issues.

The full report is available on the Riverbed site.

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