Only 33% of Enterprises Meet AI Business Case Goals, Study Finds

SAN ANTONIO and BOSTON, Nov. 12, 2026 /CourierPR/ -- Rackspace, in collaboration with HFS Research, has released a new study revealing that only 33% of enterprises have met or exceeded the business case for their most significant AI program. The findings, based on a survey of 502 senior AI decision-makers, highlight significant governance gaps, with 96% of respondents reporting such issues. This gap is particularly pronounced among enterprises deploying AI across multiple business functions, where only 28% have achieved their expected returns.

The study also found that the challenge of fragmented accountability intensifies as AI is expanded across various business functions. Among enterprises deploying AI in one function, 37% have met or exceeded their business case, compared to 28% among those deploying AI across several functions. For organizations where AI is embedded in standard operations, the success rate is even higher, with 56% meeting or exceeding their business case.

According to the report, the gains from AI investments remain concentrated in efficiency. Specifically, 58% of respondents cited workforce productivity improvements, while 42% reported measurable cost reductions. In contrast, only 28% reported better customer experience, and 21% noted measurable revenue growth. These findings suggest that while AI can significantly boost operational efficiency, its impact on customer experience and revenue is less pronounced.

HFS Research calls for a Services-as-Software (SaS) Operator, an internal team or managed services partner accountable for the day-to-day performance, economics, and governance of AI once it is live. The operator would coordinate the technology and partners already in place while the enterprise retains its business context, policy, decision rights, and legal accountability.

The research also indicates a growing demand for a new operating model. Sixty-three percent of respondents recognized the proposed operator role as meaningfully different from what they buy today, while 73% said they would pay a premium over raw infrastructure for a fully managed AI service with governance accountability. However, providers must demonstrate clear operational responsibilities and measurable outcomes to earn that premium.

The study was conducted between August and September 2026, surveying enterprises with at least $100 million in annual revenue across eight industries and four regions. All respondents were running AI pilots or more advanced programs, with 83% operating AI in production or beyond.