New HFS Research and Rackspace Study Finds Only One-Third of Enterprises Realize Expected AI Value
Key Highlights
- ➤33% of enterprises met or exceeded their most significant AI business case
- ➤96% report significant AI governance gaps
- ➤AI business-case achievement falls to 28% for multi-function deployments
- ➤73% would pay a premium for fully managed AI with governance accountability
- ➤Rackspace (RXT) proposes accountable AI operations as enterprises move into production
Expert Statements
Phil Fersht, Founder and CEO of HFS Research
“Enterprise AI has an accountability problem that nobody in the industry wants to admit”
Phil Fersht, Founder and CEO of HFS Research
“We’ve built an enormous ecosystem of companies selling models, platforms, infrastructure and consulting, yet when the promised results don’t materialize, everyone points at someone else and the enterprise is left trying to make the pieces work together.”
Phil Fersht, Founder and CEO of HFS Research
“Only a third of enterprises have met the business case for their most significant AI program, which should force us to confront how addicted we’ve become to selling AI rather than taking responsibility for making it work.”
Phil Fersht, Founder and CEO of HFS Research
“We have no shortage of technology or talent, but we are missing people and partners willing to take ownership of how the whole system operates once it goes live and whether it actually delivers what the business needs.”
Phil Fersht, Founder and CEO of HFS Research
“Until that accountability exists, enterprises will keep paying for parts that never add up to the outcomes they were promised.”
Gajen Kandiah, CEO, Rackspace
“Turning AI investment into measurable business value requires clear operational accountability”
Gajen Kandiah, CEO, Rackspace
“As enterprises move from pilots into production, infrastructure readiness, security, governance and cost have to be managed together.”
Gajen Kandiah, CEO, Rackspace
“Customers need an operator accountable for integrating, running and continuously improving the environment across infrastructure, applications, data and AI.”
Gajen Kandiah, CEO, Rackspace
“They should retain control of their data and technology choices, with clear measures of performance and cost, and deployments paced to their business needs.”
SAN ANTONIO and BOSTON, Nov. 12, 2026 (GLOBE NEWSWIRE) -- Enterprises are investing heavily in artificial intelligence, but most have yet to realize the returns they expected. New research from HFS Research, conducted in collaboration with Rackspace, finds that only 33% of enterprises have met or exceeded the business case for their most significant AI program, while 96% report significant governance gaps. The study of 502 senior AI decision makers points to a central obstacle: fragmented accountability for how AI performs, what it costs, and how it is controlled once deployed.
The report, “Run Your AI as One, or Keep Paying for Parts That Never Add Up,” finds that the challenge intensifies as organizations expand AI across multiple business functions. Companies have invested in models, platforms, infrastructure, and services, but too often no one is responsible for running the pieces as one system.
Get started
Create a free account to read the full story.