New HFS Research and Rackspace Study Finds Only One-Third of Enterprises Realize Expected AI Value
Reported AI gains were more common in workforce productivity and cost reduction than in customer experience or revenue growth.
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Rhea-AI Summary
Rackspace (NASDAQ: RXT) and HFS Research released a study finding that only 33% of enterprises met or exceeded their AI business case. The survey covered 502 senior enterprise AI decision-makers. Business-case achievement was 37% among enterprises deploying AI in one function, 28% among those deploying across several functions and 56% among those with AI embedded in standard operations. These group comparisons do not establish causation.
96% reported significant governance gaps, and 44% lacked a single, consistent approach to running AI in production. Meanwhile, 61% preferred one accountable partner across models, platforms and infrastructure, and 73% would pay a premium over raw infrastructure for a fully managed AI service with governance accountability. HFS proposes an operator responsible for AI's day-to-day performance, economics and governance.
Details
Market move: RXT -3.83% vs previous close. enterprise AI study
On Nov 12, the day this news came out, the latest delayed price for RXT is 3.83% below the previous close. Our momentum scanner has recorded 5 alerts for this stock so far that day. The latest delayed price is $3.01.
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Key Figures
- Met or exceeded AI business case
- 33%
- Enterprises surveyed; most significant AI program
- Significant governance gaps
- 96%
- Enterprises surveyed
- Survey respondents
- 502 senior AI decision makers
- Enterprise AI survey conducted with Rackspace
- Business case met across several functions
- 28%
- Enterprises deploying AI across several functions
- Governance failures viewed as a scaling threat
- 78%
- Respondents viewed governance failures as a bigger threat than technology failures
- No consistent approach to production AI
- 44%
- Enterprises surveyed
- Prefer one accountable partner
- 61%
- Across AI models, platforms, and infrastructure
- Would pay a premium for managed AI
- 73%
- For a fully managed AI service with governance accountability
AI-generated analysis. How Rhea-AI works. Not financial advice.
Survey of enterprise AI leaders identifies fragmented accountability, unpredictable costs and governance gaps as major barriers to AI returns
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
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.
Key findings from the study include:
33% have met or exceeded their AI business case. The share falls to28% among enterprises deploying AI across several functions.96% report significant governance gaps, while78% view governance failures as a bigger threat to scaling AI than technology failures.44% have no single, consistent approach to running AI in production.61% prefer one accountable partner across AI models, platforms, and infrastructure, rising to74% among production-stage firms whose programs have not delivered.73% would pay a premium over raw infrastructure for a fully managed AI service with governance accountability.
“Enterprise AI has an accountability problem that nobody in the industry wants to admit,” said 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. 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. 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. Until that accountability exists, enterprises will keep paying for parts that never add up to the outcomes they were promised.”
AI business-case achievement varies by deployment stage
The study finds that the share of enterprises meeting or exceeding their AI business case varies by deployment stage. Among enterprises deploying AI in one function,
Most reported gains remain concentrated in efficiency:
HFS calls for an accountable AI operator
To close the gap, HFS calls for a Services-as-Software™ (SaS) Operator: an internal team, group of existing providers under one remit, or managed services partner accountable for the day-to-day performance, economics, and governance of AI once it is live. The operator coordinates the technology and partners already in place while the enterprise retains its business context, policy, decision rights, and legal accountability.
“Turning AI investment into measurable business value requires clear operational accountability,” said Gajen Kandiah, CEO, Rackspace. “As enterprises move from pilots into production, infrastructure readiness, security, governance and cost have to be managed together. Customers need an operator accountable for integrating, running and continuously improving the environment across infrastructure, applications, data and AI. They should retain control of their data and technology choices, with clear measures of performance and cost, and deployments paced to their business needs.”
The research also points to demand for a new operating model:
Read the full report: “Run Your AI as One, or Keep Paying for Parts That Never Add Up”
About the research
HFS Research surveyed 502 senior enterprise AI decision-makers between August and September 2026 in partnership with Rackspace. Respondents worked at enterprises with at least
About Rackspace
Rackspace (NASDAQ: RXT) is the operator of the full enterprise AI stack, bringing together infrastructure, applications, data and AI platforms across private and public cloud environments. Through its Build | Operate | Innovate delivery model, Rackspace combines engineering, infrastructure and continuous operations to help enterprises deploy and operate AI reliably, reduce complexity and realize measurable business value. Building on more than 25 years of experience operating complex enterprise technology, Rackspace helps customers manage AI performance and costs while maintaining control over their data, technology choices and where their AI runs. Its vendor-neutral, model-agnostic capabilities give customers the flexibility to evolve as technology changes. Learn more at www.rackspace.com.
About HFS Research
HFS Research is a global research and advisory firm. We work with Fortune 500 and Global 2000 companies seeking meaningful business transformation, and with the service providers, software companies, and investors that serve them. We exist to close the gap between technology spend and the real business outcomes that make it a lasting investment. We are known for identifying and naming the shifts reshaping business and taking clear positions on what they mean. We have no outside investors to keep happy, and companies cannot pay to influence our research or ratings. For more information, visit www.hfsresearch.com.
Media Contacts
HFS Research
Aubrey Halverson
aubrey.halverson@hfsresearch.com
Rackspace
Gracie LePere
publicrelations@rackspace.com
A photo accompanying this announcement is available at: https://www.globenewswire.com/NewsRoom/AttachmentNg/810b29f9-81ea-4871-8bd3-7bb3def29fff
FAQ
AI-generated questions and answers. How Rhea-AI works. Not financial advice.
What did the Rackspace and HFS study find about enterprise AI returns?
Only 33% of surveyed enterprises had met or exceeded the business case for their most significant AI program. Reported gains included workforce productivity improvements at 58% and measurable cost reductions at 42%, compared with better customer experience at 28% and measurable revenue growth at 21%.
Who participated in the Rackspace and HFS enterprise AI survey?
HFS surveyed 502 senior enterprise AI decision-makers between August and September 2026 at enterprises with at least $100 million in annual revenue, across eight industries and four regions. All participants were running AI pilots or more advanced programs; 83% operated AI in production or beyond. The blind survey named no vendor, platform or provider and describes AI-active enterprises, not market-wide adoption.
What responsibilities would enterprises retain under the HFS proposed AI operator model?
Enterprises would retain their business context, policy, decision rights and legal accountability under the proposed model. The operator could be an internal team, existing providers under one remit or a managed services partner, coordinating technology and partners already in place.