Enterprise AI is becoming an operational priority for organizations looking to improve productivity, automate workflows and support business decision-making. Yet many enterprises are discovering that moving AI from pilot to production introduces new challenges that can delay deployments and limit business value.
Protegrity, a global leader in data and knowledge security, today launched The State of AI Friction: Why Enterprise AI Deployment is Slower, Costlier, and More Limited Than Expected, an independent research report produced by Enterprise Management Associates (EMA). Based on a survey of IT and security leaders, the report examines the operational barriers, or “AI friction” as described in the report, preventing organizations from moving enterprise AI from pilot to production and realizing its full business value. The findings show that security, governance and compliance have become major constraints on enterprise AI deployment rather than AI development itself.
“AI has quickly become a business imperative, but many organizations are discovering that getting AI into production is far more difficult than building a proof of concept,” said James Rice, VP of Product Marketing at Protegrity. “This research helps to better understand where those barriers exist and what they’re costing enterprises. The findings show that security, governance and compliance have become critical business considerations that can either accelerate AI adoption or slow it dramatically. Organizations that address this friction will be in a much stronger position to realize AI’s full value.”
The findings indicate that enterprise AI adoption continues to accelerate, yet organizations are struggling to operationalize AI at scale:
- While 37.5% of respondents are scaling AI across multiple departments and production workflows and another 20.4% are deploying autonomous agentic workflows, the research found that 82.9% say security or compliance reviews have delayed AI projects from reaching production.
- More than two-thirds of delayed initiatives remain stalled for at least one month, with nearly 30% delayed four months or longer.
- 81.6% report deploying AI with reduced capabilities due to security concerns, reducing agent autonomy or restricting access to critical enterprise data.
The report identifies the combined impact as the “AI friction tax,” the hidden cost organizations pay through delayed deployments, reduced AI functionality and manual governance processes. Rather than reflecting a lack of AI investment or technical ambition, these findings suggest enterprises are struggling to build the operational infrastructure needed to support production at AI scale.
“Security, governance and compliance are now the primary barriers preventing enterprises from moving AI into production at the pace the business demands,” said Chris Steffen, Vice President of Research, Information Security at EMA “The findings make clear that many organizations are compensating by deploying AI with reduced capabilities rather than the functionality originally intended. That compromise is widening the gap between AI investment and business value, while adding avoidable costs, delays and operational inefficiencies.”
The report further highlights a widening gap between enterprise AI ambitions and the infrastructure supporting them. Nearly 70% of surveyed organizations already operate AI agents capable of taking actions such as writing to databases or triggering APIs, yet only 19.7% report deploying highly autonomous AI systems. These findings suggest that enterprise AI infrastructure has not kept pace with governance, data access and operational requirements needed to support autonomous AI at scale.
The report concludes that organizations making the greatest progress with enterprise AI will be those that modernize the operational infrastructure supporting AI alongside innovation, embedding governance and data protection directly into AI workflows so production systems can scale without sacrificing capability or trust.
The post Protegrity Research Highlights Barriers to Enterprise AI Adoption first appeared on AI-Tech Park.
