Protegrity Research Reveals the Hidden “AI Friction Tax” Holding Back Enterprise AI

By Protegrity

Jul 30, 2026

Summary

5 min

New research identifies an “AI friction tax” slowing enterprise deployment:
An independent report produced by Enterprise Management Associates finds that security, governance, and compliance processes are contributing to delayed AI projects, reduced capabilities, and added operational costs.
More than four in five organizations report delays or compromises:
The research found that 82.9% of organizations have experienced production delays because of security or compliance reviews, while 81.6% have deployed AI with diminished capabilities because of security concerns.

Independent EMA research finds more than four in five organizations have delayed AI deployments—or launched them with reduced capabilities—because of security and governance challenges

MENLO PARK, Calif. – July 30, 2026 – Protegrity, a global leader in data and knowledge security, today released 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 preventing organizations from realizing the full value of enterprise AI. It finds that security, governance, and compliance processes have become some of the biggest obstacles to moving AI projects into production.

“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 us 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 while enterprise AI investment continues to accelerate, organizations are struggling to move projects from pilot to production without delays or compromises.

Key Findings From the Report

82.9% of organizations say security or compliance reviews have delayed AI projects from reaching production.
More than two-thirds of delayed AI initiatives remain stalled for at least one month, with nearly 30% delayed for four months or longer.
81.6% report deploying AI in a diminished state because of security concerns, including reduced agent autonomy or restricted access to critical enterprise data.
47.4% identify reducing manual audit and compliance costs as the most valuable business outcome of improved AI data security and governance.

Taken together, the findings identify what the report calls the “AI friction tax”: the hidden cost organizations absorb through delayed deployments, reduced AI functionality, and mounting governance overhead.

These challenges do not stem from a lack of AI investment or technical capability. They are increasingly tied to the processes enterprises rely on to protect sensitive data and manage risk.

“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 also highlights a widening disconnect between enterprise AI ambitions and the infrastructure supporting them. While nearly 70% of surveyed organizations already operate AI agents capable of taking actions such as writing to databases or triggering APIs, only one in five report deploying highly autonomous AI systems.

Governance limitations, data protection concerns, and compliance requirements continue to constrain AI capabilities long after development is complete, limiting business impact despite growing investment.

The report concludes that organizations making the greatest progress with enterprise AI will be those that modernize governance alongside innovation. This means embedding data protection into AI workflows rather than relying on manual reviews and legacy security processes that slow deployment and constrain capability.

Read the full report:
The State of AI Friction: Why Enterprise AI Deployment Is Slower, Costlier, and More Limited Than Expected

Go beyond the findings:
Data Friction Is a Tax on AI

About Protegrity

At Protegrity, we provide data protection for AI and modern applications, securing sensitive data while enabling enterprises to unlock insights, accelerate innovation, and meet global compliance with confidence. From emerging AI to quantum threats, our flexible and forward-looking approach ensures data protection evolves as technology advances. With developer-friendly tools such as SDKs, APIs, and containerized services, we make it easy for teams to embed strong data protection into applications and workflows, securing innovation at scale.

About EMA

Founded in 1996, EMA is a leading IT research and consulting firm dedicated to delivering actionable insights across the evolving technology landscape. Through independent research, market analysis, and vendor evaluations, EMA empowers organizations to make well-informed technology decisions. Its analysts combine practical experience with a deep understanding of industry best practices and emerging vendor solutions to help clients achieve their strategic objectives.

Learn more about EMA research, analysis, and consulting services at enterprisemanagement.com.