AI Without Guardrails? Study Finds Rapid Agent Adoption Despite Governance Gaps
The latest BARC research study, Preparing and Delivering Data for AI: Adoption Trends, Requirements, and Best Practices , finds that organizations are rapidly adopting AI, with nearly one-third already deploying AI agents in production. However, a lack of structured governance, data quality focus, and AI skills threatens long-term success.
“AI is moving fast, but many organizations are still operating without the necessary guardrails,” said Shawn Rogers, CEO of BARC US. “To realize AI’s full potential, companies must prioritize data quality, responsible governance, and workforce readiness.”
AI Progress with Mixed Maturity
While more AI adopters meet their cost and revenue goals than fall short, fewer than half consider data quality and model accuracy as top success measures — critical factors for reliable AI outcomes. Additionally, only 21% of organizations have enterprise-wide AI programs covering legal, compliance, and security aspects, a figure unchanged from last year.
Figure: Is your organization using or considering using AI agents for the following aspects of data management? (n=286, Source: BARC research study “Preparing and Delivering Data for AI”)
Responsible AI and Workforce Readiness
Most companies recognize the importance of Responsible AI, focusing on privacy, security, and compliance. However, fewer prioritize human-AI collaboration, despite the AI skills gap being the second-largest challenge. Two-thirds of organizations are addressing this by upskilling staff, creating centers of excellence, or hiring AI talent.
Leaders vs. Followers: A Growing Divide
The most successful adopters—AI Leaders—achieve higher business outcomes and show stronger governance maturity. They automate processes more extensively and run AI applications on cloud and hybrid platforms, while less mature adopters focus on tool procurement. AI Leaders also adopt AI agents at a significantly higher rate.
North America Leads in AI Maturity
North American firms surpass European counterparts in AI-driven data management, comprising nearly all respondents who exceed their AI goals. AI agent adoption in North America is five times higher than in Europe, widening the regional maturity gap.
Conclusion
As AI adoption accelerates, organizations must strengthen governance, enhance data quality, and close the AI skills gap. Without these foundational elements, the risks of unreliable AI decisions and inefficiencies remain high.
“Organizations that take a structured approach to AI—focusing on data quality, governance, and talent—will be the ones that lead in innovation and business success,” added Shawn Rogers. “The gap between AI Leaders and Followers is widening, and companies that fail to act now risk falling behind.”
The respondents come from around the world, with a clear focus on Europe and North America. A total of 370 fully completed questionnaires were evaluated. Participants were required to have solid knowledge of their company’s data and AI strategy as well as relevant projects. Individuals without project experience were excluded from the survey.
The study is available free of charge thanks to the sponsoring of Informatica, Boomi, Domo, Unstructered and Dremio.
