Organizations are struggling to maintain control over AI agents as adoption spreads across disconnected tools and workflows, according to monday.com’s 2026 AI report, published October 21.

The report draws on a survey of 1,701 directors and senior managers across seven countries, commissioned by work-management company monday.com and conducted by Nielsen. 

Although 96% of respondents said they use AI at work, only 29% said AI was fully integrated into a centralized operating system. Meanwhile, 57% reported that their organizations were using more software tools after adopting AI.

The survey also found that 46% of respondents worried about losing control over AI agents’ actions, while 52% were concerned about agents accessing data without sufficient restrictions. 

The findings point to an AI governance challenge for organizations connecting AI tools and agents to enterprise systems: adoption can expand before access controls and oversight mechanisms are in place.

Fragmented Systems Make Agent Access Harder to Govern

For Chief Data Officers (CDOs), the findings highlight the need to maintain visibility into which AI agents can access organizational data, what actions they can perform and whether those activities comply with enterprise policies.

When AI tools operate across disconnected systems, enforcing consistent permissions and tracking how data is used become more difficult. Agents that can retrieve information or take actions across applications also introduce questions about whether existing access controls are sufficient for systems that can execute multistep tasks.

Organizations need clear rules governing agent identities, data permissions and the actions agents can take without human approval. Audit logs and monitoring can help teams trace agent activity, investigate unexpected behavior and establish accountability when something goes wrong.

These priorities are central to enterprise AI governance. As AI adoption expands, CDOs and their counterparts in security, IT and risk management need a shared view of how agents interact with enterprise data and systems.