Conshohocken, USA: Adoption of AI agents among enterprises has been growing rapidly in recent years, however, many enterprises are not confident with those deployed AI agents and their actions.
New commissioned research conducted by Forrester Consulting on behalf of Boomi, reveals that despite rapid adoption of AI agents, trusting deployed AI agents and their actions remains a concern for many enterprises.
86% of organisations have moved beyond the AI agent pilot stage, but just 34% say they trust the actions their AI agents are taking, according to a new research findings.
Study highlights include:
• 77% of organisations in agentic chaos are moving to full agent deployment despite insufficient readiness
• 45% of agentic control leaders gate AI pilot decisions on having well-managed APIs, vs. just 15% of their peers
• Organisations with agentic control are seeing 59% productivity gains and 51% increased innovation from their agentic AI deployments
Among organisations in a state of “agentic chaos” (the bottom quartile for operational readiness across governance, integration, API/MCP management, and other categories), 77% are moving into production.
However, as per the study, these organisations are exposing themselves to an average of $2.1 million in added costs from compliance fines, lost customers, operational downtime, and rework.
Organisations with “agentic control” (the top quartile for readiness) are far more measured, and far more confident: 55% report high confidence in their agents’ actions and decisions, compared with just 22% of those in agentic chaos. Forrester surveyed 409 director-and-above IT and technology decision-makers across North America, Europe, and APAC.
Deployed AI Agents and Trust Deficit
“This research confirms what we’re seeing everywhere: the trust problem with agentic AI is really a data problem,” said Steve Lucas, Chairman and CEO of Boomi, the data activation company for AI.
“Agents can only be trusted to act on data that’s been properly activated, connected, and governed, and most companies deployed agents before they did that work. The ones who did it first are the ones getting real value now,” added Lucas.
Integration Leads Trust
The study identified integration as the fine line between those enterprises that trust their agentic AI and those that don’t. Decision-makers with agentic control were three times as likely as those in agentic chaos to say reliable, well-managed APIs determine whether they pilot a use case at all.
Integration platform as a service (iPaaS) showed the widest adoption gap of any method surveyed: 46% of organisations with agentic control use iPaaS to support agentic workflows, compared with just 25% of those in agentic chaos.
The gap is even wider when it comes to building the agents themselves. 86% of organisations with agentic control say iPaaS and API management capabilities are vital for building AI agents and their readiness, compared with just 58% of those in agentic chaos: the single widest gap Forrester measured in the entire study.
Leaders with agentic control were also far more likely to prioritise the operational work behind the scenes: 47% cite improving integration with tools, APIs, and apps as a top focus area, versus 31% of those in chaos, who remain focused on improving the AI model itself without building the connections needed to act on its decisions.
That same gap shows up in how organisations are handling agent sprawl. Some are now running as many as 200 agents, a symptom of what Forrester calls “POC/pilot purgatory,” where high ambition for AI agents stalls out. Because those agents were never connected to the enterprise systems for which they would need to act on their decisions.
Leaders with agentic control are far more likely to get ahead of this: 46% have established central governance of MCP, the standard that lets agents connect to enterprise systems safely, compared with 32% in chaos, and 48% have aligned their AI and integration teams under one operating model, compared with just 37% of their peers still in chaos.
The Payoff
The organisations investing in a strong integration layer are the ones seeing it pay off. Among those with agentic control, 59% reported productivity gains from their agentic AI deployments and 51% reported increased innovation. While, 46% gained reusable capabilities they could apply elsewhere in the business and 45% automated repetitive tasks.
Enterprises and organisations looking to close the trust gap need to align their AI and integration teams under one operating model. They should implement a control plane to govern AI agents, and introduce an orchestration layer that gives AI agents the reach to connect to data, applications, and each other.
Do enterprises trust deployed AI agents and their actions?
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