'The trust problem with agentic AI is really a data problem': New report shows rushing into AI deployment could cost your business big time

Only 34% of organizations say they trust their agents' actions
77% of businesses in 'agentic chaos' have deployed agents
Those organizations are focus on the wrong thing (models and tools)

New Boomi data has claimed while 86% of enterprises have evolved from agentic AI pilots to actual production-level deployment, only 34% trust the actions their agents are taking.

However those trust issues don't stem from model intelligence – Boomi argues that data quality, integrations, governance and controls could be to blame.

The research splits respondents into distinct categories, with the bottom quartile for readiness referred to as experiencing 'agentic chaos'. Among those in agentic chaos, as many as 77% are still moving AI agents into production, highlighting a worrying gap.

AI trust is entirely in the hands of enterprises

With more than three in four of the enterprises in agentic chaos still pushing ahead with their plans, Boomi warns they could face unexpected costs from compliance fines, lost customers and operational downtime.

On the flip side, the top quartile was categorized as being in 'agentic control', and more than half (55%) of them said they're highly confident in their agents' decisions and actions.

Additionally, the report criticizes those in agentic chaos for focusing on the wrong thing, with around half (51%) prioritizing AI model or tool maturity instead of the true causes of distrust.

"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," CEO Steve Lucas wrote.

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At the end of the day, Boomi's data implies that pressure to demonstrate AI value and ROI could actually be leading to premature deployment before the foundations are in place, leaving organizations to play catch-up in a far more inefficient way.

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