AI agents are usually discussed as a leap toward independence: software that can act, decide, summarize, schedule, and move work forward without waiting for another prompt. For professional services firms, the appeal is evident. The real challenge lies in establishing trust.
In a recent study, it was examined how they use and perceive AI agents. Respondents were open to agents doing more, as long as that autonomy came with control.
In the report, control appeared less as a broad principle and more as a set of practical conditions. Teams wanted agents that make their work visible, keep outputs reviewable, allow people to step in, and make data access clear.
First, Show the Work
Before professional services teams trust an AI agent to act, they need a clear view of what is happening. Productive’s research puts it simply: people want to see what the agent is doing and why.
If an agent is preparing, suggesting, updating, or summarizing something, the person responsible for the work needs to understand what is happening before they can trust the result. Visibility gives teams something concrete to judge. Without it, they are not really trusting the agent. They are trusting the surface of the answer.
Nothing Should Take Effect Without Review
Visibility helps people understand what an agent is doing. Review gives them the chance to decide whether the output should be accepted.
Respondents described “human in the loop” less as a nice extra and more as an expected standard. In professional services, that standard carries weight: unchecked output can affect billable time, delivery risk, resourcing, or client expectations.
A review is not meant to slow the agent down. It marks the point where AI assistance becomes work a person is willing to stand behind.
There Has to Be a Way to Step In
Once an agent starts moving, teams need a way to correct its course.
The research also showed that professional services teams want the ability to pause, adjust, or undo an agent’s actions. The request is practical, not overly cautious. AI can misunderstand instructions, miss context, or hallucinate.
Teams do not need agents that wait for permission at every step. They need AI agents that can keep moving without leaving people feeling locked out of the process.
Teams Need to Know What the Agent Can See
If an AI agent is going to be useful, it needs context. That is also where trust gets more complicated.
In Productive’s research, data access was one of the clearest issues concerning control. People expressed a desire to know which information an agent could use, where that data might go, and whether the agent could surface information it shouldn't. Their concerns were specific: privacy, security, GDPR, storage, and over-permissioning.
One respondent captured the risk well: an over-permissioned agent who has been asked to summarize recent attachments could expose confidential information, such as a salary spreadsheet.
Before agents can act across projects, documents, finances, or people data, professional services teams need a clear answer to the question: what data can this agent access?
The Future Is Not Full Autonomy. It Is Supervised Autonomy
The Productive’s report points to a clear threshold for professional services teams. They may be ready to hand over more repetitive work around projects, but only when they can see what is happening, review the output, step in when needed, and understand the data being used.
A 2025 Gartner survey points in the same direction. While 75% of IT application leaders said their organizations were piloting, deploying, or had already deployed some form of AI agent, only 15% were considering, piloting, or deploying fully autonomous agents that do not require human oversight.
Productive’s AI Agents match this idea of bounded autonomy. Agents can work when people do not, but within the boundaries those people set. Teams can schedule them to act on their own or prompt them directly when needed.
Professional services teams do not want AI agents that can do everything. They want agents they can trust to handle the work that slows them down, without losing control over how it gets done.
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