AI agents: when to allow autonomy and when to require approval

An AI agent should receive autonomy when a business can explain its assignment, recognize a correct result and stop an inappropriate action. Before connecting tools or delegating decisions, separate three permissions: reading information, preparing a proposal and carrying out an action. Each requires a different level of responsibility.

This choice comes up in everyday work. A system may organize quotation requests without permission to offer discounts. It may draft a customer response without sending it. Its usefulness depends on which part of the work has been delegated and who remains responsible for the outcome.

What the news comparison tells us

On June 25, 2025, Reuters covered Gartner's prediction that over 40% of agent projects would be canceled by the end of 2027. That is a forecast. Associated Press reporting on October 30, 2025, described professional documents containing false references generated with AI assistance.

The stories address different issues: project viability and observed errors in completed work. The second does not validate the first forecast. Our combined reading is that a purchasing decision should consider both the expected benefit and the business's ability to check what the system produces.

Rule-based automation and agents are different choices

Anthropic's documentation distinguishes predefined paths from systems in which the model decides how to organize steps and use tools. That distinction supports a straightforward question: does this task need to choose a path, or simply follow an established sequence?

Consider an inquiry submitted through a form. Checking that a phone number is present and sending the inquiry to a queue can follow clear rules. Interpreting an incomplete request calls for judgment. Even then, the first version could merely suggest a category for someone to confirm.

Create an authorization sheet for each task

Instead of granting broad access to an entire department, describe each activity on a short authorization sheet. Any responsible team member should be able to understand the arrangement without depending on the person who configured the system.

• Input: which information the system may consult, where it comes from and who keeps it current.
• Deliverable: what should exist at the end, such as a draft proposal with every required field completed.
• Boundary: which decisions remain outside the assignment, including changing prices, promising deadlines or making commitments.
• Approval: who checks the work, at which stage, and who substitutes when that person is unavailable.
• Interruption: who may suspend the system and how the team resumes the work manually.

A gradual implementation example

Imagine a Brazilian distributor receiving inquiries about spare parts. This is a hypothetical example. During the first stage, AI organizes topics and drafts answers using the approved catalog. A salesperson checks the product identification, availability and delivery estimate before sending a response.

After evaluating the results, the company might allow automatic answers only for questions about public catalog specifications. Availability and delivery inquiries would still require commercial confirmation. Permissions expand by task, using separate criteria. Correctly describing a product does not automatically qualify the system to negotiate its sale.

Test the situations that should stop the process

A demonstration usually starts with a complete request. A business test should also include missing information, similar product names, repeated requests and conflicting document versions. For each case, write down the acceptable response in advance and specify when assistance is mandatory.

Classify mistakes by their consequences. A category that a team member fixes in seconds differs from a promise already sent to a customer. Count how many deliverables needed correction, how long review took and whether any action exceeded its authorization. Define before testing which events require immediate suspension.

Compare the cost per accepted deliverable, including review, maintenance and discarded attempts. A system that generates many inexpensive answers can still consume too much checking time. If the projected benefit depends on ignoring that work, the calculation is not ready to support expansion.

Keep the initial scope understandable to the people doing the work. They should know what has changed, how to question an output and where to report a repeated problem. A clear operating agreement also makes it easier to assess whether a later change actually improved results.

How Vero 4 approaches the decision

From Vero 4's perspective, automation should support the offer and service the business has promised. The practical recommendation is to select a limited task, document responsibilities and evaluate its effect on operations. Each new permission should follow demonstrated results and customer needs, with a named person responsible for approving it.

Sources and further reading

• Reuters, 2025-06-25.
• Associated Press, via Tech Xplore, 2025-10-30.
• Gartner, 2025-06-25.
• Anthropic, 2024-12-19.