An RFQ Arrived. Who Owns the Next Action?

An RFQ lands in a shared inbox with a PDF attachment. Sales reads it, operations needs to confirm capacity, procurement needs supplier pricing and somebody must remember the response deadline. An AI agent is useful when its job is explicit: capture the request, create the work item, gather approved context and route the next step.

Micro AIPublished 10 September 2026Reviewed 8 September 20265 min read

The problem is usually a handoff

Consider this manufacturing scenario. An RFQ lands in a shared inbox with a PDF attachment. Sales reads it, operations needs to confirm capacity, procurement needs supplier pricing and somebody must remember the response deadline.

The request is not lost, but it sits between teams because no single person can see the whole chain. This is an illustrative operating scenario, not a claim about a named customer. The point is to make the workflow visible before talking about software.

Why the obvious automation is not enough

An AI agent is useful when it has a defined job, known inputs, limited permissions and a clear completion state. The important question is not whether the model can take an action, but whether the business has authorised that action in this situation.

An AI agent is useful when its job is explicit: capture the request, create the work item, gather approved context and route the next step. For a sales operations manager, that means the design should make responsibility clearer after automation than it was before. If staff still need to ask who owns the next step, the technology has not solved the operating problem.

A practical way to improve it

A useful pilot begins with one measurable workflow and representative real-world inputs. Test the routine path, then deliberately test the awkward cases that normally create manual chasing, duplicate work or uncertainty.

Capture deadline, requester, scope and attachment at intake
Assign a named owner for each stage
Escalate missing data instead of inventing it

Keep the human decision where it belongs

Automation should not turn missing context into a confident guess. High-impact decisions, unusual exceptions and actions outside an approved boundary should stop or route to an authorised person. The handover should include the source information, current status, reason for escalation and the action that is still required.

This is also where measurement becomes useful. Track elapsed time, manual handling, exceptions, rework and unresolved items. A faster automated step is not a meaningful improvement if the end-to-end job still waits somewhere else.

One question to take back to your team

If this task were a job description, what exactly would the agent be allowed to do without asking a person?

Write the answer in plain business language before choosing a model, agent framework or integration. The strongest automation projects usually begin with a clear operating problem, not with a list of AI features.