Run a Nashville AI workflow discovery workshop that produces decisions

Prepare evidence instead of a feature wish list

Ask participants to bring a normal request and a difficult one, with sensitive information removed where appropriate. Capture the current systems and the point where each person receives or hands off responsibility. Avoid circulating production credentials or unnecessary customer records as workshop materials.

For a small Nashville business, the owner may fill several roles. Make those roles explicit even when one person occupies them all. For a larger Middle Tennessee team, include the downstream employee who fixes incomplete work. Their perspective often explains why an apparently quick task creates rework later.

Walk through the process without skipping steps

Start at the event that triggers work and continue until the next team can use the result. Ask what each person knows at that moment and which source they trust. Record decisions separately from data entry. A manual copy step may be easy to automate while the preceding judgment remains unclear.

When people disagree about the correct sequence, preserve the disagreement as a question. Do not let the diagram imply a settled process that participants have not accepted. An AI project built on an unresolved operating rule will inherit the same ambiguity.

Rank candidates with visible reasoning

Compare frequency, employee effort, data readiness, and the consequences of a mistake. Keep those dimensions separate so participants can challenge an assumption. A frequent task with accessible records can be a better candidate than an impressive idea that depends on unavailable data.

NIST’s AI Risk Management Framework is a reference for considering context and risk. Our workshop approach translates that concern into a short register: what the system may read, what it may change, how people check it, and how operations continue when it cannot complete a case.

Reference: NIST: AI Risk Management Framework

Close with a testable next step

Assign an owner to every unresolved question and agree on the examples that will be used in a feasibility test. The output can be a one-page brief plus the workflow map. It should include the boundary of the pilot, the expected handoff, and the decision that follows the test.

Agentix discovery work can connect the workshop to implementation and team training. Ask for editable working documents so your staff can correct them after the meeting. The value of discovery is the decision it enables, including a well-supported decision to simplify the process before adding AI.

Reference: Agentix (publisher): Agentix services

Common questions