The decision this supports
Leave the selection meeting with one bounded workflow, an accountable owner, a baseline to measure, and the next uncertainty to resolve.
For business sponsors and transformation leads
01 / Decision guide
Start at the point where work gets stuck
“Use AI in customer service” describes an ambition. “Prepare a complete onboarding case for a reviewer” describes work you can inspect. Define its trigger, inputs, completion condition, and accountable owner before comparing models or platforms. The boundary should be small enough to test and meaningful enough that improving it changes somebody’s day.
Walk through recent cases with the people who did the work. Note where they searched for information, copied it between systems, asked for clarification, or waited for a decision. Distinguish effort from elapsed time: a case can spend three days in a queue while requiring only twenty minutes of handling. Faster document preparation will not remove a separate approval bottleneck.
Write the candidate in one sentence: when a specified event occurs, help a named role complete a defined task using approved information, with a stated person or system accepting the result.
02 / Decision guide
Compare opportunities without hiding the blockers
Use a short decision record for each candidate. A numerical score can help discussion, but a high total must not conceal unavailable data, missing permission, or an owner who cannot accept the work. Treat those as prerequisites to resolve before committing to implementation.
Scroll across the table to read all columns.
| Dimension | Evidence to bring | Reason to defer |
|---|---|---|
| Value | Observed handling time, case volume, errors, and the downstream consequence of delay. | The benefit depends entirely on an untested assumption. |
| Feasibility | Representative inputs and an inspected integration path. | Access or source ownership is unresolved. |
| Acceptance | Examples of acceptable work and who can judge them. | Nobody can explain how success will be tested. |
| Adoption | A participating operating owner and reviewers with time to evaluate. | The people expected to use it are absent from the decision. |
Keep uncertainty visible. “We need to examine twenty representative cases” is a better next step than treating an unverified effort estimate as a fact. The appropriate sample depends on the variety and consequence of the work; no fixed count establishes readiness.
03 / Decision guide
Check whether AI is the appropriate mechanism
A deterministic rule may be enough to route a form with complete structured fields. A language model may help interpret inconsistent documents or prepare an explanation. A fixed sequence of steps may be easier to evaluate than an agent that chooses its own next action. Choose complexity only when it improves the specific task.
Anthropic’s Building effective agents distinguishes predefined workflows from model-directed agents and recommends beginning with simpler approaches. Our practical application is to compare an existing application feature, conventional automation, and an AI-assisted design against the same acceptance criteria.
Include the cost of integration, reviewer effort, ongoing evaluation, source maintenance, and support in that comparison. A cheap model call does not establish a cheap operating capability.
04 / Decision guide
Make the economics explicit
For a capacity hypothesis, calculate eligible case volume multiplied by the change in total staff effort per case. Include preparation, review, corrections, and exceptions. Then account for recurring operating effort and technology cost. Separate time that could be redeployed from cash savings that require an actual change in expenditure.
Illustrative calculation
At 600 eligible cases a month, reducing preparation from 20 to 8 minutes while adding 4 minutes of review releases 80 staff hours before ongoing support effort. Those inputs are assumptions for a worked example, not a PrismWorks customer result. If review takes 12 minutes, the estimated capacity benefit disappears.
Test the sensitive assumptions first. Confirm eligible volume, compare difficult cases as well as easy ones, and ask the operating owner how any released capacity would be used. A modest measurable improvement can be a better first engagement than a larger claim with no credible path to adoption.
05 / Decision guide
End with an investment decision
Choose a next action with an owner: adopt an existing capability, improve the process, commission a bounded implementation, investigate a specific uncertainty, or stop. Record what would change that decision. A short assessment is useful when it resolves a decision; producing a longer opportunity list is not enough.
For an implementation, specify the permitted inputs and actions, human approvals, acceptance cases, operating owner, and a controlled rollout boundary. Agree the evidence needed to expand. A successful first workflow should create learning and reusable operating practices as well as a useful outcome.
Use the workflow decision brief to bring the business, technology, and operating owners into the same conversation.