Workflow design
When to build AI into a workflow
Add AI when it improves a defined task and the team can assess the result.
Cortez Lake
Assess whether a workflow needs AI, conventional automation, or a process change by examining the task, available information, review burden, and cost of errors.
Name the problem before choosing the technology
Map the work from the first input to the completed outcome. Identify where people wait, repeat work, search for context, or make decisions without enough information. Then ask whether the bottleneck needs a process change, a straightforward rule, an integration, or AI.
For example, routing a request by a known account number may only need a rule. Summarizing a varied collection of documents for a reviewer may warrant testing a model. The choice depends on the task and the evidence available to assess its output.
Look for a task with a reviewable result
A useful candidate has identifiable inputs, a defined output, and a way to judge whether that output helps. Drafting, summarization, and classification can fit when someone can review the result using the underlying information and the task has clear boundaries.
Include that review effort in the assessment. A draft that takes longer to verify than to write may not improve the workflow. Likewise, moving work out of one queue can create more work for the team responsible for exceptions.
- Define what a correct and useful result looks like.
- Identify who can verify the result and what context they need.
- Estimate the consequence of an error and the work required to recover.
Recognize the reasons to wait
A workflow is a weak candidate when ownership is unresolved, necessary data is unavailable, or the team cannot explain how outputs will be evaluated. Automating an unclear process can make its problems harder to locate.
Address those gaps before funding a build. If existing software or a simple process change resolves the problem, use it. AI should have a defined advantage worth testing, rather than a place reserved for it in every workflow.
Test the whole workflow in a scoped pilot
Agree on a baseline, representative examples, and the measures that will inform the next decision. Include quality, elapsed time, reviewer effort, exceptions, and the experience of the people doing the work. Keep sensitive actions subject to the agreed controls.
A workflow pilot should end with evidence for a scale, revise, or stop decision. Expansion into production is a subsequent decision with its own operating owner, release criteria, and responsibilities. H2H uses that boundary to keep an experiment from becoming an unplanned production commitment.
Next step
Find the part of the workflow worth changing.
See how H2H defines the task, tests the proposed improvement, and helps your team decide what should happen next.