Where AI automation helps
Look for a process with a repeatable starting point and a result someone can check. An enquiry arrives, a document needs classifying, or approved information needs turning into a draft. The work may cross several tools, with a person copying information between them.
Automation connects the steps. AI can help interpret unstructured input or prepare an output; fixed rules handle the predictable parts. An approval step gives the responsible person a clear place to check the work.
Example: from an enquiry to a reviewed draft
- Receive. An authorised form or inbox provides the request.
- Interpret. Propose a category, summarise the need and identify missing information.
- Prepare. Draft a response or an internal handover using approved service information.
- Review. A person checks the output and resolves missing details.
- Complete. Perform only the agreed follow-up actions and record the outcome.
This is an illustrative project scope. An initial pilot can stop at the reviewed draft. Sending messages or updating customer records can be considered separately, once permissions and testing are agreed.
What the implementation includes
- Process map & scope
- The trigger, inputs, tools, outputs and exceptions, with a defined first release and acceptance criteria.
- Connections & logic
- The agreed integrations, field mappings, prompts or rules, with access limited to the work the system needs to perform.
- Review & recovery
- Approval points, visible failures and a route for correcting or retrying a task without duplicating actions.
- Evaluation
- Representative examples, expected outputs and checks for missing information, wrong categories and failed connections.
- Handover
- Operating instructions, account access and guidance for changing the workflow. Ongoing monitoring or support is agreed explicitly.
Estimate the time a workflow could free up
Compare the current workload with the review, exceptions and upkeep a proposed automation would still require. Use estimates first, then replace them with measurements from a pilot.
Worked example: 200 tasks at 12 minutes each take 40 hours a month. With 3 minutes of review per task, 10% needing an extra 12 minutes, and 2 hours of upkeep, the proposed workload is 16 hours. The difference is 24 hours of potential capacity.
How the estimate works
Current hours = tasks × current minutes ÷ 60. Proposed hours = tasks × (review minutes + exception rate × extra minutes) ÷ 60 + monthly upkeep. The difference can be negative if the new workflow adds work.
This estimates staff time, not cash savings. It excludes implementation time and software costs. It does not assess output quality or whether the workflow is suitable for automation. Test those separately before making a decision.
Start with a pilot you can compare
Record how the task runs today: frequency, hands-on time, common mistakes and the effort of checking the result. Select examples that include ordinary work and the exceptions people remember having to fix.
Compare those same cases after the build. Review time, missed information, correction effort and operating cost all matter. Expand the workflow when the evidence supports it and someone can maintain the connections.
Use our first AI automation workflow guide to prepare the assessment. For document assistants, agents and other builds, see the broader AI services and custom solutions.
Before automating a workflow
Is AI needed for every automation?
No. Predictable inputs and fixed rules can often be handled with conventional automation. AI is useful when the task needs to interpret information or produce a draft that can be reviewed.
What if a connected tool fails?
The design should make the failure visible, preserve enough context to resolve it and avoid repeating completed actions. The project scope includes recovery behaviour and the person responsible for exceptions.
Can you guarantee a time saving?
The result needs to be measured against your current process. The workload calculator is a planning estimate; a pilot checks whether review, exceptions, maintenance and output quality support the expected benefit.
What should I send for an initial discussion?
Describe the recurring task, the tools involved, how often it happens and what a good result looks like. Include a redacted example if available. We can then define the questions and a sensible first scope.