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Automation

Is your workflow ready for AI automation?

Before an automation pilot, check process stability, data, access and exception handling. An uncertain answer calls for preparatory work; it does not establish that your organisation is ready.

Binov · 2 min ·

In this guide

This checklist helps you assess readiness before committing budget and change management effort.

A readiness list with an action for every no

Fictional example: a team wants to classify requests, but its categories change every week. The first step is to stabilise the rules and name their owner before automating classification.

For each row, choose yes, no or needs clarification and record evidence. A “yes” applies only to the observed scope; do not add responses together to calculate a maturity score.

Criterion Answer and evidence Owner Next action if no or uncertain
Sufficiently stable process … Business: … Document variants and agree the current rules
Usable data … Data: … Correct a representative sample and check sources
Available access … Engineering: … Obtain permissions and test their limits
Recognised exceptions … Operations: … List ambiguous cases and organise human handover
Assigned accountability … Decision owner: … Name who approves, monitors and can stop the workflow
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Then decide on a limited trial or preparatory work. An unresolved point may block a sensitive action even if every other row is positive. A pilot must check actual conditions, not just the existence of a document.

1) Process readiness

Confirm the target workflow is documented, repeatable, and owned by a team that can manage exceptions.

If the baseline process is unstable, automation will amplify inconsistency.

2) Data readiness

Validate data quality, access permissions, and update frequency.

Production automation depends on reliable inputs more than model sophistication.

3) Control and accountability

Define who approves decisions, who handles fallbacks, and which logs are required for audits.

Operational clarity reduces risk when automation decisions affect customers or finance.

4) Rollout sequencing

Start with one bounded workflow, instrument it, and scale after performance is proven.

Avoid large cross-team launches before reliability baselines are met.

5) Change adoption

Train owners, document expected behavior, and track adoption metrics in weekly cadence.

Move your workflows forward with fewer manual tasks.

Identify repetitive steps and connect your tools with explicit rules, checks and exception handling.

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