Planning guide · Hyperlinq Technology

How to identify workflows worth automating

A practical planning guide for ai automation.

Start with the business decision

Teams handling repetitive enquiries, CRM updates, reporting, or operational data across disconnected tools. Start by identifying one business goal, a decision-maker, and the constraints that will shape the engagement. A useful brief explains what needs to change and how you will assess the work.

What should you compare in proposals?

  • Workflow mapping and feasibility assessment
  • Integration design with agreed systems and permissions
  • Automation implementation, exception handling, and testing
  • Documentation, handover, and an agreed support plan

Compare proposals against the same scope. A lower headline fee may exclude production, tools, advertising spend, implementation, or ongoing support. Ask for a written breakdown rather than assuming these costs are included.

Which tasks should stay under human review?

Approvals, sensitive decisions, and uncertain AI outputs need a defined review path. Access permissions, data handling, monitoring, and fallback procedures should be agreed before a workflow goes live.

Which workflow is a sensible first candidate?

Look for a repeated task with stable inputs, clear rules, and a measurable baseline. Record task volume, time spent, error rate, tool costs, and the review effort needed after automation. Start with a limited pilot and a manual fallback.

Questions to settle before signing

  • What is included, and what is explicitly excluded?
  • Which costs recur and which are paid once?
  • What approvals and source material are needed from us?
  • What is the baseline, reporting period, and data source?
  • What happens at handover or when the engagement ends?

Next step

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Prepared by Hyperlinq Technology. Editorial review: 6 November 2026.

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