Design Thinking with AI: Turn Business Needs into Better Workflows
Use observation, prototypes and user feedback to decide where AI can help a business process.
Key takeaways
- Understand the user’s task before choosing a tool.
- Test a small workflow with the people who perform it.
- Use observed evidence to revise the idea.
Observe the work before proposing AI
Ask staff to show how a task moves from request to completion. Look for missing information, repeated checking, waiting and workarounds. Interview the people receiving the output as well as those preparing it.
Turn observations into a specific problem statement. For example: account managers spend time finding the latest service information before drafting a response. Avoid assuming that every delay requires an AI solution.
Explore several possible responses
Consider a clearer template, better search, simpler rules and AI assistance. Compare the change each option requires. The best choice may combine an improved process with a limited AI step.
Google’s People + AI Guidebook is a reference for human-centred AI design. Keep the user’s ability to understand and control the workflow in view.
Prototype the smallest useful workflow
Prepare a draft interface or manually supported example before integrating systems. Show what information enters, what the AI proposes, where the source appears and how a person accepts or rejects the result.
An illustrative proposal assistant could produce an outline from an approved brief. Ask a user to check missing requirements and explain what they would change before testing automatic document creation.
Test behaviour, not enthusiasm
Give participants realistic tasks and watch where they hesitate or correct the output. Include an unclear request and a missing source. Ask whether the workflow helps them complete the task accurately.
Record review effort, errors and unresolved questions alongside feedback. A positive reaction to a demonstration is not enough to justify deployment.
Turn findings into a pilot decision
Summarise what you learned, what changed and what remains uncertain. Select an owner and acceptance criteria for the next experiment.
Use AI use case prioritisation to compare ideas, then move into a contained AI adoption pilot.
Sources and further reading
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