AI Workflow Reset · Capability inside
Start with one workflow.
Find and improve the repeated knowledge work using up the team’s time. Start with a workflow review in the tools the team already uses.
Identify the workflowThe starting point
Good knowledge.
Too much rework.
- A repeatable task
Research, proposals, briefs or sales material that the team produces regularly.
- Usable sources
Documents and knowledge the team has permission to use.
- Someone who owns the result
A named person who can check quality and help the team adopt the workflow.
The method
Find. Build. Embed.
- Find the friction
Map the inputs, handoffs and output. Agree a baseline and decide whether an AI-assisted pilot is appropriate.
- Build a bounded pilot
Use approved sources, clear prompts and human review. Test representative work before wider use.
- Embed the working method
Agree the owner, review rules and handover. Compare effort, quality and adoption against the baseline.
Illustrative starting points
A clear input.
A useful output.
- Approved research → a checked brief
Keep the source behind each finding visible to the reviewer.
- Product knowledge → a sales draft
Build from agreed claims and examples; flag missing evidence.
- Meeting notes → a reviewed action list
Extract the decision, owner and next action for someone to confirm.
These are example workflow types, not client results. The first conversation establishes fit; implementation scope follows the diagnostic.
The scope
One workflow.
Clear controls.
Work starts with permission to use the sources, a named reviewer and a practical measure of improvement.
Enterprise platform replacement, custom software products, ongoing IT support, staff monitoring and sensitive-decision automation sit outside the initial offer.
Where the source material also needs a clearer story, a Narrative Reset can sit alongside it.