Automation is not the goal
Most enterprises confuse automation with optimisation. Automation makes an existing process faster. Optimisation asks whether the process should exist in that shape at all. AI process optimisation combines both: redesign the work, then apply AI where it adds judgement rather than just speed.
The OpenGaps methodology
Step 1: Build the brain
Consolidate the knowledge and data your teams need into one governed, queryable foundation, typically a company knowledge graph plus a retrieval layer. AI initiatives that skip this step stall because the models cannot get trustworthy answers.
Step 2: Upskill the team
Give the people who own the process the fluency to redesign it with AI. Not "prompt engineering" workshops, but structured capability building so operators can identify, scope, and run optimisation cycles themselves.
Step 3: Leave it running
Ship optimised processes with monitoring, ownership, and documentation so your team can extend and maintain them without perpetual reliance on outside consultants.
Where we focus
Sales
CRM hygiene, meeting prep, follow-up drafting, pipeline anomaly detection, proposal drafting. Recovering hours per rep per week without adding headcount.
Marketing
Content operations, brief-to-draft cycles, campaign analysis, audience insight synthesis. Compressing days into hours while raising quality baselines.
Operations
Service triage, exception handling, supplier communications, order management. Cycle-time cuts of 40 to 60% on well-scoped workflows.
Finance
Invoice processing, reconciliations, expense management, management reporting drafts. Removing month-end firefighting and freeing analysts for actual analysis.
Why this beats point-tool adoption
Bolting a copilot onto every team creates the silo problem: multiple tools, conflicting answers, no shared knowledge, no measurable ROI. A unified optimisation programme aligns process, data, and AI so improvements compound instead of colliding. See why shadow AI is the new shadow IT for the full picture of what happens without this discipline.
What good outcomes look like
- 25 to 40% capacity recovery on targeted processes.
- 40 to 60% cycle-time reduction on operational workflows.
- Clear owner, KPI, and review cadence on every optimised process.
- A team that can run the next wave without us.
See how this connects to the AI process optimisation service and our three-step method.