AI Opportunity Matrix
A classification of the business’s meaningful tasks across Human, AI Assist, AI Worker, and Automation.
The AI-Native Assessment maps how your business works today, identifies where AI can create value, and shows what must change before implementation.
For businesses that are experimenting with AI, but can feel the operating model is not ready: scattered knowledge, unclear ownership, manual handoffs, disconnected tools, or workflows that still depend too heavily on individual people.
You leave with a clearer view of where AI belongs, what is blocking progress, and which operating changes should happen before investing in more tools or automation.
A classification of the business’s meaningful tasks across Human, AI Assist, AI Worker, and Automation.
A clear view of how work, knowledge, ownership, and decisions currently move through the organisation.
A prioritised roadmap for becoming more AI-native, including readiness gaps, sequencing, and next-step implementation priorities.
This is not a tool recommendation session. It is a structured diagnostic for understanding how ready the business is for AI to take on more meaningful work.
Identify the business areas, workflows, and responsibilities that matter most to becoming AI-native.
Determine the ideal owner for significant work: human, AI-assisted, AI worker, or automation.
Clarify what must change in architecture, context, governance, and decision ownership before implementation.
Leave with the clearest priorities for transformation rather than another list of AI tools to test.
We evaluate how work is performed today, where knowledge is trapped, how decisions are owned, and where AI-native redesign will create the greatest value.
Every meaningful task should be classified according to its ideal owner and the conditions required for AI to take more responsibility safely.
High judgement, ambiguity, trust, or risk. A person should remain clearly responsible.
AI improves speed, preparation, drafting, or analysis while a person stays accountable.
The task can move to AI when context, boundaries, and repeatability are strong enough.
Stable, rule-based work that benefits from deterministic automation rather than reasoning.
Work remains human-led because judgement, ambiguity, trust, or risk still require direct human ownership.
AI supports the work, but a person remains the clear owner of the outcome and final decision.
AI can take meaningful responsibility for the task when context, repeatability, and governance are strong enough.
Traditional automation handles highly repeatable flows where clear rules are already established.
It is a strategic diagnostic of how work, knowledge, ownership, and decisions move through your business, so you can see where AI can create practical leverage.
It is designed for founder-led businesses and professional services teams that want to move beyond scattered AI experiments and prepare their operating model for meaningful implementation.
You receive an AI Opportunity Matrix, a view of the current operating model, and a prioritised transformation roadmap that identifies readiness gaps and next-step priorities.