From AI readiness to operating reality.
The Edison AI Implementation Method is a four-step framework. Diagnose, Build, Train, Improve, for taking an Australian SMB from AI confusion to measurable operating leverage in 30 to 90 days. Each step has clear deliverables and runs as a defined sprint.
- Step 01
Diagnose
Map where time, money and attention leak.
We sit with the team that does the work. We look at the tools, the data, the volumes, the friction and the failure modes. The output is an AI opportunity matrix. Ranked by impact, effort and risk, so the first sprint targets the highest commercial value with the lowest implementation friction.
Deliverables
- Workflow map of the current state
- AI opportunity matrix (impact × effort × risk)
- Quick wins (30-day ship list)
- Risk and readiness assessment
- Recommended first sprint
- Step 02
Build
Ship working systems your team can use.
We design and build the AI workflows, automations, agents, dashboards or bespoke tools your business actually needs. Using the lightest tool stack that solves the real problem. First useful version typically lands in 2–6 weeks. Real software shipped into your environment, not slides.
Deliverables
- Workflow / agent / system design
- Working software in your stack
- Integrations with existing tools
- Monitoring and error handling
- Documentation and runbooks
- Step 03
Train
Embed the change into how work gets done.
Software that nobody uses creates no value. We train the team on the workflows, build the prompt libraries and playbooks, define the manager review practices, and write the AI usage policy, so the new way of working sticks instead of fading in three weeks.
Deliverables
- Team training sessions
- Role-specific prompt libraries and playbooks
- Manager review checklists
- AI usage policy and approved-tool list
- 30-day adoption check-in
- Step 04
Improve
Measure, tune, and remove what is not working.
AI implementations decay without a feedback loop. We instrument adoption, measure what is working, tune what is not, and add what should come next, on a quarterly rhythm that keeps the system improving long after the initial build is done.
Deliverables
- Adoption metrics and reporting dashboard
- Quarterly review and tuning cycle
- AI-generated weekly insight summary
- Roadmap of next-best improvements
- Ongoing async support
AI only creates value when it changes the way work gets done.
Common questions about the method.
What is the Edison AI Implementation Method?
The Edison AI Implementation Method is a four-step framework. Diagnose, Build, Train, Improve, for taking an Australian SMB from AI confusion to measurable operating leverage in 30 to 90 days. Each step has clear deliverables and runs as a defined sprint, with the next step planned only when the current one has shipped real outcomes.
How long does the method take end-to-end?
Most engagements take 30 to 90 days from Diagnose through first Build and Train. Improve runs continuously on a quarterly rhythm thereafter. We deliberately keep the cadence tight. Long transformation programmes lose momentum and rarely ship.
Do we have to commit to all four steps?
No. Most clients start with Diagnose (the AI Readiness Audit) and commission Build only after the opportunity matrix is in front of them. Some clients commission Build and Train without us; others retain us across all four. The method is a sequence, not a contract.
How is this different from a generic consulting framework?
Diagnose is the only "thinking" phase. Build through Improve are execution phases where we ship working software, write actual playbooks, train real teams and measure adoption. We don't sell vague strategy decks; we sell shipped systems and trained capability.
What does it cost?
Diagnose (AI Readiness Audit) is fixed-scope, typically a two-week engagement. Build is scoped to the workflow or system, most first builds land in the $15K–$60K range. Train ranges from a half-day workshop to a six-week structured adoption programme. Improve is a monthly retainer for clients who want continuous iteration.