Enterprise architecture and consulting
Strategy work with large organisations taught us how to turn a good idea into something that survives governance, politics, and delivery pressure.
Training, strategy, and implementation
Most AI pilots stall. We make them ship.
A&O helps mid-market companies turn AI from a portfolio of pilots into a way of operating. We do three things: train your people, set the strategy, and build what's needed to make it real.
Twenty minutes. You'll leave with one concrete next step, whether or not you hire us.
Founder's experience includes work with
- BC Hydro
- Telus
- Trulioo
- Accenture
Roles held prior to founding A&O, and delivery undertaken through prior employers. Listed as professional background — not as A&O client engagements or endorsements.
Proof
Proof, not promises.
A&O is led by Robin Fitzpatrick, with proof grounded in delivery experience, shipped systems, and the kind of operational judgment that keeps AI work moving once it leaves the slide deck.
Engineering operations
Working close to delivery made the failure modes obvious: pilots stall when ownership, sequencing, or operating discipline is missing.
Production AI systems
The site is backed by a live multi-agent system, so the advice is grounded in shipping systems, not just talking about them.
The problem we solve
AI work stalls in the gap between intent and operations.
Pilots don't become production.
Most companies have run a dozen AI experiments. Few have shipped a system that changes how the business operates. We close that gap — from feasibility to deployment to the day-two work nobody warns you about.
Teams don't adopt what they don't understand.
AI literacy is the difference between a tool that gets used and a tool that gets ignored. We train executives, operators, and specialists at the level each needs — and we measure adoption, not attendance.
Strategy decks don't run themselves.
A roadmap that nobody owns is a roadmap that nobody executes. We design strategy alongside the people who will deliver it, then stay close enough to know when the plan needs to change.
Three ways to start
Train the people. Set the direction. Build the system.
Each one can stand alone. The strongest engagements connect all three.
01Training
AI That Sticks
From $2,500· Half-day or full program
Hands-on training on your team's real workflows — not a generic tools tour. You keep the playbook.
02Strategy
AI Opportunity Sprint
From $1,500· 1 week
Your top three AI opportunities, ranked by ROI and effort, with the metric each one should move.
03Implementation
Ship One Thing
From $8,000· 2–4 weeks
One AI-powered workflow, built end to end and deployed in your environment. A live tool, not a recommendation.
Locate, Land, Live framework diagram
Locate
Discover
- Prioritised opportunities with feasibility scores
- Target operating model shaped around the work
- Roadmap leadership has argued through
Land
Deliver
- Systems built alongside your teams
- Training runs in parallel
- Production work starts immediately
Live
Stabilise
- Transfer of ownership and documentation
- Operating discipline hardened in the real world
- Support through the handoff and stabilisation
Locate → Land → Live
A simple operating rhythm for moving from pilots to production.
Locate where AI changes the business, not where a tool looks impressive. Land the systems with the teams who will own them. Live through the first weeks of operational reality.
The framework keeps strategy, training, and implementation connected instead of handing work from one silo to the next.
Who you work with
You work with me, not an account team.
I'm Robin Fitzpatrick. I've spent my career on the delivery side of large technology programmes — enterprise architecture inside a top-five global consultancy, then Director of Engineering Operations at a North American identity-verification unicorn with roughly 300 engineers.
That's where the point of view comes from: I've watched enough AI work stall between the strategy deck and production to know it's rarely a model problem. It's an ownership, sequencing, and operating problem.
A&O is deliberately small. The person who scopes your engagement is the person who does the work.
Selected experience
Relevant work, with provenance made explicit.
Identity verification platform: agentic AI strategy and engineering operations.
North American identity verification SaaS unicorn, ~300 engineers.
Founder’s role: Director of Engineering Operations (not as A&O).
Global consultancy enterprise architecture engagement: digital transformation strategy.
Large enterprise client of a top-five global consultancy.
Founder’s role: Enterprise Architect / Consulting Manager (not as A&O).
Content cluster
The questions leaders ask before they commit.
These are the pages that should attract traffic, answer search intent, and feed the service pages with internal links.
Why AI training fails when it stops at vocabulary
Only 13% of employees have had any AI training while 80% already use AI tools at work. That gap is where shadow AI lives — and why most training changes nothing.
What an AI readiness assessment should actually answer
Most readiness assessments produce a scorecard nobody acts on. A useful one answers five questions and tells you what not to do yet.
Why AI pilots stall before production
Most enterprise AI pilots never ship. The blocker is almost never the model — it is ownership, integration, and the day-two work nobody scopes.
Governance that helps AI move faster
Governance that reviews everything reviews nothing well. Risk-tiering, a named owner, and clear defaults let teams ship — and beat the August 2026 EU deadline.
Agent product analytics: why the run matters more than the session
Agents can hit 60% success on a single run and 25% across eight. Session dashboards hide that completely — here is what to measure instead.
What Canadian privacy law actually requires of your AI
There is no federal AI statute in force in Canada. What binds you is privacy law — PIPEDA, BC PIPA, and Quebec's Law 25, which already regulates automated decisions.
How to become an AI-native company when you weren't born one
AI-native is usually defined so that only startups qualify. Here is the version that works for a 30-year-old business — built on your people, not your org chart.
Start the work