Go or no-go, on page one, with a name signed under it. The free assessment comes first, and it costs nothing.
The free assessment takes two days. The AI Opportunity Audit takes up to another five business days.
AI made software cheaper to build. Building the wrong software is still expensive.
The building got easy and the scoping disappeared. AI will write whatever you ask it to write. What it won’t do is stop and ask whether the thing should exist, or what done means. It says yes to everyone.
Most AI pilots never make it to production, and most of the ones that do never show up in the P&L. Nobody scoped them.
So we scope. Twenty-five years of it, now pointed at AI.
The scoping has a name on it: Phil Cowan. 140+ engagements. ShapeShift and SALT Lending launched out of our own office. Creative direction for Disney, Pixar, and Universal film campaigns. Fund rails for WallStreetBets. The rest is on the record.
The AI Opportunity Audit is one document, eight parts, every time. Your procurement team will recognize the shape and your engineers will recognize the substance.
On the first page, not a maybe with charts behind it. A person’s name goes on it, because someone has to stand behind the answer, and it isn’t a model.
Everything we found, tested against a written, disclosed rubric: architecture under load, security under attack, the workflow with real users in it, costs at real volume.
Bounded in writing. The exclusions matter more than the inclusions, because that is where the surprises are.
Functional, performance, security, accuracy. Done is defined before the iteration starts.
If the verdict is go, this is the path: sequence, milestones, and the build clock. Whoever builds, ours or yours, this is what they follow.
In numbers, agreed before anything gets built, measured against the non-AI alternative. If it doesn’t pay, the scope says so.
What the work requires from your systems and your people, named up front.
What we’re taking on faith, what could move, what it costs, and how the engagement ends. The exit is written in advance.
The scope runs under NDA, signed before any sensitive code moves. Nothing you send trains any model, and your artifacts are deleted on request when the work is done.
No-go is always an acceptable answer.
The verdict is yours to take anywhere, including to someone else’s build team. We’d rather you build with us, obviously. But a scope that only works if you hire us isn’t a scope, it’s a pitch.
If we find where it breaks, good. That’s the point of looking. If it holds, you get your go with the evidence behind it. Either way you stop guessing.
You have the idea, the deck, or the roadmap, and money is about to move. The scope gives you direction first: which door to take, what it will cost, what paying off means in numbers, and a written no if the answer is no. Cheaper to hear it now.
You built it. The demo works, people leaned in, and then it stopped moving: probably around seventy percent done, and the last stretch is the wall. The scope is the diagnosis: what’s actually missing, ranked by what decides, with a priced plan through it.
You didn’t build it. You inherited it: the contractor rolled off, the founder moved on, and now a system nobody can fully explain runs under your name. You need to know what you’re holding, and the scope tells you in writing: what it is, what it needs, what it costs to keep alive, and whether it should be.
An audit attached to a build practice is a conflict of interest, and you’re right to treat it like one. So the controls are structural: the scope is priced to stand alone, a no-go pays us exactly what a go does, and the document is built to hand to someone else’s team without us in the room. If the verdict is go, the scope prices and schedules every door below. You pick who opens them:
Agentic systems built into your operation and wired to your data and tools: research, ops, support, sales. Real work, under human judgment.
The demo works. Production must hold. Your AI-built app hardened, scaled, and shipped for real.
Bring the problem. Get the finished system. Greenfield builds with AI and your team, integrated with what you already run.
AI built it. Now secure it. Reviews and hardening for AI-generated systems, before they meet the real world.
An AI readiness audit is a written test of whether an AI plan, prototype or running system should go forward, and what that would take. Innovation Theory’s version is the AI Opportunity Audit: $5,000, within five business days after a free two-day assessment, one signed document in eight parts, including a go or no-go verdict on page one, ranked findings with evidence, acceptance criteria, a production plan and success metrics in numbers. No-go costs the same $5,000 as go, and the document is written to hand to any build team.
The free assessment is $0 and comes back in two days. If it’s worth a scope, the AI Opportunity Audit is $5,000 and takes up to five more business days. Anything after that is priced by the scope, in writing, before it starts.
One signed document, eight parts: the go or no-go verdict on page one, ranked findings with evidence, scope and exclusions, acceptance criteria, a production plan, success metrics, the data and access the build needs, and the assumptions, risks, exits and pricing. It’s built to hand to any build team, including one that isn’t us.
Yes, that’s most of the job. Tell us the work you want to improve and what keeps getting in the way. You don’t need a technical spec, and the free assessment tells you whether an AI Opportunity Audit is worth doing at all.
If the AI Opportunity Audit says no-go, the client hears no, in writing, and the $5,000 fee is the same as for go. You keep the findings either way.
An AI project pays off when its success is written as numbers before anyone builds it: hours saved, errors avoided or revenue moved, set against what it costs to build and run. The AI Opportunity Audit ends with exactly that, success metrics in numbers and a go or no-go verdict on page one. No-go costs the same $5,000 as go.
No. Innovation Theory has done business strategy, product, tech, marketing and design work since 2011, and we still do all of it. AI now runs through every part of it, and your project doesn’t need an AI feature to be worth scoping.
The free assessment runs on context, and Phil and the team read it. Code is welcome, never required. For the free assessment, we don’t rely on subcontractors or AI. The scope runs under NDA, signed before any sensitive code moves, nothing you send trains any model, and your artifacts are deleted on request.