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The 70/30 thesis

Technology matters. It's still only 30% of AI adoption.

The visible 30% is the stack — budget, integration with the systems you already run, security and compliance. Below the waterline is the 70% that decides the outcome: choosing the right opportunities and proving their ROI, skills and AI literacy, redesigned workflows, the fear of what AI means for jobs, and a roadmap that holds. I've run both sides at scale; I work where programs sink or swim.

Adoption enablers — the 70% in four disciplines.

  • Process redesign & operating model. Re-architect the workflow and the target operating model around AI — not bolted onto yesterday's process.
  • Change management. PROSCI-based adoption so the organization uses what was built, not just buys it.
  • Governance & responsible AI. Bank-grade controls so AI scales without surprises.
  • Adoption discipline. KPIs and benefits realization that hold the program to outcomes.

That's the 70% — ownership, controls, measurement. I don't sell it as a separate project; it's how every build is delivered. The four ways in →

More questions.

The home page keeps the eight most asked. These are the rest.

Who builds it?

I lead every build and write the controls. Vetted developers do parts of the engineering under my review. It runs in your tenant, on your keys.

Who is this not for?

If you want a roadmap and no build, a strategy firm will serve you better.

How do we know what you build is tested and reviewed?

Everything I build passes a strict delivery-assurance standard — registered in your AI registry with a rollback plan, human-in-the-loop by default, tested with an evidence pack you keep, rolled out in stages, 30-day warranty. If it can't produce its evidence pack, it doesn't go live. The record shows what was tested, what was reviewed, and who signed off — your named owner makes the call.

You're one senior operator, not a dev shop — how is quality assured?

Three ways: an eligibility rubric in writing (I build on your existing stack, internal-facing or human-reviewed, always reversible — and I decline what's not mine to build); staged rollouts with the code in your repo, not mine; and when a build needs deep engineering, I say so and direct a vetted engineer instead of pretending.

We already run a GRC program — does yours compete with it?

Never. Your GRC is the skeleton; AI governance arrives as an overlay — the registry maps into your platform, AI controls extend your existing control families, and AI risk reports into the committee pack your board already reads. You'll get two lists: what your GRC already covers (don't pay again), and what's genuinely new for AI.

Where does our data actually go?

Two kinds of machines: my tools and your appliances. My tools process what you hand me — under business contracts that forbid the AI vendors from keeping or learning from it, with deletion deadlines in the SOW; anything too sensitive is processed inside your walls instead. Everything I build permanently runs in your house: your tenant, your cloud, your API keys — nothing phones home to me. The registry is a document in your SharePoint or your GRC platform, not a service of mine. Revoking my access is one click.

Do you build AI agents?

Yes — governed ones. Agentic orchestration without process redesign automates chaos at machine speed. I build agents your board can defend: registered in your AI registry, human-in-the-loop where it matters, with a rollback switch.

What does it cost?

Fixed fee, known before we start: the 7-day Check is $4,500, credited in full to a Build or a Governance Setup within 90 days; the 30-day Build is from $19k, with up to 30% paid on the day-30 number; Agent Care from $3,500 a month and a Fractional CAIO from $8k a month, each on a 3-month initial term, then monthly. Governance Setup is scoped on a 30-minute call.

How do you handle risk and compliance?

As a method, not a promise: every build has a named owner, every decision is logged, there is an off switch, and the evidence pack is written while we build. If you run several AI initiatives or a regulator is asking, the Governance Setup covers the whole company — inventory, owners, risk tiers and a policy your board can sign.

Can you get us SOC 2 / HIPAA compliant?

I prepare and map — policies, AI-layer controls, evidence structure — into the frameworks and tools you already run (including Vanta-class platforms; I overlay, never replace). Certification itself comes from auditors: SOC 2 attestation from a CPA firm, HIPAA counsel where health data is real. I make sure you walk into that process ready, and that your AI layer doesn't break what you've already certified.

How fast do we see results?

The 7-day Check tells you which process to automate first and what it saves. The 30-day Build puts it in production, with the number read on day 30 from your systems.

Do we need a governance project before we build?

No. Every build carries its own controls — owner, log, off switch, evidence. If you run several AI initiatives or a regulator is asking, the Governance Setup covers the whole company.

We're not regulated. Why the controls?

Because the agent has to survive your CFO's month-end, your auditor and the next system upgrade. The controls are a few hours inside a 30-day build; leaving them out is how pilots die in month three.

Still have questions? Book a 30-minute call and we'll work through them together.