monthly AI Advisory

When AI is everywhere, in everything, all at once, AI Decisions Start Compounding, Too.

One good decision doesn’t protect you from the next one.

3 FAILURE MODES

The 3 Ways AI Strategy Fails, Even When It Starts Right

6 months ago, you did everything right. You got aligned. You built a strategy. You knew where your organization stood on AI. But the landscape kept moving. A new tool launched that your CTO is excited about. A vendor promised your investors something you hadn’t approved. A team started building outside your governance because the official process felt too slow.

And now you’re back to making calls alone, except the calls are harder, the stakes are higher, and the decisions are moving faster than your strategy can keep up.

Pilot Purgatory

You ran a successful pilot. Now it’s 6 months later, and you’re running another one. And another one. The organization is experimenting, not deciding.

Shadow AI

Teams are using AI tools you didn’t authorize, in workflows you haven’t mapped, for outcomes you haven’t measured. You’ll find out when something goes wrong.

Fragmentation

Every department has a different answer to the question “What are we doing with AI?” No one’s wrong. No one’s aligned.

They feed each other. Pilot purgatory creates pressure to experiment outside governance. Shadow AI creates fragmentation. Fragmentation makes the next pilot harder to justify. The cycle continues until someone decides to break it, or until the board asks a question no one can answer.

At the Department of Education, a federal directive required every public-facing website to meet new encryption standards. The official count was 14. My branch of 6 ran the first real audit the agency had ever done, cataloging hosting, code bases, encryption, and ownership. We found hundreds.

The gap between what leadership believes is running and what is running is usually the largest number in the room.

One Advisor. No Handoffs. No Platform to Sell.

Who You’re Working With

I’ve spent 25+ years in these rooms. At IBM as Principal AI Experience Design Lead. Before that, program lead on federal modernization at the Department of Education and the Census Bureau.

In 2024 I facilitated the work behind Smarter Balanced’s 8 student-centric design principles for AI in assessment, the tests millions of students take. Assessment and measurement experts. State, district, and local educators. Higher education. Policymakers. 3 national conferences of feedback before anything was agreed.

The principles became the requirements. Then the test every AI solution had to pass. The measure was written before the AI was built.

I built this practice because I kept seeing the opposite. Good intentions, and no one holding the strategy accountable.

At an aviation client, I led a GenAI pilot that cut safety data review time by 75% and uncovered $11M in validated process savings, with a solution the agency could see into, defend, and trust.

THE COST OF INACTION

What One Decision Costs When It’s Made Under Pressure

Not a catastrophic decision. Just one call, made without a second opinion, under vendor pressure, with investors watching, that takes your organization 6 months in the wrong direction.

At the U.S. Census Bureau, a server upgrade completed 24 hours before a scheduled economic data release introduced an undetected error. The data published 15 minutes late. That 15-minute window moved financial markets.

The decision that caused it wasn’t reckless. A routine infrastructure change, made without enough lead time to test it. No malice. No warning. No governance guardrail.

The fix: no infrastructure changes within 7 days of a scheduled release. Zero delays after.

12 months of decisions get made the same way.

WHAT THE ADVISORY INCLUDES

A standing seat at your AI decisions.

If I disappeared tomorrow, you should be able to explain what was built, why it was built, and how to defend it.

6 months. Every month:

→ A working session on whatever is actually in front of you. No fixed agenda, because your month doesn’t have one.
→ Your vendor proposals, board materials, and internal decks read before we talk, not during.
→ Access between sessions, because the decisions that matter rarely wait for the calendar.
→ A written decision log your organization keeps, so the reasoning outlives the engagement.

CONCRETE SCENARIOS

What This Looks Like in Practice

Independent Assessment

Your vendor sends a proposal for a new AI capability. You forward it before the meeting. I’ve reviewed it, flagged the 3 assumptions they’re counting on you not to question, and drafted the 2 questions that will tell you everything you need to know. You walk into the meeting prepared.

Sustain Your Values

A team lead tells you they’ve been using an AI tool for 6 weeks without approval. I help you figure out whether this is a risk you need to stop immediately or a pilot worth formalizing, and build the process so it doesn’t happen again without visibility.

Leadership Intelligence

The board wants an AI update. I help you frame what’s been decided, why it was decided, and what the next decision point is, in language that answers the question they’re actually asking, not the one they wrote down.

There’s always a known unknown

Something happens that wasn’t in the plan. An acquisition, a regulatory change, a team departure. I help you figure out what it means for your AI strategy before you have to explain it to someone else.

FAQs

Questions Leaders Usually Ask.

Is this ongoing or project-based?

6-month retainer, with the option to continue afterwards. The first 3 months are typically the most intensive. That’s when we’re building the accountability framework alongside your existing processes.

How many spots are available?

Limited. I work with a small number of advisory clients at any time so I can give each organization the depth of attention the engagement requires. If you’re considering it, the 30-minute conversation will tell you whether there’s availability and fit.

Do I need to have completed The AI Field Lab™ first?

No. But if your organization doesn’t have a clear AI values framework, that’s the first thing we’ll build together. Some advisory clients start here; others move from the Field Lab directly into advisory. Either path works.

What if this isn't the right fit?

I’d rather tell you this isn’t the right fit than take your retainer if it isn’t. The 30-minute conversation is where we find that out.

How is this different from hiring an AI consultant?

Most consultants are project-based. They come in, deliver a recommendation, and leave. This engagement is ongoing. The value compounds over time as I understand your situation more deeply.

Do you work with technical leaders or non-technical leaders?

Both. I’m particularly skilled in tech-to-business and business-to-tech translation.

How quickly can we start?

That depends on availability. I typically have a 2 to 4 week intake process before we begin formal sessions. Submit an inquiry, and we’ll talk through timing.

Can I cancel?

After the minimum 6-month commitment, you can cancel with 30 days’ notice. I don’t lock people into engagements that aren’t working. If it’s not the right fit, we figure that out early.

What does one wrong call actually cost?

A single misaligned AI decision takes 6 months to surface and another 6 to unwind. 12 months of decisions get made in the meantime, every one of them built on the first. The advisory exists so the first one gets a second opinion before it compounds.

The Monthly Advisory

You’ve been carrying the AI strategy alone long enough.

The leaders who reach out aren’t in crisis. They’re the ones who saw pilot purgatory coming, and decided to do something before it became a board conversation.

I’d rather tell you this isn’t the right fit than take your retainer.

Schedule a 30-minute strategy conversation →

No pitch. No deck.