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VOL. 01 · EST. 2026

Fractional CAIO
for operating
companies.

AI strategy, implementation, and governance for $10M–$100M operating companies — without hiring a full-time executive.

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Freight & logisticsHealthcare servicesFranchises & multi-unit operatorsProfessional servicesMid-market & enterpriseOperating co. · $10M–$100M+Freight & logisticsHealthcare servicesFranchises & multi-unit operatorsProfessional servicesMid-market & enterpriseOperating co. · $10M–$100M+
01— Introduction

Own your AI transformation without hiring a full-time executive. I partner with $10M–$100M operating companies to turn AI from a line item into measurable leverage.

02— The problem

Most companies have AI anxiety, not an AI plan.

i

Hype without a thesis.

Every vendor claims to be AI-first. Your team can’t tell which tools matter, which are theater, and which will regret-purchase you in six months.

ii

Pilots that never leave the sandbox.

Marketing demos an ops chatbot, legal flags it, IT shelves it. No one is accountable for getting real systems into production.

iii

Tool sprawl, no leverage.

You’re paying for six copilots and seeing no margin, no hours back, no compounding. Spend is up, output is flat.

iv

No governance, rising risk.

Clients and carriers are starting to ask. You don’t have a policy, a data boundary, or a clear answer when they do.

03— Engagement

What a Fractional CAIO actually does.

01— Pillar

AI Strategy

Define where AI creates real margin in your business — then say no to everything else.

— Case

For a 40-person freight forwarder: prioritized 3 use cases worth $480k/yr in recovered ops hours, killed 5 shiny pilots.

02— Pillar

AI Implementation

Ship real systems into production. Not slideware, not sandbox demos.

— Case

Built a Claude-powered quote-drafting workflow that cut response time from 40 minutes to 3, hands-on with the ops team.

03— Pillar

AI Governance

Policy, data boundaries, model selection, and an answer when clients ask.

— Case

Authored a usage policy and data handling framework for a healthcare services firm ahead of an enterprise client audit.

04— Fit

Built for a specific kind of company.

— FOR

  • Operating companies, $10M–$100M in revenue
  • Real customers, real margin, real operations
  • Leadership that wants an owner, not a deck
  • Industries without an in-house AI bench

— NOT FOR

  • —Tech startups with in-house AI teams
  • —Early-stage companies without a business to augment
  • —Buyers looking for a PowerPoint deliverable
  • —Anyone who wants to stay anonymous about AI usage
05— Cadence

How we work together.

Weekly working sessions with your leadership, shared Notion, and a real backlog — not a report.

— MONTH 1

Audit

DISCOVER

Map workflows, interview the team, identify where AI creates leverage — and where it doesn’t. Output: a prioritized roadmap, not a 90-slide deck.

— MONTHS 2–3

Pilot

BUILD

Ship 1–2 real systems into production. Fast feedback loops, hands on keys with your ops and engineering teams.

— MONTHS 4+

Scale & govern

OPERATE

Expand what works, document policy, train the team so they own it. My job is to make myself progressively less necessary.

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— INSTAGRAM · PUBLIC BUILDING

@baehr.ai

Field notes on deploying AI inside real operating companies — what’s working, what isn’t, and why.

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