Fractional Chief AI Officer

An AI executive who ships, without the $500K salary.

Strategy, custom agents, and board-level accountability, delivered by a senior operator on a monthly retainer. The kind of AI leadership a mid-market company actually needs, at a price that makes sense.

Book a Strategy Call → How it works
your AI program running
Support agent cleared 214 tickets overnight06:10
Board deck refreshed with this week’s numbers07:02
Second agent in eval before productionnow
Quarterly governance reviewFri
your Fractional CAIO, this week
The problem

The mid-market
AI gap

Big companies hired their CAIO last year. You're stuck between vendors selling tools and consultants selling decks. Neither moves the number.

Hiring a full-time CAIO is too much

Base salary for a credible Chief AI Officer in the US is $300K–$450K, plus equity, bonus, and benefits. Fully-loaded that's $450K–$700K a year. For a company doing $10M–$50M in revenue, that's a quarter of your engineering budget gone before a single agent ships.

You also can't reliably attract one. Senior AI talent is choosing between FAANG, well-funded startups, and PE-backed roles. Mid-market job posts sit open for 9 months.

Generic AI consultants don't ship

The big firms will sell you a six-month "AI transformation" engagement. You'll get a roadmap, a maturity model, and a PDF. Nothing in production. The juniors who did the work move to the next client; the partner who sold it isn't building anything.

Boutique consultancies often ship, but they ship someone else's platform, the one they have a kickback deal with. That's not strategy, that's resale.

Deliverables

What you get with
a Fractional CAIO

Six concrete deliverables, every engagement. Nothing fluffy.

Deliverable 01

12-month AI roadmap

Prioritized use cases ranked by impact, feasibility, and time-to-value. Each tied to a revenue, margin, or capacity number you actually report on.

Deliverable 02

Custom AI agents

Bespoke agents built for your workflows: sales, ops, support, internal knowledge, research. Deployed on infrastructure you own.

Deliverable 03

Architecture and vendor decisions

Model selection, vector DB, orchestration layer, evaluation framework, monitoring. Vendor-neutral and documented for your engineering team.

Deliverable 04

Deployed in your environment

Agents run in infrastructure you control, or a dedicated tenant we stand up for you. Never pooled with another client’s, and we don’t train on your data.

Deliverable 05

Team enablement

Your people learn to use, evaluate, and extend what we build. Workshops, runbooks, and 1:1 coaching with the engineers who will inherit the work.

Deliverable 06

Board and exec reporting

Quarterly AI-impact reviews written for executives. Metrics, costs, risks, next 90 days. The deck a board chair actually wants.

The engagement

How an
engagement runs

A 12-month engagement, broken into four predictable phases. Each phase ends with tangible artifacts.

audit · phase 1 indexed
crm-export.csvtooling-auditworkflow-mapsvendor-list.xlsx+31 combed
Across your stack, 7 workflows are ready to automate now and 3 shadow-AI tools are already in use without review.
34 sources · 1,900 pages
Phase 1 · Days 1–30

Audit and roadmap

We embed with your leadership for the first month. Workflow audit, data inventory, vendor review, and an AI roadmap that maps to your business goals.

  • Cross-functional interviews with leadership and operators
  • Inventory of current AI usage (and shadow AI usage)
  • Ranked use-case backlog with ROI estimates
  • Architecture and vendor decision document
agent-eval · phase 2 running
Deployed the first agent to staging09:12
Ran 240 evaluation cases09:40
Reviewing 3 regressionsnow
Promote to productionon pass
eval before ship
Phase 2 · Days 31–90

First agent in production

We pick the highest-leverage use case and ship it. End to end: design, build, deploy, train your team, measure impact.

  • One production agent integrated into a live workflow
  • Evaluation framework and dashboards
  • Onboarding for the team using it day-to-day
  • First impact readout to leadership
model · phase 3 your call
Which model for the routing agent?
Claude (Anthropic) recommended
Best refusal handling for your policy, but slightly higher cost per 1k
Open-weight, self-hosted
Lowest marginal cost, but you carry the ops burden
Keep the incumbent
No migration, but fails two of your evals
vendor-neutral · logged
Phase 3 · Months 4–9

Scale the fleet

Two to four additional agents across the prioritized backlog. Governance, monitoring, and internal enablement run in parallel.

  • Additional agents shipped on a 6–10 week cadence
  • AI usage policy, governance, and risk register
  • Team enablement and "AI guild" coaching
  • Quarterly board readout with cost and impact
handoff · phase 4 needs you
Handoff ready
Runbooks
written for all three agents
Team
trained · dry-run passed
Access
transferred to your admins
Your team can run this without us. Sign-off closes the engagement.
phase 4 of 4
Phase 4 · Months 10–12

Operationalize and hand off

Your team owns the work. We document, train, and (if it's time) help you hire a full-time CAIO or AI Lead. Or stay on at a reduced cadence.

  • Full runbooks and architectural documentation
  • Hiring scorecard if you're bringing AI in-house
  • Optional ongoing oversight at a reduced retainer
  • Final board readout and 12-month impact summary
How we build

The technical
posture

Vendor-neutral, model-agnostic, compliance-first. We build on partner infrastructure that satisfies enterprise security review.

  • 01

    Models

    Frontier and open-weight models from Anthropic, OpenAI, Google, and the leading open-source providers. Picked for the workload, not loyalty.

  • 02

    Compliance

    Where your data lives, who can reach it, and what the agents are permitted to do are decided up front and written down. Designed to pass your security review.

  • 03

    Data residency

    Your data stays in your cloud or in a dedicated, audited tenant. No training on customer data, ever.

  • 04

    Integrations

    Native connectors for the operational stack: Salesforce, HubSpot, NetSuite, Snowflake, Google Workspace, Microsoft 365, ClickUp, Notion, Slack.

  • 05

    Evaluation

    Every production agent ships with an evaluation suite and observability. We measure regressions, drift, and unit economics in dollars.

  • 06

    Governance

    AI usage policy, decision logs, risk register, and a quarterly review process aligned with NIST AI RMF and ISO 42001.

What it costs

Pricing

Retainer-based, month-to-month, no long-term contracts.

Most popular
The engagement

Fractional CAIO

$10K–$25K/ month

Retainer scales with company size, agent-fleet scope, and board involvement. Most engagements land at $15K–$20K/mo on a 12-month commitment.

  • Senior CAIO embedded in your leadership team
  • Custom AI agents designed and deployed
  • Deployed in infrastructure you control
  • Quarterly board reporting
  • Team enablement and internal AI guild
  • Vendor-neutral architecture and tooling decisions
  • Month-to-month, cancel anytime
Book a Strategy Call →

Common questions

How is this different from a big-firm AI consulting engagement?

One senior operator is accountable end-to-end. We ship a working agent in 90 days, not a deck in six months. We're vendor-neutral, so we recommend what fits, not what we have a referral deal with. And we work on a retainer, not a multi-year SOW.

Can you embed inside our cloud account?

Yes. We can deploy inside your AWS, GCP, or Azure account, or in a dedicated, audited tenant on our compliance partner's infrastructure. Your call.

What does the time commitment from our side look like?

Plan on 4–6 hours/month from the CEO or COO, plus a small working group (typically 2–4 people) at ~8 hours/month during build phases. The agents save more team time than the engagement consumes by month 3.

What if we're not ready for the full engagement?

We sometimes start with a 30-day audit and roadmap at a fixed fee. If we're a fit, that fee credits toward the first month of a full engagement. If we're not, you keep the roadmap and we part ways.

Do you sign an MNDA?

Yes. We sign mutual NDAs before deep discovery, and we work under your MSA where you have one.

Who's the "we" behind Chief Of Life?

A small senior team. The fractional CAIO leading your engagement is a hands-on senior operator with prior leadership experience deploying AI in regulated and enterprise settings. The build team are senior engineers, not interns. See the About page for more.

30 minutes to see if we're a fit.

No pitch deck. No pre-canned demo. Just an honest conversation about your AI ambitions and what it would take to ship.

Book a Strategy Call →