AI Governance · for CTOs, CISOs and CFOs
Get your AI under control.
Your teams already use Copilot, Cursor and ChatGPT. Get every AI tool and its cost in one view, sensitive data kept out, AI-written code checked and an audit trail your board can rely on.
45 minutes · a written plan, whether or not we work together
Example leadership view with illustrative data: AI spend by team this month, the AI tools in use with their approval status, and AI risks caught with the decision taken.
ISO 27001
ISO 9001
- Clutch 5.0★ (opens in a new tab)
- Claude Certified Architects
The gap
AI is already inside your org. Nobody owns it.
The CTO is shipping product, the CISO is watching the perimeter and finance sees one invoice. The place where AI risk actually sits has no owner.
- 45%
- of AI-generated code contains security flaws Veracode GenAI Code Security Report, 2025
- 42%
- of companies scrapped most of their AI initiatives in 2025, up from 17% S&P Global Market Intelligence, 2025
- Inventory
Today: Nobody can say which AI tools are in use, by whom, or where.
With AI Governance: Every AI tool, team and repository mapped to an accountable owner, within 72 hours of access.
- Spend
Today: Invoices and license totals, with no link to teams, products or results.
With AI Governance: AI spend by team and user, where your tools expose usage data, set against what it produced.
- Security
Today: Scanners built for human-written code miss hallucinated packages and injection patterns.
With AI Governance: AI-aware checks on every commit, with hallucinated packages blocked before they ship.
- Audit trail
Today: The board or an auditor asks which code was AI-assisted and who reviewed it. There is no answer.
With AI Governance: A record from prompt to deploy: what changed, which controls applied and who decided.
What we install
Five layers. One owner. Full control.
Each layer runs inside the tools you already use: your IDEs, Git, CI/CD and monitoring. Choose a layer to see what it covers.
What AI may be used for, by whom, with which data.
- An inventory of every AI tool, repository and workflow, each with an accountable owner
- An executable AI policy: approved, restricted, prohibited and escalation-required use, live by Day 14
- Shared rules files and context for your codebase, and the right model for each task on cost and capability
How AI-written work is produced and reviewed.
- Prompt standards and a pattern library your teams reuse
- Automated review of every pull request for logic inversions, invented APIs and authentication bypasses
- Multi-step AI workflows with human checkpoints where judgment matters
Checks built for the mistakes AI makes.
- AI-aware security scanning on every commit: injection, credential sprawl, insecure output
- Supply-chain checks that block hallucinated packages, with SBOMs generated
- Infrastructure-as-code checks for insecure defaults before anything is applied
- Continuous adversarial testing of AI-written code
Evidence produced as the work happens.
- Mapping to the frameworks that apply to you: SOC 2, HIPAA, GDPR, PCI-DSS, the EU AI Act
- Traceability from prompt to deploy, with every AI decision logged
- Quality gates in CI/CD that cannot be bypassed
- A reusable evidence pack for enterprise security questionnaires
What AI costs, and what it is worth.
- AI spend by team and user, with burn-rate alerts and forecasts
- A live dashboard for the CTO and CISO: AI code share by team and risk exposure
- Quality measures: defect rates and cycle time for AI-written against human-written work
- Production monitoring that links incidents back to the prompts and changes behind them
The 90-day plan
A plan your board, auditor and CTO can back.
Ninety days with a walk-away checkpoint at Day 30. After Day 90 the work moves from implementation to monthly oversight: new tool approvals, quarterly compliance reports and board summaries.
- Step 01
Day 14: policy live
Stakeholders aligned, AI tools audited and your executable AI policy published and enforced.
- Step 02
Day 30: risk report
Your actual AI risk, quantified and mapped, with a gap analysis and roadmap. You can stop here.
- Step 03
Day 60: observe mode
IDE, Git, CI/CD and production monitoring connected. Baseline captured, policies tuned, nothing blocked yet.
- Step 04
Day 90: enforced
Gates live on every pull request, incidents traced to their cause and a full return-on-investment model.
What we commit to
Each commitment depends on you giving us the access, decisions and feedback we ask for on time.
- Your governance environment is visible within 72 hours of access being granted.
- Your executable AI policy is live by Day 14.
- At Day 30 you get the risk report, gap analysis and roadmap, and can walk away owing only for work done to that date.
- If the agreed controls are not in place by Day 90 for reasons within our control, we keep working at no extra management fee.
What we don’t guarantee: certification, a regulator’s or auditor’s conclusion, legal compliance in every jurisdiction, or the removal of every vulnerability. Those depend on your systems and on factors outside any vendor’s control.
Who leads it
One accountable owner for AI risk.
Delivered as a Fractional AI Officer engagement with a governance focus. Choose whether your team leads with our guidance, or we run it for you.
- A person, not software
- A senior governance specialist embedded in your engineering team: attends standups, reviews pull requests, writes policy and owns the outcome.
- Background
- Eight or more years in software engineering, with AI and compliance expertise.
- Time
- Eight to twelve hours a week, dedicated: enough to follow your sprints, review AI-written changes and report weekly.
- Named before you sign
- You meet your specialist on the discovery call. If the fit isn’t right, we find a better one.
Questions
Questions security leaders ask.
How is this different from the security scanners we already run?
SAST and SCA tools were built for human-written code. We add checks for the mistakes AI makes, such as hallucinated packages, inverted logic and credential handling, plus the layers scanners don’t cover: an AI inventory, policy, spend visibility and an audit trail.
How fast can it start?
Your governance environment is visible within 72 hours of access being granted. For regulated enterprises, procurement, legal review and contract signature usually add four to eight weeks first; the 72 hours run from signing. We tell you what to prepare on the discovery call.
Do we have to change our tools or infrastructure?
No. We connect to your IDEs, Git, CI/CD and monitoring, start in observe mode so nothing is blocked while we tune, and there is no lock-in during the pilot.
Can our team run it, or do you run it for us?
Either. Done with you: your team leads and we guide, train and co-design, with full knowledge transfer. Done for you: you give us access, your AI tool list and your compliance obligations, and we audit, install, observe and report. One person is accountable in both.
How does this relate to AI-Native Engineering?
AI Governance controls the AI your teams already use, across engineering and beyond. AI-Native Engineering installs a complete governed delivery pipeline, from spec to production, with these controls built in. You can start with either.
What does it cost?
AI Governance runs as a Fractional AI Officer engagement on a monthly fee, scoped to your organization’s size and how hands-on you want us to be. See Fractional AI Officer pricing. You get a written proposal before anything starts.
Get AI spend, data and code under control in 90 days.
Book a 45-minute discovery call. We’ll map where AI is already used in your organization and send a written plan, whether or not we work together.
Not ready for a call? Get your AI Governance Score in 2 minutes