AI governance and adoption

Protect Your Business Information.

Put AI to use with a clear view of how it handles customer information, pricing, business plans and company knowledge. We help you understand exposure and put appropriate protections in place alongside your IT team and existing partners.

Governance supports both reliable results and protection of business information. We build on your existing policies and capabilities, with depth suited to your AI use, business needs and risk.

Sound familiar?

Leadership asks “are we safe with AI?” and nobody can answer with evidence.
Legal or security stalled an AI pilot, and nobody owns the decision.
Teams need clear guidance on which customer and company information is appropriate to use with AI.
People have built AI apps and automations in personal accounts, outside company oversight.
AI subscriptions and API costs are scattered across teams and expense reports, and nobody sees the total.

We identify the gaps that matter most to your business, agree on the work and put practical rules and protections in place with your team.

What changes

Your teams know which tools they can use, what information they can share, and who to ask.
Your leaders can see where AI is used, who owns it, and what protects it.
Your business moves useful AI work forward, with results you can show.

Our governance framework

A foundation for confident AI adoption.

Value-Based AI Adoption connects each important AI use to a measurable business outcome, accountable owners and safeguards proportionate to its impact. The five pillars below guide that work.

Five governance pillars: Direction and ownership; Rules and protection; Data and tools; People and adoption; Results and learning. Choose useful work, apply appropriate controls, use and measure, improve and reuse. — A practical operating foundation that grows through reviewed, measurable use.

Direction & ownership

Prioritize measurable business value
Name accountable owners
Define decision authority

Rules & protection

Address unapproved tools and data exposure
Set data and autonomy boundaries
Match controls to risk

Data & tools

Know where data is stored and processed
Set identity and access permissions
Track, update and retire AI

People & adoption

Enable teams around real work
Share approved practices
Make exceptions and escalation clear

Results & learning

Track outcomes and costs
Verify AI work and controls
Improve and reuse what succeeds

Choose useful work → Apply appropriate controls → Use and measure → Improve and reuse

Every AI use gets a record: purpose, success criteria, owner, risks, controls, evidence and review triggers. Approved practices get reused, and changes get reviewed.

These pillars connect appropriate access, approved models and uses, cost management, development standards and accountable ownership. Together, they help teams adopt AI responsibly and produce work the business can rely on. We apply the depth your situation calls for.

An AI application can be over-permissioned: able to access more information or take more actions than its purpose requires. Defining an appropriate boundary helps protect information and keep AI actions aligned with the work.

Design references: ISO/IEC 42001 and NIST AI RMF. This is a conceptual framework and makes no certification or conformity claim.

Where to begin

Start where the problem is biggest.

Get control of AI already in use

Find where AI is used across the teams and tools that matter most, including apps built in personal accounts, agent permissions and costs. Put owners, rules and protections on the uses that carry real risk.

Move stalled AI work forward

Identify what is holding useful AI work back. We clarify responsibilities and appropriate standards so teams can move forward, verify results and build on what works.

Trusted Delivery

A clear commitment, informed by your situation.

We understand the priority, access, dependencies and client inputs before agreeing on the work. Progress stays visible, results are verified against agreed acceptance criteria, and you control the next commitment.

See how Trusted Delivery works →

Need help building or improving dependable AI work? Explore AI Workflows. Information protection and appropriate review are part of how we build, too.

Find Your Starting Point

Explore practical starting points. No contact details required.

Start here

What would help you trust your AI?

Tell us about information you need to protect, results you need to rely on, or AI adoption that has stalled.

Tell us what is getting in the way

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