AI Governance and Operating Model
AI governance establishes decision rights, accountability and the controls around AI-supported work. We define the roles, responsibilities and operating controls for your people and AI, so your team knows who owns each outcome, what AI is responsible for and which financial or customer commitments require approval.
The work covers:
- Accountability and decision rights. Named owners for each outcome and documented authority for spending, pricing, scope and customer commitments.
- Access control and information governance. Defined access rights and approved uses for the systems, records and company information involved in the workflow.
- Operational controls. Clear approval requirements, action limits and stop conditions for the agreed workflow.
- Risk and exception management. A clear escalation path for missing information, conflicting instructions, out-of-scope requests and failed checks.
- Control testing and operating evidence. Acceptance criteria, test results and open issues that show what has been verified and what still needs attention.
- Traceability and management oversight. Records linking the work to its source, result and approval, so your team can investigate problems and review performance.
Your team controls budgets, authorizes payments and approves pricing, scope and customer commitments. AI supports the work within defined decision rights and financial controls.
AI output can vary. The acceptance record shows which controls were tested, what happened and what still needs attention.
Enterprise Knowledge Management and Context Engineering
We organize your company's knowledge so your people and AI can work from consistent information: your services, customers, terminology, operating rules and decision standards. Context Engineering prepares that information for the responsibilities and workflows it supports.
The work covers:
- Knowledge architecture and business definitions. A clear model of your services, customers, roles, priorities and business terms, so your people and AI use the same meanings.
- Information quality and verification. Facts linked to supporting sources, approved statements and clearly labeled assumptions; claims without support remain open for review.
- Source lineage and traceability. References showing where information came from, which statements it supports and where it is used.
- Information governance. Clear ownership, classification and approved use for company knowledge, including what is suitable for internal work and what may be used publicly.
- Issue and exception management. A record of missing, outdated or contradictory information, with responsibility for resolving each issue.
- Change impact management. Identification of the outputs that need review when their source information changes.
- Knowledge transfer. Reusable company context, operating documentation and a handoff to the people responsible for using and maintaining the work.
Your company gains a reusable knowledge asset that your people and AI can apply to the agreed work, with sources, ownership and unresolved issues visible.
Your data and business knowledge remain yours. Ownership of delivered materials and the treatment of pre-existing or third-party components are set out in your agreement.
Fractional Chief AI Officer: implementation leadership
5 Talents leads the agreed AI implementation: prioritizing the work, building company context, establishing governance and bringing the selected workflow into use.
We define the business need, the expected deliverable, the accountable owner and the evidence used to accept the work. Your engagement specifies who operates the workflow and what ongoing management includes.
Company Brain, Context Library and Governance OS
The Company Brain provides structured intelligence across 12 core business functions. Each function has a Map, Model and Brief, creating 36 intelligence elements.
The Governance OS is a separate layer of Results, Rules and Rights for each core business function, with 36 governance controls in the core design.
The Context Library connects this intelligence and governance with approved sources, decisions and operating knowledge for your people and AI to reuse.
Your engagement defines which business functions, intelligence elements, governance controls and workflows are included.
The 6 deliverables for 1 selected workflow
For the selected workflow, you receive these 6 deliverables within the agreed engagement scope.
- A Company Brain and Context Library covering the business functions, intelligence, governance and source knowledge included in your engagement.
- A record of approved sources and the facts used in the workflow.
- Defined accountability, access controls and decision rights.
- The agreed workflow output, with known limitations and unresolved issues recorded.
- Acceptance criteria and recorded test results showing what worked and what still needs attention.
- Operating documentation and a handoff to the person responsible for running the workflow.
Your engagement confirms the selected workflow, connected systems and records, deliverables, delivery timeframe, operating responsibilities and support scope.
Service availability
Monday through Friday, 8 a.m. to 6 p.m. Central Time, excluding U.S. public holidays.
This is the service availability window. Dedicated hours or capacity and recurring meetings are defined in the engagement scope. In-scope troubleshooting and repair do not include guaranteed response or repair times, immediate response, same-day repair or an uptime SLA.
Performance and value measurement
We measure adoption, quality, speed, capacity, cost and risk against an agreed starting point. Your performance record separates targets from observed results and links value claims to evidence from actual work.
Key terms, in everyday language
| Enterprise term | What it means |
|---|---|
| Company Brain / Intelligence OS | Structured company intelligence across business functions, organized as Maps, Models and Briefs |
| Context Library | Reusable company intelligence, governance, approved sources, decisions and operating knowledge |
| Governance OS | Results, Rules and Rights defining expected outcomes, applicable requirements and decision authority |
| AI operating model | How work is assigned across your people and AI, who decides and how results are reviewed |
| Decision rights | Who is authorized to make each decision, such as approving a payment or changing customer scope |
| Accountability | Who owns the result and is responsible for addressing a problem |
| Access control | Which people and systems may use particular records or perform particular actions |
| Information governance | Who owns company information and the conditions on its use, including whether it is approved for internal work or public use |
| Context Engineering | Preparing company knowledge so your people and AI use relevant facts, business context and decision standards for the work |
| Knowledge architecture | How company knowledge is organized and connected, including services, customers, roles and business terms |
| Information quality | Whether information is accurate, current, consistent and suitable for the task |
| Source lineage and provenance | Where information came from, which statements it supports and which outputs use it |
| Grounding | Supporting an answer with relevant evidence |
| Data contract | An agreed structure for information, including required fields and quality checks, so programs can use it consistently |
| Exception management | Routing missing information, failed checks and out-of-scope requests to the accountable person |
| Change impact management | Identifying what needs review when a source, rule or business requirement changes |
| Acceptance criteria and evidence | The agreed conditions the work must meet, together with test results showing whether it met them |
Governance and Company Brain
Questions & answers
What is AI governance?
AI governance establishes decision rights, accountability and the controls around AI-supported work. We define the roles, responsibilities and operating controls for your people and AI, so your team knows who owns each outcome, what AI is responsible for and which financial or customer commitments require approval.
What is a Company Brain?
The Company Brain is the structured intelligence about your company: its business functions, performance drivers, priorities and decisions. The core Intelligence OS organizes 36 intelligence elements across 12 business functions, with a Map, Model and Brief for each function.
Do the 36 intelligence elements include governance?
The 36 elements describe the core Intelligence OS. Governance is a separate layer: Results, Rules and Rights across the same 12 core functions, giving 36 governance controls in the core design. Your engagement specifies the functions and elements included.
What is in the Context Library?
The Context Library brings together company intelligence, governance, approved sources, decisions and operating knowledge. Context Engineering prepares the relevant knowledge for your people and AI to use in the agreed work.
Who approves financial decisions and customer commitments?
Your team controls budgets, authorizes payments and approves pricing, scope and customer commitments. AI supports the work within defined decision rights and financial controls.
How do we know the AI governance controls work?
The acceptance record identifies the agreed checks, the observed test results and the issues still needing attention. A written governance policy or a completed document does not by itself establish that a control works in operation.
What is the difference between the company foundation and a workflow installation?
The company foundation is the Company Brain, Context Library and governance content defined in the engagement. A workflow installation applies the relevant company knowledge and controls to a selected business responsibility, with an agreed output, acceptance evidence and operating handoff. The engagement identifies which parts of the broader foundation are included.