Editable workbook · Enterprise AI strategy

Enterprise AI Strategy Template

This browser-viewable template helps a company define its own AI strategy using questions aligned to mission, opportunity selection, governance, platform architecture, responsible use, change management and measurable value.

Your answers auto-save in this browser as you type.

Data protection note: draft answers are stored only in this browser's local storage on this device. They are not submitted to this website, sent to a server, or shared with Fede's AI & Data Lab. Anyone with access to this browser profile may be able to view the saved draft. Use “Clear saved draft” or clear site data to remove it.

Organization

Strategy owner

Date

Version

1. Strategic intent: what must AI serve?

Start with the mission and values. AI should support existing organizational outcomes rather than become a separate technology agenda.

What mission, stakeholder outcomes or business priorities must AI advance?

Which values become non-negotiable AI design requirements?

Which decisions, data or actions must remain under explicit human or controlled-system authority?

2. Stakeholder and risk context

Who benefits if the strategy succeeds?

Who carries risk, burden or oversight responsibility?

What trade-offs must be made explicit before implementation?

3. Opportunity portfolio: select where AI has asymmetric value

List candidate AI opportunities and evaluate them through impact, feasibility and responsible-use lenses.

Opportunity ID	Candidate opportunity	Impact question	Feasibility question	Responsible-use question	Initial priority
OPP-01
OPP-02
OPP-03

Strong early candidates often include compliance and error detection, structured data automation, research synthesis, service preparation, defensive security triage and carefully governed ambient assistance. Use the predefined opportunity IDs above, such as OPP-01, OPP-02 and OPP-03, when later sections need to distinguish portfolio-wide answers from opportunity-specific answers.

4. Risk classification and oversight model

Scope this section: choose whether the answers below apply to the whole AI opportunity portfolio or to selected opportunity IDs from section 3.

Applies to

Opportunity IDs, if specific

Green: low-risk productivity

Yellow: sensitive or externally visible

Red: high-stakes decisions

Where should humans sit in the OODA loop?

5. Operating model: four AI maturity pillars

Scope this section: use this section for portfolio-wide operating capabilities unless a pillar is being designed for a named opportunity.

Applies to

Opportunity IDs, if specific

Pillar	Current state	Target state	Owner	Next action
Enablement: secure access
Literacy: hands-on skills
Innovation labs: safe testing
Governance: lifecycle control

6. Architecture choices

Scope this section: mark whether this is the shared enterprise AI platform architecture or a solution architecture for one or more opportunities.

Applies to

Opportunity IDs, if specific

Which platform layers are required?

What data architecture principles will govern AI context?

Which authoritative systems should AI access through governed tools or APIs?

How will the Agents Rule of Two be enforced?

7. Governance, evaluation and evidence

Scope this section: portfolio-wide governance sets minimum rules; opportunity-specific entries define additional evidence gates for selected use cases.

Applies to

Opportunity IDs, if specific

Each AI initiative has a named business owner, risk owner and technical owner. Success metrics include baseline time, cost, error, quality, risk or experience measures. High-risk outputs require source evidence, traceability and human review. Model changes trigger retesting against accepted evaluation scenarios. Production systems have monitoring, audit logs, escalation paths and decommissioning criteria.

What evidence is required before a pilot can move to production?

8. Change management and workforce design

Scope this section: separate general adoption planning from role, workflow or stakeholder impacts tied to a specific opportunity.

Applies to

Opportunity IDs, if specific

How will teams learn, experiment and build trust safely?

Which human skills must be preserved or strengthened?

Where might resistance appear and how will it be addressed?

How will environmental, labor and cost impacts be tracked?

9. Implementation roadmap

Scope this section: create a portfolio roadmap, then reference opportunity IDs where a horizon includes a specific pilot, production release or decision gate.

Applies to

Opportunity IDs, if specific

Horizon	Outcomes	Initiatives	Controls	Decision gate
0-90 days
3-6 months
6-12 months

10. Executive strategy statement

Summarize the AI strategy in one page.