Non-Engineering Function Enablement
A company does not become AI-first when only engineering adopts AI. It becomes AI-first when core business functions redesign their workflows, controls, and operating cadence around AI-assisted work.
This section closes that gap.
Objective
Provide a practical operating model for extending AEEF principles beyond engineering into business functions with clear ownership, controls, and value metrics.
Function-by-Function Adoption Map
| Function | Primary AI Opportunities | Core Controls | KPI Examples |
|---|---|---|---|
| Product Management | PRD drafting, experiment design, backlog synthesis | Human approval for scope and prioritization decisions | PRD cycle time, experiment throughput |
| Customer Support | Case summarization, response drafting, knowledge suggestions | PII controls, escalation rules, sampled QA | First response time, resolution time, CSAT |
| Sales and Revenue Ops | Account research, proposal drafting, call summary | Data boundary policy, approval for external communications | Proposal turnaround time, win-rate support metrics |
| Finance | Forecast commentary, anomaly triage, variance narratives | Source-of-truth reconciliation, audit trail | Month-end close efficiency, forecast accuracy |
| Legal and Compliance | Clause analysis, policy draft support, obligation extraction | Attorney/compliance officer sign-off required | Contract review cycle time, policy update lead time |
| HR and Talent | JD drafting, learning plans, skill mapping | Bias review, privacy controls | Time-to-hire support metrics, training completion |
Company-Wide Operating Rules
- Every function MUST define human decision rights for AI-assisted tasks.
- Every external-facing artifact generated with AI MUST have accountable human approval.
- Sensitive data classes MUST be mapped per function before tool rollout.
- Function-level KPI dashboards MUST include both productivity and risk indicators.
- Each function MUST nominate an AI Function Lead linked to the CoE.
Rollout Model
Wave 1 (0-90 days)
- Select 2-3 business functions with high-volume repeatable workflows
- Define approved use cases and blocked use cases
- Launch role-specific training and baseline measurement
Wave 2 (90-180 days)
- Expand to additional functions
- Integrate function workflows into shared governance reporting
- Introduce cross-function playbooks and reusable prompts/templates
Wave 3 (180+ days)
- Standardize AI operating reviews in quarterly business reviews
- Tie function-level AI KPIs to planning and investment decisions
- Mature toward AI-native business process redesign
RACI Model
| Activity | Function Leader | CoE | Security/Legal | Operations |
|---|---|---|---|---|
| Use-case selection | A | C | C | I |
| Tool and data policy | C | C | A | I |
| Workflow redesign | A | C | C | R |
| KPI reporting | A | C | I | R |
| Incident escalation | R | C | A | C |
Success Criteria
- At least three non-engineering functions running governed AI-assisted workflows
- Function-level risk events stable or improving quarter-over-quarter
- Demonstrable cycle-time improvement without compliance exceptions
- CoE review cadence includes business functions, not only engineering teams