Phase 2: Structured Expansion (Months 1-3)

Phase 2 scales AI-assisted development beyond pilot teams with formal governance frameworks, CI/CD pipeline integration, cross-team knowledge sharing, expanded metrics, and structured risk assessment. Where Phase 1: Foundation proved the concept with controlled pilots, Phase 2 builds the organizational infrastructure to support 5-10 teams operating under AEEF standards simultaneously. This is the phase where ad hoc practices become repeatable processes and informal guidelines become enforced governance.

Goals

Phase 2 has five primary goals:

1. Implement formal governance — Establish approval workflows, review gates, compliance checkpoints, and audit mechanisms that scale beyond individual team discipline — see Governance Framework Implementation
2. Integrate AI governance into CI/CD — Automate quality checks, security scanning, and governance validation within existing build and deployment pipelines — see CI/CD Pipeline Integration
3. Enable cross-team learning — Build communities of practice, shared prompt libraries, and knowledge-sharing forums that accelerate adoption — see Cross-Team Knowledge Sharing
4. Expand measurement — Scale metrics from pilot-level to team-level and organizational-level KPIs with dashboards and trend analysis — see Expanded Metrics & KPI Dashboard
5. Scale risk management — Develop risk categorization, automated scoring, and escalation procedures that handle the increased scope of adoption — see Risk Assessment Scaling

Prerequisites from Phase 1

Phase 2 MUST NOT begin until the following Phase 1 prerequisites are verified:

Mandatory Prerequisites

• Phase 1 go/no-go review completed with a "Go" or "Conditional Go" decision from the Steering Committee
• At least one AI tool assessed, approved, and deployed with approved configurations
• Baseline security policies documented, approved, and enforced
• All pilot team developers completed training and passed assessment
• At least one pilot project completed with documented results
• Measurement baselines established for velocity, quality, security, and developer experience
• No unresolved Critical or High severity security incidents from pilot period

Recommended Prerequisites

• Pilot team developer satisfaction score >= 3.5/5.0
• Pilot velocity data shows no degradation (or shows improvement)
• Initial prompt patterns documented by pilot teams
• Lessons-learned session conducted with pilot teams
• Phase 2 budget approved by executive sponsor

Deliverables

By the end of Phase 2, the following artifacts MUST be produced:

Deliverable	Owner	Approval Required
Governance Framework document	Governance Lead	Steering Committee + Legal
CI/CD pipeline configurations with AI governance gates	Platform Engineering	Security Lead + Governance Lead
Community of Practice charter and operational plan	Knowledge Sharing Lead	Engineering Director
Shared prompt library (initial population)	Community of Practice members	Tech Lead review
Organizational KPI dashboard	Metrics Lead	Steering Committee
Risk categorization matrix and scoring automation	Risk Lead	CISO + Steering Committee
Expanded training materials for new teams	Training Lead	Engineering Director
Phase 2 Completion Report with go/no-go recommendation	Phase Lead	Steering Committee

Team Composition

Phase 2 expands the core team and introduces new roles:

Core Team (Dedicated)

• Phase Lead (1 person, 75-100% allocation) — Accountable for Phase 2 deliverables and cross-team coordination. This SHOULD be the same person from Phase 1 for continuity.
• Governance Lead (1 person, 75% allocation) — Owns governance framework design, implementation, and enforcement. This is a new role in Phase 2.
• Platform Engineering Lead (1 person, 75% allocation) — Owns CI/CD integration, tool scaling, and configuration management.
• Knowledge Sharing Lead (1 person, 50% allocation) — Facilitates communities of practice, prompt libraries, and cross-team learning.

Expanded Team

• Team Champions (1 per expanding team, 10-15% allocation) — Serve as the AI adoption point of contact within each team. They receive advanced training, facilitate team onboarding, and escalate issues.
• Security Engineers (1-2 people, 25-50% allocation) — Support governance gate implementation, security scanning configuration, and incident response.
• Metrics Analyst (1 person, 50% allocation) — Expands dashboards, produces reports, and supports data-driven decision-making.

Timeline

Period	Key Activities
Weeks 5-6	Launch Phase 2; design governance framework; begin CI/CD integration planning; identify expansion teams; onboard first wave (2-3 teams)
Weeks 7-8	Deploy governance workflows; configure CI/CD gates; launch Community of Practice; begin prompt library population
Weeks 9-10	Governance framework operational; onboard second wave (2-3 additional teams); expand KPI dashboards; mid-phase review
Weeks 11-12	Risk assessment automation operational; cross-team showcases; all expansion teams active; full dashboard operational
Week 13	Compile Phase 2 Completion Report; conduct go/no-go review for Phase 3; lessons-learned sessions

Success Criteria

Phase 2 is considered successful when ALL mandatory criteria are met:

• Governance framework implemented and operational for all expansion teams
• CI/CD pipelines include automated AI governance checks for all expansion teams
• Community of Practice meets regularly with active participation from all teams
• Organizational KPI dashboard operational with automated data collection
• Risk assessment process scales to handle all expansion teams without bottlenecks
• No Critical severity security incidents attributable to AI tool usage
• At least 70% of expansion team developers report satisfaction >= 3.5/5.0
• Aggregate defect density across all teams has not increased more than 5% relative to baselines

Phase Gate: Go/No-Go for Phase 3

At the end of Phase 2, the Steering Committee MUST conduct a formal go/no-go review for Phase 3: Enterprise Scale. The Phase Lead SHALL present the Phase 2 Completion Report demonstrating that governance, automation, and measurement infrastructure can support organization-wide adoption.

Phase 2 is operationally the most complex phase. It is where the transformation either builds sustainable momentum or stalls. Organizations that invest in robust governance and genuine knowledge sharing during this phase will find Phase 3 a natural progression rather than a disruptive leap.