1. Drive Execution Across the Wind Engineering AI Portfolio 

• Maintain visibility across all approved AI initiatives. 

• Monitor progress against commitments, milestones, deliverables, and success metrics. 

• Ensure initiative owners remain aligned to agreed execution plans. 

• Proactively identify execution risks, delays, and resource constraints. 

• Escalate issues requiring leadership intervention. 

• Develop consistent project health and portfolio status reporting. 

2. Own Portfolio Operations and Governance 

• Maintain the master portfolio of AI initiatives. 

• Track initiatives through relevant lifecycle stages, including opportunity identification, assessment, business case development, proof of concept, pilot, production deployment, scaling, and sustainment. 

• Ensure governance requirements are completed at appropriate maturity gates. 

• Coordinate portfolio reviews. 

• Support prioritization activities led by the AI Process Transformation Lead. 

• Maintain portfolio documentation, scorecards, and reporting assets. 

3. Establish and Operate Portfolio Management Systems 

• Build and maintain portfolio dashboards and executive reporting mechanisms. 

• Create standardized project tracking and performance measurement processes. 

• Define portfolio health indicators and key performance measures. 

• Provide leaders with visibility into initiative health, resource capacity, risks, dependencies, value realization progress, and adoption metrics. 

• Enable data-driven portfolio resolutions and transparent leadership reviews. 

4. Lead Cross-Functional Program Coordination 

• Coordinate execution across Engineering, Digital, ARC Foundry, and business stakeholders. 

• Manage dependencies across initiatives and functional teams. 

• Facilitate alignment when initiatives span multiple engineering domains. 

• Identify and resolve execution bottlenecks. 

• Support resource planning and workload balancing across the portfolio.