Portfolio governance for a multi-million-dollar AI and technology program
PMO foundations, hybrid delivery models, and executive visibility across an active AI portfolio.
- 20%Predictability & visibility lift
- 40%Cycle-time reduction
- Multi-millionPortfolio under governance
The challenge
A growing enterprise technology portfolio—spanning AI initiatives and core platform work—needed consistent governance, clearer decision rights, and reliable executive reporting. Delivery teams were moving fast, but dependencies, risks, and resource trade-offs were difficult to see across programs.
Frame, ship, govern
- Frame
Established portfolio governance and PMO foundations: standardized stage gates, RAID discipline, owner tracking, and a hybrid Agile/Waterfall operating model suited to mixed workstreams. Aligned steering forums on outcomes, escalation paths, and what “green” meant for production-critical AI delivery.
- Ship
Provided program leadership across active AI and technology initiatives—surfacing blockers early, coordinating engineering dependencies, and stabilizing critical production deployments. Drove design and enforcement of implementation SOPs, playbooks, and operational runbooks that teams could reuse.
- Govern
Delivered leadership-ready portfolio health reporting, post-launch optimization reviews, and KPI signals tied to delivery quality. Mentored delivery leads on consistent PM practice and change management for new AI capabilities.
Outcomes
- Improved project predictability and portfolio visibility by approximately 20%
- Reduced delivery cycle time and rework by approximately 40% through repeatable playbooks
- Stabilized critical AI production deployments with clear escalation and ownership
- Left scalable PMO artifacts—not ad-hoc coordination—as the operating baseline
Practice areas
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