A growth-stage R&D and software development company needed a structured, measurable approach to adopting AI across it’s teams and functions. AI experiments were happening in pockets, portfolio leadership teams lacked alignment, and no unified roadmap existed to guide priorities or investment.

AXP partnered with the executive leadership to deploy a complete AI adoption framework, creating a clear, data-driven system for scaling AI across the organization.

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• Aligned leadership on an AI Charter & KPI priorities: Unified stakeholders around a single North Star vision, KPI weights, functional scope, & guardrails for responsible AI adoption.
   

• Defined maturity ladders across all engineering functions: Established clear maturity paths for each functional team within the organization, giving staff a shared understanding of AI progression milestones towards core objectives and tasks.
   

• Built a baseline scorecard with measurable KPIs: Selected metrics tied to Velocity, Quality/Risk, Cost, Innovation, and Team Health, and assessed each function’s current stage to anchor future targets.
   

• Prioritized high-impact AI initiatives: Created a Use-Case Matrix to score initiatives by Impact, Complexity, and Risk, linking each priority directly to functional targets and KPI improvements.
   

• Developed actionable AI roadmaps for each function: Converted chosen initiatives into sequenced roadmaps with stage-gates, guardrails, tool strategy, resourcing needs, and success criteria.
   

• Implemented quarterly reporting and governance: Built a repeatable Quarterly AI Report tracking progress to targets, maturity stage movement, compliance, and ROI, enabling leadership to continuously adjust priorities with clarity into impact.
   

Outcome: A unified AI operating system that improved engineering velocity, quality, and operational resilience, supported by clear metrics, aligned leadership, and disciplined execution.