AI Strategy•2025•Case Study

AI Product Prioritization Framework

Role:

AI Product Manager at Magnetiz.ai

Focus:

Prioritization Framework for AI Initiative Planning

Problem

As our AI delivery team scaled across multiple enterprise clients, our roadmap planning cycles began to lose clarity. Engineering teams were overloaded with disconnected feature requests, and stakeholders struggled to align on what should come next. Roadmap churn was high—priorities shifted frequently, creating delivery delays and reduced confidence in our planning process.

We needed a repeatable framework to evaluate and prioritize AI initiatives based on business value, technical feasibility, and operational fit.

Approach

Stakeholder Discovery

I ran interviews with product leads, engineering managers, operations directors, and client success to understand:

What "value" looked like across teams
Where priorities conflicted
Where we lacked shared evaluation criteria

Framework Design

I developed a scoring system that evaluated AI use cases across 5 weighted dimensions:

Business Impact (Revenue potential, efficiency gains)
Operational Fit (How well the AI solution fits existing workflows)
Technical Feasibility (Model availability, data quality)
Speed to Value (Estimated time to pilot/impact)
Strategic Alignment (Company and client-level goals)

Implementation

I introduced the framework into roadmap planning using a shared Airtable and async pre-work. Each proposed initiative was scored collaboratively in planning sessions. The result: clearer discussions, fewer last-minute pivots, and more confidence from leadership.

Outcome

35% reduction in roadmap churn across a 6-month period
Faster decision-making in roadmap meetings and sprint planning
95% pilot-to-production success rate, in part due to stronger upfront alignment
The framework became the default prioritization method across 3 internal teams and was referenced in client workshops as a decision model

Artifacts (Available on request)

Prioritization Scoring Template (Notion)
Evaluation Rubric & Weighted Matrix (Airtable)
Facilitation Agenda for Cross-Functional Planning Session

Why This Matters

AI product work is inherently ambiguous. This framework gave our team a way to cut through that ambiguity, stay focused on outcomes, and reduce friction between product, research, and operations. It's now baked into how we evaluate every roadmap decision.