2–4 weeks
AI Strategy & Roadmapping
Turn AI ambition into a sequenced, funded plan your team can actually execute.
What You Get
Outcomes
Tangible results you can expect from this engagement.
Deliverables
What's Included
Concrete outputs you receive at the end of the engagement.
- 1 Current-state assessment report
- 2 AI opportunity matrix scored by impact and feasibility
- 3 90-day implementation roadmap
- 4 Governance and risk framework
- 5 Executive presentation deck
Who It's For
Recommended For
Measurement
Success Metrics
How we track and prove the impact of this engagement.
What This Engagement Looks Like
Most AI strategy work fails in one of two ways: it’s either too abstract to act on, or too tactical to get funded. We’ve designed this engagement to land in the narrow space between—specific enough for your engineering team to start building, structured enough for your CFO to approve the spend.
We start with a focused discovery phase. Over the first week, we interview stakeholders across business and technology teams, review your current data infrastructure, and catalog the AI use cases already floating around your organization. In our experience, most mid-size companies have between 15 and 40 informal AI ideas scattered across departments. The problem is never a lack of ideas—it’s a lack of prioritization.
From there, we score each use case against a matrix that weighs business impact, technical feasibility, data readiness, and organizational risk. This isn’t a theoretical exercise. We pull in actual data about your systems, your team’s capabilities, and your regulatory environment. The output is a ranked list of opportunities with realistic ROI estimates—not best-case fantasies.
How We Build the Roadmap
The 90-day roadmap is sequenced around dependencies, not ambition. We identify which use cases can start immediately with existing data and infrastructure, which ones need preparatory work, and which ones should wait. Each phase has clear milestones, resource requirements, and decision points.
We also build in governance from the start. That means defining who approves model deployments, how you’ll monitor for drift and bias, what your escalation paths look like, and how you’ll handle the inevitable edge cases. Organizations that bolt governance on after deployment spend roughly three times as much fixing problems as those who build it in from the beginning.
What Makes This Different
We don’t sell AI. We don’t have a proprietary platform to push. Our recommendations are based on what will actually work given your constraints—budget, team, data, timeline, and risk tolerance. If the right answer is “don’t build AI for this, use a rules-based system,” we’ll tell you that.
Every deliverable is designed to be used, not filed. The executive presentation is built for your actual audience—whether that’s a board of directors, a steering committee, or a CEO who wants the answer in two pages. The technical roadmap is written for the people who will build it, with enough detail to start sprint planning.
We’ve delivered this engagement for organizations ranging from 200-person companies evaluating their first AI project to enterprises with existing ML teams who need strategic realignment. The common thread is a need to move from “we should do something with AI” to “here’s exactly what we’re doing, why, and when.”
Risk Management
Risks & Mitigations
We plan for what can go wrong so you don't have to.
Governance gaps lead to compliance exposure
We embed a governance framework from day one, covering data privacy, model oversight, and audit trails—before any deployment begins.
Unrealistic expectations about AI capabilities
Every use case goes through a feasibility assessment that includes technical constraints, data readiness, and honest timeline estimates. We flag what's not ready.
Vendor lock-in from early platform decisions
Our roadmaps are platform-aware but not platform-dependent. We design for portability and recommend abstraction layers where they make sense.
FAQ
Frequently Asked Questions
How is this different from what a big consulting firm would deliver?
Most large firms hand you a 200-slide deck and leave. We deliver a working plan with specific technical recommendations, realistic timelines, and a governance structure—not just a vision document. And we stay available to support execution.
What if we already have AI projects in flight?
Even better. We assess what's working, what's stalled, and where the gaps are. Many clients find that their existing projects need repositioning more than their future ones need planning.
Do we need to have our data in good shape before we start?
No—data readiness assessment is part of the engagement. We'll identify gaps and build a data preparation plan into the roadmap. Waiting for perfect data is one of the most common reasons AI projects never launch.
What happens after the roadmap is delivered?
You'll have everything you need to execute internally or with any implementation partner. If you want PADMG to continue into execution, we can scope that separately—but the roadmap stands on its own.
Ready to get started?
Let's scope a ai strategy & roadmapping engagement for your team. 30-minute call, no pitch deck.
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