Home / Solutions / AI Strategy
AI Strategy
Know where AI actually creates value in your organization, before you spend on building anything.
Most companies don’t have an AI problem — they have a prioritization problem. We help you cut through the noise, evaluate your real options, and leave with a roadmap you can fund and defend.
The Problem
Most AI initiatives fail from a prioritization problem, not a technical one.
Teams jump to a vendor, a tool, or a pilot without agreeing on which problems are actually worth solving first, or whether a use case belongs on a platform they already own, a custom build, or a lighter workflow automation. The result is scattered pilots that never add up to anything leadership can point to.
What We Do
Five things, in service of one prioritized roadmap.
Opportunity Mapping
Surveying the organization to identify where AI could realistically move a metric leadership actually cares about.
Build vs. Buy vs. Platform-Native
Deciding whether a use case belongs on a platform you already run, a custom application, or a lighter workflow automation.
Prioritization & Sequencing
Ranking candidate initiatives by feasibility, data readiness, and expected impact, not by who asked loudest.
Stakeholder Alignment
Getting leadership and the teams who’ll live with the outcome aligned before money is committed.
Vendor & Tool Evaluation
Assessing platforms and vendors against your actual requirements, not their marketing.
How We Get There
Four steps to a roadmap you can defend.
Discovery Interviews
Conversations across the business to surface real pain points and appetite, not just leadership’s assumptions.
Opportunity Assessment
Evaluating candidate use cases for feasibility, data readiness, and impact.
Roadmap Development
Sequencing initiatives into a plan that’s fundable in stages, not all at once.
Executive Readout
Presenting the roadmap, and the reasoning behind it, to the people who have to approve it.
Frequently asked questions
Answers to common AI strategy questions
How is this different from the Data Readiness Diagnostic?
The Data Readiness Diagnostic is tactical: it evaluates one workflow you already want to automate. AI Strategy is portfolio-level: it looks across the organization to decide which initiatives are worth pursuing at all, and in what order, before any single workflow is scoped.
Do you help us decide whether to build on Salesforce/Palantir versus a custom application?
Yes. That decision is central to the engagement — whether a given use case belongs on a platform you already run, a custom-built application, or a lighter workflow automation, evaluated against your actual data, team, and timeline rather than a vendor’s roadmap.
What’s the deliverable?
A prioritized roadmap of AI initiatives ranked by feasibility and impact, the reasoning behind build-vs-buy-vs-platform calls for each one, and a sequencing plan you can take into a budget conversation.
Who from our team should be involved?
At minimum, the executive sponsor and the operational leaders closest to the processes being considered. The roadmap holds up better when the people who’ll live with the outcome are part of building it.
Get Started