The problem this solves
Most companies approach AI from the tool side: someone trials a writing assistant, someone else demos an SDR agent, and six months later there are eleven subscriptions, no measurable outcome, and growing skepticism. The missing piece is not tooling, it is a map: which parts of your GTM process have the repetition, data, and volume that AI actually rewards, and which are better left to humans. Without that map, AI spend follows enthusiasm rather than value.
How we work
We walk your GTM operation end to end, from demand generation through sales, service, and operations, looking for the specific conditions where AI pays off: high-volume repetitive work, decisions starved of context that exists somewhere in your systems, and content or communication bottlenecks. Each candidate use case gets documented with the process it changes, the data it requires, and the effort to implement.
Then we score the inventory on impact and feasibility, using your data reality rather than vendor promises. A use case that needs clean CRM context your portal does not have scores accordingly, and that dependency gets named.
The deliverable is a ranked AI opportunity map with a recommended starting sequence: which use cases to pilot first, what each requires, and which popular ideas we would explicitly skip. It feeds directly into AI strategy and use case design work if you continue down the path.
Deliverables
- AI use case inventory across marketing, sales, service, and operations
- Impact and feasibility scoring grounded in your actual data and systems
- Dependency map showing what each use case needs before it can work
- Ranked starting sequence with explicit skip recommendations
- Findings readout with your leadership team
What buyers ask before scoping.
How is this different from the AI Data Readiness Assessment?
This assessment finds and ranks the opportunities; the data readiness assessment tests whether your data can support them. They connect: our feasibility scoring flags data dependencies, and the readiness assessment is how you verify the flagged ones. If you already have a shortlist of use cases, you may only need the readiness work.
Do we need to be on HubSpot for this to be useful?
No. The opportunity map is drawn from your processes, whatever stack runs them. That said, we know the HubSpot AI surface deeply, including Breeze agents and where they genuinely perform versus where they need more context than most portals hold, so HubSpot-based companies get unusually specific feasibility answers.
Does this include implementing any of the use cases?
No. This is deliberately a diagnostic: implementation decisions made mid-assessment tend to favour whatever is easiest to demo. The output is designed to hand off cleanly into AI use case design and development engagements, with the business case already argued and the dependencies known.
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