A CFO working session on turning go-to-market into the company’s strongest revenue engine.
At a sub-$100M company, three pressures compound into the same outcome.
Leadership wants AI-native now, but the route from mandate to revenue is unclear.
Teams are willing, but lack tools, training, and permission to change workflow.
No single accountable person connects governance, systems, adoption, and revenue outcomes.
Customer context is scattered, so every deal restarts from zero.
Sales is ~10 people. Every rep rebuilds the same customer story from scratch; the lifetime journey lives nowhere durable.
Who owns AI governance today?
Who is accountable for how AI reshapes GTM going forward?
You sell agents to your clients. Build one for yourselves.
Calls, demos, objections, champions, buying committee signals.
Campaign source, page intent, content history, research interest.
Stage movement, next steps, procurement, forecast, win/loss.
Sharper segments, proof gaps, message-market fit.
Account briefs, objection packs, next-best actions.
Pattern evidence from real enterprise conversations.
The gap is not enthusiasm. It is ownership, sequencing, and whether the workflow actually changes.
Agentic AI return expectations are high; U.S. firms report even higher targets.
Google Cloud reports first-year ROI among executives measuring AI returns.
McKinsey high performers redesign workflows instead of bolting AI onto old process.
Gartner flags unclear value, cost, and weak risk controls as cancellation drivers.
That is the internal inequality we level: one governed customer brain, one owner, and a first workflow that proves revenue value before the transformation expands.
IBM’s pressure point: only about a quarter of AI initiatives have delivered expected ROI.
Sales first. One measurable win. Then expand into the north star.
Map exactly where the pipeline leaks: handoffs, CRM evidence, deal notes, lost reasons, proof gaps, and governance owners.
Build one agent around one revenue workflow. Instrument it before scaling it.
Turn the validated workflow into the centralized customer-intelligence agent across marketing, sales, and product.
Listen first. Go deep on one sales workflow. Prove whether it moves revenue.
Find the live revenue leak.
Build the smallest useful agent.
Track conversion, cycle time, and reuse.