AI-First GTM Readiness Checklist
A 10-point audit to see if your revenue team is ready for AI automation. Check what applies, score your readiness, and get a recommendation for where to start.
Assessment
Data Foundation
1. Is your CRM API-accessible?
Salesforce, HubSpot, or similar with REST API. AI systems need programmatic access to your customer data to operate autonomously.
3. Are your lead sources centralized in one system?
All inbound, outbound, and partner leads flow into a single source of truth. Fragmented lead data makes AI scoring impossible.
4. Do you track win/loss reasons on every closed deal?
Structured win/loss data on every opportunity. This is the training data AI needs to predict outcomes and improve messaging.
6. Do you have at least 12 months of historical deal data in your CRM?
A year of deal velocity, conversion rates, and outcome data. AI models need sufficient history to identify patterns and make predictions.
Process Maturity
2. Do you have a documented winning sales script or talk track?
A repeatable framework your best reps follow. AI coaching and outbound systems need a baseline to optimize from.
5. Is your sales process documented with defined stages and exit criteria?
Written stage definitions with clear requirements to advance. Without this, AI cannot accurately assess pipeline health or forecast.
7. Are your marketing and sales teams using the same lead definitions?
Agreed-upon MQL/SQL criteria and shared SLAs. Misaligned definitions create data quality issues that compound in AI systems.
9. Is your pricing standardized enough to quote without manual intervention?
A pricing model that can be expressed in rules, not judgment calls. AI-powered quoting requires structured pricing logic.
Infrastructure
8. Do you record and store sales calls?
Gong, Chorus, or similar conversation intelligence platform. Call recordings are the highest-signal data source for AI coaching.
10. Does your team have a dedicated RevOps or Sales Ops resource?
At least one person whose job is revenue operations. AI systems need ongoing tuning and someone who owns the data infrastructure.
Why readiness matters
AI systems compound on good data and clean processes. Deploying autonomous outbound on a broken CRM creates expensive noise. Deploying call coaching without recorded calls creates nothing. This checklist maps the prerequisites so you invest in the right sprint at the right time.
16-20
AI-Ready
Your stack is ready for AI automation. Start with the highest-ROI sprint.
10-15
Almost There
A few gaps to close. Build your data foundation first.
0-9
Foundation First
Foundational work needed before AI can compound.
Want help closing the gaps?
Book a strategy call. We assess your current state and map the fastest path to an AI-ready revenue stack.
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