AI is no longer a tool, it's a teammate. Every high-performing company starts in chaos and scales toward predictable revenue. This is the GTM maturity curve. The 5 stages every teams go through, the pain points at each, and how AI agents and humans work together to drive growth.
Stage 1: Ad Hoc (The Wild West)
“We don't really have a process. We just sell.“
Pains:
- No clear ICP definition
 - No primary channel
 - Random leads, inconsistent follow-ups
 - Founders do everything manually
 
Humans: talk to users
- Founders sell, guess ICP, test scripts manually
 
AI Agents: basic assist
- Draft outreach copy
 - Enrich leads
 - Speed up ICP testing
 
AI Contribution:
- ~10%, Humans run the show, AI supports
 
Stack
- Google Sheets to track conversations with prospects
 - ChatGPT to write and iterate on the messaging
 - Clay for list building and data enrichment
 
Stage 2: Undefined (The GTM Fog)
“We're active, but it's messy.“
Pains:
- CRM exists but isn't used properly
 - No clarity on what works
 - Sales and marketing not aligned
 
Humans: Validate what's working
- Early GTM hire qualifies and closes deals
 - Founders still drive GTM but focus on ops and basic reporting
 
AI Agents: Automation + feedback loop
- Take notes on calls, summarize meetings
 - Identify what channels or personas work
 - Automate follow-ups
 
AI Contribution:
- ~25%, Humans experiment, AI makes them faster
 
Stack
- Hubspot for GTM tracking and sequences
 - Instantly for email automation
 - Clay for list building and data enrichment
 
Stage 3: Progressive (Repeatable Motion Begins)
“We're starting to see what works and double down.“
Pains:
- Manual processes slow things down
 - Friction in handoffs
 - Marketing, Sales, CS not fully in sync
 
Humans: Scale what works
- Full-stack AEs own enterprise deals
 - Leadership begins to focus on metrics
 - GTM Engineer starts building custom AI agent
 
AI Agents: GTM Co-pilot
- Surface intent signals (website visits, product usage, job changes)
 - Enrich and prioritize leads automatically
 - Route opportunities based on territories, rep capacity, or deal size
 - Suggest next-best action and sequences
 - Sync golden records across CRM, enrichment, and engagement tools
 
AI Contribution:
- ~50%, AI is now a co-pilot. Humans drive outcomes.
 
Stack
- Hubspot/Salesforce is fully adopted and becomes the source of truth
 - Cargo to build custom AI agents for scoring, enrichment, lead routing
 - Outreach to pilot the work of the fullstack AEs
 - Gong to analyze talk tracks, coach reps
 
Stage 4: Mature (The GTM Engine)
“We’re aligned across functions and predictably growing.“
Pains:
- Cross-team orchestration becomes complex
 - Scaling personalization is hard
 - Holistic understanding of the engine
 - Clear attribution model
 
Humans: Upsell & strategic deals
- Leadership drives strategy
 - Full-stack AEs own expansion and entreprise deals
 - GTM Engineers manage AI workforce
 
AI Agents: Multi-agent orchestration
- Specialized AI agents collaborate across the all funnel: qualification, routing, upsell, reactivation
 - AI defines when they need to handle the lead vs an AEs
 - Coordinate campaigns, track pipeline health, enforce SLA handoffs
 - Suggest coaching points from calls
 
AI Contribution:
- ~75%, AI runs the GTM engine. Humans supervise and improve it.
 
Stack
- Cargo to manage AI workforce and human workforce
 - Hubspot as the unified system of record
 - Outreach for multi-channel account engagement
 - Gong for revenue intelligence
 - Hex for GTM analytics and dashboards
 
Stage 5: Self-Optimizing (Compounding Growth)
“Our GTM system evolves with the market.“
Pains:
- Staying agile while scaling
 - Balancing fast growth with experimentation
 - Hiring fast enough
 
Humans: High-level strategy + market bets
- Leadership sets high-level priorities
 - GTM Engineers maintain the AI architecture
 - Full-stack AEs close high-touch strategic deals
 
AI Agents: Continuous self‑optimization
- Run autonomous A/B tests
 - Optimize playbooks continuously
 - Forecast revenue, recommend hiring
 - Trigger next best actions from customer behavior
 
AI Contribution:
- ~90%+, AI drives growth, humans steer direction.
 
Stack:
- Same stack than for stage 4