Machine Speed on Prospecting, Human Judgement at the Close
Where AI compresses outbound’s grunt work, and where it just generates more bad-fit pipeline, faster.
AI & GTM
Leveraging AI in GTM: Where It Actually Moves the Number
AI doesn’t fix your commercial engine. It amplifies whichever one you actually have — a disciplined process gets faster, a broken one breaks faster and more expensively, just with more confident-sounding output.
The Amplifier Effect
Every AI tool a scaling business adopts gets layered on top of a commercial engine that already exists, warts and all. If that engine has a defined process and clean data, AI genuinely compresses the work. If it has undefined qualification, inconsistent process and messy data, AI just produces the same dysfunction at a higher volume and a more convincing tone of voice.
That’s the whole thesis behind this section. AI isn’t a strategy. It’s a multiplier on whatever strategy is already running underneath it — which means the sequencing of how you adopt it matters more than which tool you pick.
Hard Truth
If a vendor’s demo shows AI doing your qualification for you, watch what happens the moment a real buyer asks a question that isn’t in the script.
Read the full cornerstone post: The Amplifier Effect: Why AI Makes Good Sales Teams Better and Bad Ones Worse, Faster.
Where AI Is Actually Changing GTM Right Now
- Research and enrichment — compressing hours of account and contact research into minutes, at genuinely useful accuracy.
- Drafting and summarisation — call notes, first-draft outreach, meeting prep, freed from the “Friday-afternoon chore” category.
- Pattern detection across a large account base — usage signals, health scores and expansion flags at a scale no manual review can match.
- A forecasting signal, not a forecasting answer — useful as one input into a pipeline review, dangerous as a replacement for one.
The Adoption Sequence
Fix the process. Then layer AI on top of it.
The same sequencing mistake that breaks CRM rollouts breaks AI rollouts — buying the tool before defining what it’s supposed to enforce.
1
Define the Process
Stages, exit criteria, qualification — on paper, agreed, before any tool gets configured around it.
2
Clean the Data
AI trained or run on inconsistent CRM data just produces confident, wrong outputs faster than a human would have.
3
Layer AI on the Mechanics
Apply it to the defined, repeatable parts of the process first — not the judgement calls that still need a human.
By Function
Where AI helps, and where it doesn’t, function by function.
Spotting Expansion Signals Before Your Reps Do
Pattern-matching across your account base at a scale manual review can’t touch — and where it stops being useful.
Content Velocity Isn’t a Strategy
Real leverage in production speed and research, and the trap of shipping more generic content, faster.
Catching Renewal Risk Before the Cancellation Email
Health scoring and usage signals that flag risk early — and why flagging risk isn’t the same as fixing it.
Garbage In, Faster Garbage Out
Why predictive scoring and AI forecasting are only ever as good as the process discipline underneath them.