I've built dozens of AI agents across our GTM operation.

Here’s how I decide which one to build -

Most teams think “adding AI” means dropping ChatGPT into one workflow and moving on.

That is not an agentic system.

Agents are:

→ Always-on
→ Trigger-based
→ Making decisions
→ Taking actions

No human in the loop for 90% of the low-value work.

The real question is not “which tool”.

The real question is “where in your GTM does an agent belong”.

Here is the diagnostic I use across 4 functions.

Sales

→ Time from buying signal to first outreach
→ How reps prep discovery (15 minutes of Google = agent)
→ What happens to overnight replies
→ How you choose which deals to push this week

Marketing

→ How you know which campaigns drive pipeline
→ Where competitive intel comes from
→ Time from idea to campaign live
→ Who decides inbound → sales vs nurture

RevOps

→ How clean your CRM data is
→ How many tools a lead touches before a sequence
→ Which reports still live in spreadsheets
→ What breaks when you 2x volume

Customer Success

→ How you detect churn risk early
→ What signals show expansion readiness
→ How manual onboarding feels for the team

Any answer with “too slow”, “manual”, or “we do not” is an agent slot.

Then match to 5 agent types:

→ Research: signals, company intel, tech stack
→ Enrichment: data waterfall, contacts, email verify, CRM gaps
→ Content: sequences, briefs, reports from data
→ Routing: reply tags, scoring, stage updates, alerts
→ Monitoring: churn, pipeline, anomalies, data drift

Start with one.

Pick the slowest, most repetitive, most time-sensitive workflow.

Team size rule:

→ Under 10: Routing first (reply classification or lead scoring)
→ 10–50: Enrichment first (data quality unlocks all)
→ 50+: Monitoring first (what you cannot see hurts you)

I mapped 20 concrete agent builds across Sales, Marketing, RevOps, and CS into one cheat sheet.