2 min read
Essential AI workflows to boost your GTM strategy
Alice Chen Marketing Specialist
AI in CRM has come a long way since "summarize this record" was the killer use case. The real leverage now is workflows where AI agents do work end-to-end: researching accounts, drafting messages, qualifying leads, surfacing risks, all alongside your team.
Below are five of the highest-leverage AI workflows GTM teams are running in Attio today, each with a prompt you can drop into Ask Attio to set it up.
Before you start
These workflows are only as good as the context they read. Make sure your Attio workspace is connected to the relevant data — CRM records, conversations, product activity, and your stack — before wiring any of them up.
Lead enrichment and routing
The first thing that should happen when a lead comes in is everything. Look up the company. Score the fit. Pick the right rep. Most teams do this manually and get to maybe 20% of inbound; an agent does it 100% of the time, before the rep ever sees the lead.
When a new workspace record is created, look up the lead's company on the web and add a one-paragraph summary to the lead's record. Then post the lead's name, company summary, and the assigned AE to the sales Slack channel.
Pre-deal account briefs
A good rep walking into a qualifying conversation should know who they're talking to, what the account has done with you, and what's changed in their world recently. Building that brief by hand takes 30 minutes; an agent compiles it in 30 seconds.
When a deal moves to the 'Qualification' stage, compile a brief on the account into a new note attached to the deal: a company overview from the web, all activity from our CRM in the past 30 days, and the contacts on the deal.
Signal-triggered outreach
The best outbound moments are the ones tied to something happening in the world: a funding round, a leadership change, something newsworthy. Catching them in time means a rep can reach out while the moment is warm. An agent can watch every target account in your list and queue the right play for the right rep when something moves.
When a target account announces a funding round on the web, create a task for the assigned AE with a one-paragraph summary of the announcement and a drafted opener that references it.
Lost deal pattern analysis
A single lost deal is a story. Twenty lost deals are a pattern. Most teams never read across them. An agent can structure every lost deal as it happens, so the patterns surface on their own when you go looking.
When a deal moves to the 'Lost' stage, summarize the deal into a structured note: lost reason, deal size, days in pipeline, key contacts, and the primary objection from the call notes. Tag the note with the lost reason for filtering later.
Won deal handover
When a deal closes, the AE knows everything about the account, and the AM about to take it over knows nothing. The handover meeting is supposed to fix that, but it usually doesn't. An agent can do the handover work the moment the deal is marked won, so the AM walks in with context the AE would have taken an hour to brief them on.
When a deal moves to the 'Won' stage, create a handover task for the AM. Include the deal value, key contacts and their roles, the primary use case from the call notes, and a one-paragraph summary of the buying journey.
Beyond the five
These five are starting points, not the full list. The shape of AI in GTM is moving from "summarize this record" toward agents that do real work — research, qualify, draft, and act — alongside your team. With Attio, any signal-to-action play your GTM motion needs can become a workflow.