How to Enrich Leads With AI
Turn a name and an email into a full deal profile in seconds. A practical guide to AI lead enrichment for SDRs, AEs and RevOps in 2026.
What AI lead enrichment actually does
AI enrichment takes sparse input — usually a name, an email, and maybe a company — and returns a structured brief: company overview, headcount band, tech stack, likely decision makers, buying signals, risk flags, and a suggested next step.
Unlike static database enrichment (Apollo, ZoomInfo), an LLM can reason over recent news, LinkedIn posts, and job listings, then merge that into a single narrative your SDR can act on.
The 5-field minimum input
The more you give, the better the output — but these five are enough to run:
- Full name
- Work email (best) or personal email
- Company name or domain
- Job title (optional but very useful)
- Deal context — one sentence on why you are reaching out
A typical enrichment run, end-to-end
Paste the lead into KommoAi's enrichment box on the homepage. The pipeline: (1) parse and normalise, (2) resolve the company domain, (3) run a base research pass, (4) run optional deep-dive facets — contacts, decision makers, relationship graph, social — (5) score, (6) synthesise a next task.
The whole run takes 6–15 seconds. Every field carries a confidence badge so you know which numbers to trust and which to double-check.
Where enrichment usually fails
Bad email inputs (personal domain, no company), silent 429s from the model, hallucinated headcounts, and — most commonly — copying the raw output back into the CRM as a wall of text. Fix the last one with a Kommo-formatted note template so reps get structured, scannable intel.
FAQ
How is this different from Clearbit / Apollo?
Static enrichment gives you fields. AI enrichment gives you a story — a narrative with a recommended next action, refreshed on demand.
Can I regenerate just one section?
Yes. KommoAi lets you regenerate contacts, decision makers, the relationship graph or the social panel independently.