Back to all Research

The Rise of AI SDRs

This research brief explores how AI SDRs are reshaping inbound qualification and early pipeline creation in B2B go-to-market teams. It explains why AI agents now outperform humans in specific SDR use cases and how companies are deploying them to increase pipeline at a lower cost. The brief provides practical guidance for executives and practitioners evaluating AI SDR pilots today.

Download

Send to Colleague

Summary

This research brief examines the rapid emergence of AI SDRs, with a focus on inbound lead qualification and early pipeline engagement. It combines executive-level perspective with practitioner guidance, outlining where AI agents outperform humans, which GTM metrics they most effectively improve, and how to avoid common implementation pitfalls such as the “demo effect.” The report also covers AI capabilities, training requirements, human-in-the-loop models, and vendor landscape considerations, helping teams move from curiosity to responsible experimentation and deployment.

Best For

CEOs and founders evaluating whether AI SDRs are a competitive necessity
CROs and revenue leaders seeking more pipeline without increasing headcount
Marketing leaders responsible for inbound conversion and website experience
GTM and RevOps leaders integrating AI into existing workflows and systems
Sales and SDR leaders redesigning inbound and outbound capacity models
B2B SaaS companies facing rising costs and slower pipeline velocity

Key Takeaways

AI SDRs already outperform humans in inbound qualification due to speed, availability, and consistency.
The highest early ROI comes from improving one “sticky” GTM metric at a time.
AI’s advantage lies in superhuman skills like infinite availability, deep research, and perfect recall.
Successful AI SDR deployments require strong ICP, persona, and messaging foundations.
Human-in-the-loop models reduce risk during early deployment phases.
Teams that delay experimentation risk falling behind faster-moving competitors.