How modern revenue leaders are using Agentic AI to identify high-propensity accounts, build deep buying-committee intelligence, and close deals faster — in minutes, not weeks.
The GTM stack has expanded dramatically — but pipeline quality, conversion rates, and deal velocity haven't kept pace. Here's why.
Teams are pursuing too many accounts with outdated ICP definitions and low-signal intent data — resulting in wasted outbound effort and missed opportunities.
Most GTM stacks are contact-first. Revenue teams lack the intelligence to map buying committees, identify influencers, or understand how decisions actually get made.
Gathering the level of account intelligence required for effective selling takes significant manual effort — consuming time that should be spent on actual selling.
This session is built around real-world application — not theory. You will leave with specific frameworks you can act on immediately.
How to move beyond static ICP definitions and identify high-propensity accounts using real-world signals including growth triggers, hiring patterns, product launches, and competitive movement.
A framework for mapping executive sponsors, operational buyers, influencers, and potential blockers — built from AI-acquired contact intelligence in minutes, not weeks.
How to execute coordinated, consensus-building strategies across multiple stakeholders simultaneously — increasing deal velocity and reducing the risk of single-threaded stalls.
An executive-level walkthrough of how modern agentic AI platforms apply these capabilities to real workflows — from market filtering through account prioritization to deal execution.
Every segment is designed to deliver a discrete, actionable framework — no filler, no product pitch.
Sales leaders today face three systemic challenges: too many accounts to pursue, too little reliable signal on which accounts matter now, and limited intelligence on how buying decisions actually happen.
Modern AI systems enable revenue teams to filter based on real-world signals — moving beyond who fits your ICP to which companies are most likely to buy, and why, right now.
Most B2B deals require consensus across multiple stakeholders. This segment introduces a framework for understanding buying committee structure, influence dynamics, and decision paths.
An executive-level demonstration of how modern agentic AI platforms operationalize these concepts in real GTM workflows. This is applied practice — not a technical product demo.
Direct discussion with the briefing lead. Questions are welcomed throughout but reserved time ensures all attendees can engage with specific challenges in their GTM context.
Dave Govan is a former six-time Chief Revenue Officer in the technology sector and the Founder and CEO of G2 Strategic Advisory Services. He now advises founders, investors, and revenue leaders on applying AI to go-to-market execution — with a specific focus on account selection, pipeline creation, and deal execution in AI-driven sales environments.
This session represents the real-world application of frameworks Dave uses directly with client organizations. It is a practitioner briefing, not theory, and not a product pitch.
A structured approach to improving account targeting and prioritization based on real-world signals and refined ICP definitions.
A practical methodology for applying AI-driven signal filtering to identify which accounts are most likely to buy — and when.
A methodology for multi-threaded selling and consensus building across buying committees to reduce stalled deals and accelerate close cycles.
A clear view of how agentic AI is reshaping modern B2B sales execution — and specific guidance on where to apply it for the highest ROI.
This session provides a clear, practitioner-led framework you can apply immediately. Sessions are limited in size to maintain focus and ensure a high-value experience for all attendees.