AI Architecture Lab

The Operating Framework for AI Execution

For B2B revenue leaders responsible for turning AI into measurable business performance.

Why did we build this, now?

Because in 2026…

  • GTM leaders know they must be doing more with AI…but they’re stuck.

  • There’s real pressure to act, with no operating model to anchor decisions.

  • Leaders are overwhelmed by tools, vendors, and ideas, and unsure what to prioritize.

  • Most AI efforts stall, fragment, or fail to deliver enterprise-level impact.

2025 was about experimentation. 2026 is about execution.

The AI Architecture Lab provides a practical operating framework for GTM leaders responsible for making AI work at scale. It combines AI fluency with revenue and go-to-market strategy—so AI initiatives are aligned, governed, and driving measurable performance across the organization.

Only 8% of companies are “front-runners” at scaling AI effectively, while just 15% have the essential capabilities to move beyond pilots to real enterprise-wide value.

Accenture Report, May 2025

Enrollment Details

Our first cohort in October SOLD OUT!

Our second cohort launches on Wednesday, April 22nd. Enrollment is now open, and limited to a specific number of organizations. Full details below

$8,500 / company

5 live learning sessions + dedicated implementation hours

Up to 10 participants per company (title / role approval required)

Complete compliment of tools, workbooks and ongoing resources

Special pricing for current Sales Assembly members

Curriculum

The AI Architecture Lab replaces scattered AI experimentation with a disciplined operating framework built for GTM leadership. Sessions are sequenced to help GTM leaders define strategic outcomes, identify where AI creates real leverage, and establish the foundations required to scale responsibly across teams and workflows.

By the end of the cohort, participants will have a clear operating model for AI – one they can act on, defend, and expand as AI becomes a permanent part of revenue execution.

Key Result

Build a shared baseline of AI knowledge and gain early familiarity with the AI S.C.A.L.E Framework.

Session Overview

Delivered On-demand to all participants before the live sessions begin, here we introduce the AI S.C.A.L.E Framework and establish a common language for AI across the cohort. You’ll gain clarity on the five phases of the framework and how they fit together to drive measurable AI adoption.

Main Learning Objectives
  • Understand the structure and purpose of the AI S.C.A.L.E. Framework.
  • Build a baseline knowledge of AI terminology and concepts.
  • Learn common AI capabilities relevant to GTM functions.
  • Arrive at Session 1 ready to focus on strategic application.

Key Result

Define your AI “North Star” and measurable goals that drive buy-in and justify investment

Session Overview

AI initiatives succeed when they are rooted in a clear business purpose. In this opening session, you’ll connect AI directly to the goals that matter most to your organization – whether that’s increasing revenue per rep, reducing churn, accelerating deal cycles etc.

Main Learning Objectives
  • Connect AI initiatives to core business metrics.
  • Conduct the “5 Whys” exercise to uncover root causes.
  • Identify 2–3 high-leverage performance drivers and set a baseline.
  • Gain cross-functional alignment on AI’s role in strategy.

Key Result

Identify where AI will have the biggest impact and assess readiness of your data and systems.

Session Overview

Before you invest in tools or pilots, you need a complete picture of where AI can create the most value. This session guides you through mapping your GTM workflows to reveal bottlenecks, inefficiencies, and costly handoffs between people and systems.

Main Learning Objectives

  • Map GTM workflows to surface bottlenecks.
  • Quantify the impact of solving high-friction areas.
  • Apply a Data Readiness Framework to evaluate infrastructure.
  • Prioritize AI opportunities by impact and feasibility.

Key Result

Build a practical AI roadmap by matching the right capabilities to your highest-priority problems.

Session Overview

With your top opportunities identified, the next step is finding the right AI capabilities to address them. This module introduces the core AI categories for GTM, such as summarization, orchestration, classification, and intelligent search.

Main Learning Objectives
  • Understand core AI capabilities for GTM.
  • Match high-priority use cases to specific AI functions.
  • Evaluate AI tools for fit, scalability, and adoption potential.
  • Build a vendor scorecard to guide selection.

Key Result

Successfully deploy AI initiatives with clear guardrails, measurable outcomes, and momentum for scaling.

Session Overview

The key to a successful AI rollout is starting small and focused. In this module, you’ll learn how to select and scope a pilot that is narrow enough to manage but impactful enough to build momentum.

Main Learning Objectives
  • Select and scope a high-ROI pilot use case.
  • Build a cross-functional execution team.
  • Design a tracking system for adoption and results.
  • Create an internal success narrative to drive expansion.

Key Result

Operationalize AI as an ongoing strategic advantage across teams and systems.

Session Overview

Once you’ve proven value in your pilot, the focus shifts to scaling AI responsibly and embedding it into your operating model. This session covers the creation of governance structures like an AI Center of Excellence.

Main Learning Objectives
  • Develop a scalable measurement model for AI’s impact.
  • Structure governance and oversight for AI initiatives.
  • Design enablement plans to accelerate adoption.
  • Anticipate role evolution and organizational change.

Lab Facilitators

Learn from the foremost thought leaders and innovators within the GTM AI space.

Jonathan Kvarfordt

Head of GTM Growth, Momentum.io

Jonathan “Coach K” Kvarfordt is a go-to-market leader and AI strategist who helps revenue teams turn AI from a buzzword into a daily competitive advantage. As Head of GTM Growth at Momentum.io, an AI deal collaboration platform for revenue teams, and founder of GTM AI Academy, he equips organizations, from Fortune 500s to startups, with practical frameworks, automation strategies, and playbooks that drive measurable results.

Jonathan Moss

EVP of Growth, Experity

Jonathan Moss is a revenue architect and GTM executive recognized for pioneering AI-native go-to-market strategies. As EVP of Growth & Operations at Experity, he leads the creation of AI-powered solutions like Care Agent, the industry’s first clinical intelligence platform for urgent care, while modernizing GTM systems company-wide.

About the Experience

The lab is built to maximize impact while minimizing disruption, so leaders can install an AI operating framework without stepping away from their core responsibilities.

Live, Interactive Sessions

Five live, 90 min sessions over 6 weeks – designed to drive decisions, not just discussion

Defined Methodology

The SCALE Framework is a methodology leaders can use to evaluate, prioritize and govern AI initiatives

Built for GTM Leaders

Purpose-built for CROs, CMOs, Heads of RevOps and Enablement, and GTM executives accountable for revenue performance

Async Support

Office hours, Slack collaboration and even custom GPTs to help drive adoption of what’s learned

Action-Oriented Resources

Practical templates, planning tools, and decision frameworks leaders can deploy immediately

Modern Curriculum

Continuously updated to reflect real-world AI execution, evolving tools, and the realities of scaling AI inside revenue organizations

Collaborative Peer Support

Work alongside your exact leadership peers + leaders @ other companies facing the same execution challenges to share patterns & pressure-test decisions

Custom AI Assistants

Dedicated GPTs aligned to the Lab’s operating framework, designed to help leaders evaluate ideas + apply decisions in real time

Frequently Asked Questions

Everything you need to know about the AI Architecture Lab.

The AI Architecture Lab is specifically designed for VP, C-level or “head of” leaders across Sales, CS, Marketing, RevOps, and/or Enablement.

The Lab is led Jonathan Kvarfordt and Jonathan Moss, the two foremost thought leaders and innovators within the GTM AI space today.  The AI S.C.A.L.E. framework and specific sessions have been designed based off of research, real-world application and years of direct operational experience.

The Lab is constructed around five 90-minute live sessions + one live “implementation hours” workshop, in order to maximize impact while minimizing time off the floor.  In addition there are plenty of async resources and guides to tap into on your own time.

Unlike costly in-house consulting, the Lab delivers a clear AI strategy playbook at a fraction of the price, plus the added benefit of peer collaboration.

Session 1 (4/22); Session 2 (4/29); Optional Implementation Hours Workshop (5/6); Session 3 (5/13); Session 4 (5/20); Session 5 (5/27).

We’re limiting the cohort to 20 companies with companies allowed to enroll up to 10 people each.

Enrollment into the Lab costs $8,500/company.  This includes up to 10 seats.  Sales Assembly members can enroll at a rate of $7,500 / company.

No.  Corporate Sales Assembly membership not required (though members do get preferred pricing).

Of course.  You have up until the cohort begins to “assign” the seats to the specific participants. 

Yes.  Since we have a strict number of seats available, once you purchase a seat, that sale is final.  However, keep in mind you can determine the exact participants up until the program begins.