Outreach, the agentic AI platform for revenue teams, has introduced the AI Maturity Model, a framework that helps revenue organizations measure how they use AI across workflows and identify what it takes to operate at a higher level. The model provides a four-stage path from manual execution to AI-Efficient GTM where AI agents work as true teammates.
Outreach launched the AI Maturity Model to help revenue teams benchmark AI adoption and advance toward AI-driven execution.
The model maps revenue maturity across four stages: Traditional, Connected, Consolidated, and AI-Efficient.
Five dimensions are measured: workflow standardization, data trust, inspection and accountability, cross-team alignment, and AI readiness.
Each dimension includes a playbook with step-by-step operational changes to move teams up the curve.
The model is based on Outreach's decade of experience working with thousands of revenue organizations.
Any team can take a quick assessment at outreach.ai; customers receive the full model and playbooks through their customer success team.
Outreach, the agentic AI platform for revenue teams, introduced the AI Maturity Model, a framework that helps revenue organizations measure how they use AI across their workflows and identify what it takes to operate at a higher level.
Most revenue organizations invest heavily in AI without a clear view of where they stand or where they are headed. Entire teams adopt tools and automate isolated tasks, then struggle to connect that work to a coherent operating model. The AI Maturity Model addresses that gap and builds the right foundation for AI agents to act as true teammates. It gives leaders a way to benchmark their current state, understand what separates each stage from the next, and build toward an operating model where AI agents don't just support the team, they work alongside them, designed to carry out the execution that drives pipeline, accelerates deals, and sharpens forecast confidence.
"The maturity model gives teams the language to tell leadership, 'Here is where we are, here is what the next stage requires operationally;' it can turn an AI conversation into a roadmap," said Heather Dahmer, global head of Demand Generation and Sales Activation, SoftwareOne. "Having that shared vocabulary across the business drives real alignment, giving a repeatable way to measure progress and keep moving forward."
The model maps revenue maturity across four stages:
Traditional: Revenue execution relies on individual effort and manual processes. Systems and workflows vary across the team, and technology adoption is early-stage, making AI impact difficult to establish a baseline for.
Connected: CRM adoption, documented processes, and modern tools are in place. Workflows span multiple systems, and AI supports execution, though consolidating data sources would increase its measurable impact.
Consolidated: Workflows connect across the stack, data flows reliably, and buyer signals inform the decisions that matter most. AI surfaces insights for the team to act on.
AI-Efficient: AI drives execution. Agents prospect from live account signals, keep deal data current, flag risk, and draft messages that convert, with people directing the work and reviewing it where it counts.
"Sales organizations are moving beyond AI experimentation and into operational scaling, but many lack a framework for knowing where they stand or what to prioritize next," said Michelle Morgan, research manager for Sales Force Productivity and Performance at IDC. "Outreach's AI Maturity Model gives revenue leaders a structured way to benchmark their current state and a concrete path toward AI-driven execution."
The AI Maturity Model scores an organization across five dimensions: workflow standardization, data trust, inspection and accountability, cross-team alignment, and AI readiness. That score is a benchmark of where a team stands today, showing leaders their strongest and weakest areas. The model then pairs each dimension with its own playbook, a step-by-step guide to the operational changes that move a team up the curve, from standardizing how reps execute to building the clean, connected data that AI agents depend on. The playbooks are the core of the model, a practical path for GTM teams to improve how they operate with humans and AI agents working side by side.
"Most revenue teams are investing in AI without knowing whether it's actually moving the needle, or how they rank against the organizations getting it right," said Cathlyn Lang, SVP of Global Customer Success and Professional Services at Outreach. "The AI Maturity Model removes all that guesswork. It gives an organization a distinct understanding of where they stand and a clear path to the next stage, grounded in what we are seeing across thousands of revenue organizations."
Revenue leaders use the model to anchor planning, prioritize investment, and track progress over time. Any team can take a quick assessment at outreach.ai to see where they stand today; Outreach customers get the full model, complete assessment and stage-by-stage playbooks, through their customer success team who will guide them through a practical plan toward becoming an AI-efficient organization.
About Outreach
Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World leading enterprise organizations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon to name a few
