Who can use this: Business admin, Any team member
Available on: Enable Essentials
AI Trainer is a Gong AI agent that provides a structured training environment for go-to-market teams to prepare for customer conversations. Reps practice new messaging, pitches, and talk tracks through simulated conversations with customer personas generated from real interactions already captured in Gong. This allows teams to train on their own data without introducing external tools or exposing sensitive information outside the Gong environment.
Sales teams often prepare through self-practice, manager roleplays, or live outreach. While helpful, these methods offer limited opportunities for repeated practice with consistent, objective feedback before engaging real prospects and customers. AI Trainer provides a controlled environment where reps can experiment, refine their approach, and build confidence before speaking with live buyers.
AI Trainer integrates practice and evaluation directly into Gong, using the same scorecards applied to live calls to ensure consistency between training and real customer interactions. It extends traditional preparation methods in the following ways:
Realistic practice scenarios: Reps engage with dynamic customer personas modeled on real conversations from their organization, reflecting the objections, questions, and behaviors they are likely to encounter.
Consistent, structured feedback: Sessions are evaluated using Gong's AI Call Reviewer, delivering objective feedback aligned with live-call standards. Reps can repeat sessions before submitting a final attempt.
Scalable training delivery: Enablement teams can build and deliver structured learning programs with flexible course formats that include micro-learning, practice, and assessments.
How AI Trainer works
AI Trainer follows a defined flow that brings together training modules, scenario design, practice, and evaluation into a single training experience.
Building lessons and practice scenarios
Lessons and practice modules can be combined in different sequences to create structured learning paths tailored to specific roles or skills. Editing permissions are needed in order to add, edit and delete trainings.
Lesson modules
Written and/or visual context for the trainee. Lessons establish the foundation for the scored practice that follows.
Practice modules
Simulates customer conversations.
Each practice scenario created includes:
Contact persona
Defines who the trainee is speaking with, including their title, responsibilities, experience, motivations, priorities, and communication style. The persona behaves dynamically during the conversation based on this profile.
Customer company
Provides detailed company context, including industry, size, business model, current initiatives, operational challenges, goals, and buying considerations that shape the conversation.
Meeting objective
This includes the outcomes the trainee is expected to achieve during the conversation, such as uncovering specific challenges, or securing next steps.
Meeting scenario
Explains why the meeting is happening now. It sets the situational context (for example, renewal discussion, or discovery call) and frames the customer’s mindset.
Relationship background
Describes prior interactions or account history, such as whether this is a new prospect, or a continuation of an existing deal cycle.
About our company
Outlines relevant positioning, value propositions, or solution capabilities the trainee may need to incorporate during the conversation.
Difficulty level
Determines how receptive, neutral, or resistant the customer persona will be. This setting influences the tone, objections, and level of challenge during the simulation.
Background for the trainee
Summarizes key context shown to the trainee before the session begins to allow them to enter the conversation prepared. Includes who they are speaking with, the company situation, and their objective.
Relevant Gong calls and snippets (optional)
These are linked to ground the scenario in real interactions and used to generate a customer persona with realistic behaviors, responses, and challenges.
Practicing, evaluating, and tracking performance
Once trainees begin practicing, AI Trainer combines realistic simulations, structured evaluation, and performance tracking to drive improvement and give managers visibility into progress at scale.
Practice
Trainees participate in timed simulated conversations, supported by any lesson modules, background information, and evaluation criteria configured as part of the session.
Evaluation
After each practice, performance is evaluated using the selected scorecard. This provides an overall score and detailed feedback when a scorecard is configured for the session. Trainees can repeat practice sessions unlimited times to refine their approach before submitting a final attempt.
Tracking
Once submitted, managers and enablement teams can track completion status, review performance, and identify skill trends across individuals and teams. This visibility allows enablement teams to identify skill gaps and assign targeted follow-up training where needed.