AI-powered training simulations and conversation practice

Last updated October 21, 2026

Training in which AI plays a part: a conversation partner, an adversary, a scenario author, or a tutor that adapts to the trainee.

This guide lists 11 providers of AI-powered training simulations and conversation practice, in alphabetical order: Alelo, CAE, Charles River Analytics, Cubic, Discovery Machine, Lockheed Martin, Moth+Flame, Mursion, SoarTech, Synthesia and Virti. The order is not a ranking. Each provider is described with the same fields, from its own materials and public records, with sources.

1. Questions buyers ask

2. Overview

AI-powered training puts artificial intelligence inside the practice itself. Computer-controlled role players act as teammates, opponents or civilians, tutors adjust lessons to each learner, and avatars hold practice conversations and score them. It differs from courses that teach people how to use AI tools, which federal policy now also calls for.

The services are building AI into training programs. The Army says its Simulation, Training, Test and Threat portfolio, which includes the Synthetic Training Environment, harnesses artificial intelligence, game engines and simulation, and the Navy has funded AI-driven adaptive courseware for its Basic Electricity and Electronics school.

Generative AI is also reaching the whole defense workforce. The Department of the Air Force launched NIPRGPT for generative AI experimentation in 2024, the Defense Department introduced GenAI.mil in December 2025, and in 2026 the Navy told sailors, Marines and civilians to complete at least one AI training course within 30 days.

The problem

Classroom instruction does not adapt to each learner. The Navy reported high failure rates in its Basic Electricity and Electronics school, where many students had to retake training, and sought adaptive training that sailors could also complete offline.

Instructors and human role players limit how much practice each trainee gets. Program descriptions present AI agents that play crew members or role players, assess performance automatically, and show instructors where students struggle so they can manage larger classes.

Generative AI brings new risks to training content. NIST lists confabulation, confidently stated but false output, as a generative AI risk, and OMB requires extra safeguards when AI output is a principal basis for significant decisions, such as federal performance management.

Mandates and programs

• America's AI Action Plan (July 2025). The White House plan recommends requiring agencies to ensure, as far as practicable, that employees whose work could benefit from frontier language models have access to, and appropriate training for, those tools, and that DOD identify the AI skills its workforce needs and run talent development programs.
• OMB Memorandum M-25-21 (April 3, 2025). Directs agencies to build an AI-ready workforce and apply minimum practices to high-impact AI, including pre-deployment testing, ongoing monitoring and human oversight. AI that is a principal basis for federal performance management or promotion decisions is presumed high-impact. It does not cover AI in National Security Systems.
• OMB Memorandum M-25-22 (April 3, 2025). Sets rules for buying AI: contracts must bar vendors from using non-public agency data and outputs to further train commercial AI without consent, and solicitations should reduce vendor lock-in through knowledge transfer, data and model portability and clear licensing. National Security Systems are excluded.
• DoD Data, Analytics, and Artificial Intelligence Adoption Strategy (November 2, 2023). The Defense Department released this strategy to accelerate adoption of advanced AI capabilities so that warfighters keep decision superiority on the battlefield.
• Army Synthetic Training Environment (STE). The Army describes its Capability Program Executive Simulation, Training, Test and Threat as harnessing artificial intelligence, game engines and simulation; its Synthetic Training Environment uses extended and augmented reality for repeatable scenarios, and Next Generation Constructive offers a cloud-based simulation marketplace.

3. Providers compared

Every provider below is described with the same fields and the same length limits, from its own published materials and public records. Where a provider does not publish something, the entry says “Not published.” Providers are in alphabetical order.

4. What to ask a vendor

1. Where do the AI models run: your cloud, a government cloud, our servers, or fully offline? Where models run decides whether training works on disconnected or classified networks and which security approvals apply; OMB's 2025 AI memos do not cover National Security Systems.
2. Will trainee data, recordings or transcripts be used to train your models or anyone else's? OMB M-25-22 requires federal AI contracts to bar vendors from using non-public agency data and outputs to further train commercial AI without agency consent.
3. How do you stop AI characters from inventing facts or drifting from doctrine and policy? NIST names confabulation, confidently stated but false content, as a generative AI risk; ask about scenario guardrails, approved source material and review of AI output.
4. Who reviews AI scores before they affect qualifications, evaluations or promotions? OMB presumes AI that is a principal basis for federal performance management or promotion decisions is high-impact, requiring human oversight and a way for people to get timely human review.
5. What independent evidence shows trainees perform better, and who measured it? Many published results come from vendors; ask for government or third-party evaluations, the measures used and how many trainees took part.
6. Can our instructors write and change scenarios, characters and scoring without your engineers? Doctrine, threats and policies change; content your own staff cannot update goes stale or becomes costly to maintain.
7. Can we export scenarios, scores and transcripts in standard formats if we change vendors? OMB M-25-22 tells agencies to seek knowledge transfer, data and model portability and clear licensing to reduce the risk of vendor lock-in.
8. How well does speech recognition handle accents, jargon and radio procedure? If the system mishears trainees it can score them unfairly; test with your own users and terminology before buying.

5. How buying works

Under the SBIR/STTR Policy Directive, an agency can fund a Phase III award that derives from, extends or completes a firm's earlier SBIR Phase I or II work without running another competition.

The Chief Digital and Artificial Intelligence Office's Tradewinds Solutions Marketplace holds post-competition, readily awardable pitch videos for AI, digital and data solutions; government users with .gov or .mil email can view them and then buy through their contracting office.

GSA's Multiple Award Schedule lets federal, state, local and tribal governments and other eligible buyers get commercial products, services and other solutions.

OMB M-25-22 applies to AI contracts from solicitations issued 180 days or more after April 3, 2025, and encourages performance-based requirements and demonstrations so agencies can assess vendor claims before award.

For SBIR, GSA schedules, OTAs and other routes in general, see How buying works.

6. More questions