Learning professionals have long recognized that scenario-based role-play training can be transformative for developing communication skills. When done well, realistic simulations allow learners to practice handling difficult conversations, navigate complex objections, and build confidence in a safe environment before facing real customers or colleagues.
The challenge has always been execution. Delivering high-quality role-play training traditionally requires skilled facilitators who can improvise believable scenarios, provide consistent feedback, and adapt to different learner needs. Without that expertise, organizations often resort to peer-to-peer practice sessions where employees awkwardly role-play with each other—a approach that feels artificial and produces limited learning outcomes.
Artificial intelligence promised to solve this scalability problem by automating the facilitator role. During a recent conversation with David Lawson, founder and CEO of Call Simulator, I explored how his company has approached this challenge, along with the broader landscape of AI-powered training solutions that are reshaping how organizations develop essential behaviors and human-facing skills that deliver business value.
From 911 Dispatchers to Fortune 500: An Unlikely Training Revolution
Call Simulator’s origin story reveals why their approach works. Starting in 2017, Lawson’s team tackled one of the most demanding communication challenges imaginable: training 911 dispatchers. When your practice scenarios involve life-or-death situations with callers representing diverse demographics and emotional states, your simulation platform better be bulletproof. The platform they built had to handle genuinely unpredictable conversations — no scripts, no staying within predetermined paths, just raw human communication under pressure.
After partnering with Priority Dispatch, a major provider of emergency protocols, Call Simulator has been deployed across hundreds of emergency centers. They’re the only role-playing system approved for continuing education credits by the International Academy of Emergency Dispatch—a credential that’s notoriously difficult to obtain.
But Lawson always intended 911 as their launching pad into corporate training. The platform has since expanded into enterprise markets across various industries and use cases.
The Crowded Field of AI Training Competitors
The conversational AI training market has expanded rapidly, with numerous platforms offering different approaches to automated role-play. Each brings distinct strengths and limitations to the challenge of scaling realistic practice scenarios:
- Zenarate — Combines conversation simulation with software screen simulations, specifically designed for contact center and customer-facing agent training. Their comprehensive approach covers both dialogue and system navigation simultaneously, though the platform requires more setup and technical integration compared to voice-only solutions.
- Virti — Provides immersive learning with AI-powered virtual humans across healthcare, retail, and safety training, supporting VR, AR, and desktop platforms. Their strength lies in visual realism and no-code content creation, though the platform is optimized for guided scenarios rather than completely free-flowing conversations.
- Second Nature — Offers AI role-play training for both sales and customer service with avatar-based interactions and multi-language support. Their established market presence and integration capabilities provide reliability, though their approach centers on avatar interactions rather than voice-only training methods.
- Yoodli — Focuses on communication coaching and presentation skills with real-time feedback on speaking patterns, pace, and delivery. Their analytical approach serves public speaking and pitch development well, but the platform is less suited for complex conversational scenarios or customer interaction training.
- Inworld — Provides AI character creation tools and APIs for building custom role-play scenarios across various business functions. Their flexibility in character development appeals to organizations wanting deep customization, though implementation requires technical expertise and development resources.
- Exec — Combines AI simulations with human coaching support for sales, management, and leadership training across multiple scenarios. Their hybrid approach delivers comprehensive development through both AI practice and expert guidance, though the human coaching element increases costs and limits pure scalability.
Most competitors have focused on specific verticals or made significant technology bets — such as avatar-based interactions or all-in-one platform approaches. Call Simulator represents one particular philosophy in this diverse market, emphasizing conversation flexibility and platform openness.
How Call Simulator Approaches the Flexibility Challenge
Call Simulator’s platform reflects specific design choices that differentiate it within the broader market:
Complete Conversational Freedom — Unlike platforms that guide users through predetermined paths, Call Simulator allows genuine conversation. Want to ask about the weather in Atlanta during a customer service simulation? Go ahead. This mirrors how real customer interactions actually unfold—unpredictably and often tangential to the original topic. The platform uses multiple AI models simultaneously, switching between providers for optimal performance and resilience.
DIY Content Creation Philosophy — Everything in the platform can be customized without professional services fees. Users can edit voices, background sounds, scenarios, and scoring rubrics independently. Lawson’s team aims for zero professional services revenue, viewing any consulting fee as evidence their product isn’t complete. This stems from his early days in business intelligence, where he “hacked his way to solutions” rather than paying vendors to make their software work.
Vendor-Agnostic Architecture — The platform isn’t dependent on any single AI provider, cloud platform, or voice vendor. This technical resilience emerged from their early experience with IBM Watson, where vendor dependency created business risk. If they needed to switch from Google Cloud to Azure tomorrow, they could. If OpenAI changes their pricing or terms, Call Simulator has alternatives ready.
AI-Powered Coaching and Evaluation — The platform includes what Lawson calls “AI coaching” through their rubric creation system, which provides detailed feedback on communication performance. This goes beyond simple scoring to analyze conversation patterns, tone, and adherence to best practices. The coaching system can be customized to reflect each organization’s specific communication standards and methodology, allowing companies to maintain their unique training voice while leveraging automated feedback capabilities.
Who Actually Needs Flexible Role-Play Training
Based on deployment patterns across their customer base, five types of organizations see the strongest results:
- High-Turnover Service Industries – Hotels, retail, and restaurants where employees need rapid skill development before customer-facing roles. The platform accelerates onboarding while improving retention through early success experiences.
- Regulated Industries with Compliance Requirements – Healthcare, financial services, and insurance companies that need documented training for regulatory purposes. The platform’s continuing education credits and detailed reporting satisfy audit requirements while delivering actual skill development.
- Enterprise Organizations with Distributed Teams – Large companies that need consistent training across multiple locations, departments, or time zones. The DIY approach allows local customization while maintaining corporate standards and integration with existing LMS platforms.
- Sales Organizations with Complex Products – B2B companies selling technical solutions where reps must handle sophisticated objections and lengthy sales cycles. The platform’s ability to incorporate company-specific language and product knowledge into simulations proves especially valuable.
- Emergency Services and Critical Infrastructure – Organizations where communication mistakes have serious consequences. Beyond 911 centers, this includes utility companies, transportation authorities, and healthcare systems where staff must perform under pressure.
Strategic Position: One Approach Among Many
Call Simulator has made deliberate choices that position them distinctly within the AI training market. Their decision to focus on voice-only interactions, for instance, runs counter to industry trends toward visual avatars and VR environments. This decision reflects one philosophy among several valid approaches in the market. While avatars may work well for specific use cases like eye contact training or visual presence skills, Lawson argues they introduce unnecessary complexity for core communication development. “The actual ‘what am I going to say?’ We actually believe you shouldn’t have the screen there.”
Other providers have made different choices, with some finding success in avatar-based training for specific contexts and learner preferences. Call Simulator’s voice and chat-based approach eliminates certain technical complexities while focusing learners on conversation content, but it’s one of several viable strategies in the expanding AI training landscape.
The Next Phase: Beyond Traditional Training Boundaries
This expansion challenges the traditional learning and development technology stack. While most L&D platforms focus on content consumption, Call Simulator enables actual skill practice. As AI assistants become more prevalent in customer-facing roles, the need for human communication training may paradoxically increase — people will need even stronger skills to handle the complex situations that automation can’t resolve.
The company’s success will likely depend on their ability to maintain their DIY philosophy while scaling across diverse use cases. Their technical architecture appears ready for this challenge, but the real test will be whether organizations embrace practice-based learning over the content-heavy approaches that have dominated corporate training for decades.
For learning leaders evaluating AI role-play solutions, the market now offers multiple mature approaches with different strengths. Call Simulator’s focus on conversational flexibility and DIY customization appeals to organizations seeking platform openness and rapid deployment capabilities. Their proven track record in high-stakes environments like emergency dispatch provides credibility, while their expansion into broader corporate training demonstrates platform versatility.
The success of any AI training solution ultimately depends on alignment between organizational needs, learner preferences, and platform capabilities. As the market continues maturing, the diversity of approaches — from avatar-based to voice-only, from specialized to comprehensive — gives learning professionals more options to find solutions that genuinely improve communication performance rather than simply digitizing traditional training methods.
