CoverStory
By Elisa Torres, Mark Baldisserotto and Katia Leonhardt
Rodriguez, M., & Peterson, R. (2024). Artificial intelligence in business-to-business (B2B) sales process: A conceptual framework. Journal of Marketing Analytics.
Friess, M. (2025). Gamification in virtual sales training: Evidence from a field experiment. Journal of Personal Selling & Sales Management.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial intelligence coaches for sales agents: Caveats and solutions. Journal of Marketing.
Life sciences commercial learning organizations face several challenges. Sales professionals must master complex anatomy and surgical approaches, regulatory requirements and diverse product portfolios. Trainers and people leaders have limited time to coach large, globally distributed teams and traditional in-person training formats have a high opportunity cost. Additionally, global organizations must localize training for multiple regions with limited resources.
These pressures increase cognitive load for learners and strain team capacity.
Recent peer-reviewed research in B2B sales and sales coaching suggests that artificial intelligence (AI) can help address these challenges in practical ways. (Rodriguez & Peterson, 2024; Luo et al., 2021)
At Johnson & Johnson, our commercial education team applies AI in practical ways throughout the learning journey. We focus on solving everyday training challenges rather than exploring theoretical possibilities. Our initial goals are to use AI to scale coaching, accelerate skill development and expand training access globally.
Three early applications have been especially impactful: AI-enabled clinical knowledge support, AI-powered role-play practice and AI-assisted translation for global learning. These initiatives show how AI can augment educators, support learners and deliver measurable results for commercial organizations.
These initiatives also required strong cross-functional collaboration. The marketing and commercial excellence teams funded the development of key tools, while the data science team evaluated and operationalized AI platforms to support skill development. This collaboration enabled successful implementation into the learning journey led by the commercial education team.
In a highly regulated environment such as healthcare, organizations must take a thoughtful and proactive approach to adopting emerging technologies. Without clear guidance and approved tools, employees may turn to publicly available large language models that are not designed to meet compliance or data governance requirements. By introducing governed AI solutions within the learning ecosystem, organizations can support innovation while maintaining the standards required in regulated industries.
The result is a practical platform for applying AI in life sciences commercial education.
Commercial training programs must balance competing priorities. Learners need foundational knowledge of products, clinical data and disease states, while classroom time should focus on discussion, application and skill development.
Training sessions run the risk of being overloaded with content, and instructors spend valuable time answering highly specific questions relevant to only a few learners.
AI-enabled knowledge tools help address this issue by supporting more efficient knowledge transfer while ensuring that responses are generated only from approved, active training and marketing assets, helping maintain compliance in a regulated environment.
Research on AI-enabled coaching systems suggests that combining AI-generated feedback with human coaching can improve training outcomes and agent performance by pairing data-driven insights with managerial guidance (Luo et al., 2021).
In Johnson & Johnson’s new hire foundations programs, we introduced AI Advisor internally to support learners during and after training. This tool serves as an on-demand resource for product knowledge, clinical information and program content.
Learners can independently ask AI Advisor detailed and often clinically complex questions without interrupting classroom flow. The system retrieves relevant information and provides clear explanations linked to training materials.
This approach offers several benefits:
Instructors can focus classroom time on key learning objectives. Rather than addressing numerous niche questions, they guide discussions on strategy, positioning and real-world application.
Learners have a resource they can use after training. As sales professionals enter the field, the AI Advisor offers reinforcement and just-in-time learning support.
The tool reduces cognitive overload by providing learners with reliable and compliant knowledge support when needed.
The AI Advisor platform was developed in partnership with Johnson & Johnson’s marketing team, which funded and supported its creation. Marketing leaders recognized that improved product knowledge and faster learning drive stronger commercial performance.
More broadly, the external literature on AI adoption in sales organizations reinforces the importance of cross-functional sponsorship, alignment with business goals and a clear definition of value for successful implementation (Rodriguez & Peterson, 2024).
While knowledge is essential, commercial success depends on skill execution.
Recent sales training research underscores how often practice opportunities are constrained by time, logistics and facilitator availability. Sales professionals must navigate complex clinical conversations, respond to objections and communicate value in regulated environments.
These skills require practice to develop. Unfortunately, practice opportunities are often limited. Traditional role-play exercises require instructors, scheduled workshops and significant time commitments, which limits the number of structured practice sessions that can be offered (Friess, 2025).
To address this, Johnson & Johnson implemented an AI-enabled role-play platform.
The application enables sales professionals to role play with an AI-powered avatar and receive automated scoring and feedback based on predefined competencies. Learners can repeat exercises and compare results with peers.
This application is now used across multiple stages of our commercial training ecosystem.
The platform supports recertification for the sales organization, reinforces learning during foundations training for new hires and offers ongoing practice in advanced and masters curriculum programs.
To test whether AI-driven role play could scale coaching across the organization, the team deployed the platform during a large-scale recertification effort.
The impact has been substantial.
Across the organization, more than 800 account executives were recertified in 21 days. More than 4,800 role-play submissions were evaluated using a seven-competency Challenger framework.
Learners showed measurable improvement. Overall scores increased by 80.7%, with the most challenging competencies showing the greatest gains. Average performance improved by 25% across four complex selling capabilities.
Learner engagement was also notable.
Although only one submission was required, participants averaged 3.06 attempts per scenario. In total, 88% of learners voluntarily repeated role-play exercises to improve their scores.
This engagement reflects the influence of gamification elements in the platform. Leaderboards, scoring feedback and opportunities to refine performance encouraged continued practice.
Operationally, the program generated significant efficiency gains. By reducing reliance on in-person role-play workshops, the initiative saved approximately $670,000 annually in travel, scheduling and facilitator costs.
These outcomes show that AI-enabled coaching tools can expand practice opportunities while maintaining quality and consistency.
The platform was implemented through collaboration with Johnson & Johnson’s data science team. Their expertise was essential in evaluating the technology and ensuring the platform met internal requirements.
This cross-functional partnership ensured the tool delivered both educational value and operational reliability.
Large global organizations face another challenge: Training programs developed in one region must be localized for multiple markets.
Localization requires translation, cultural adaptation and coordination with regional stakeholders, which can delay the rollout of critical training initiatives.
Artificial intelligence is helping address this challenge.
Johnson & Johnson is utilizing AI-enabled translation tools to accelerate localization of commercial training programs. These tools help learning teams quickly translate course materials, scripts and supporting content while maintaining consistency with original objectives.
AI translation does not eliminate the need for regional review. Subject matter experts still validate content for regulatory accuracy and cultural appropriateness.
However, AI significantly reduces the initial workload for preparing translated materials. Regional teams receive high-quality draft translations that can be reviewed and refined quickly.
This approach enables global teams outside the United States to access training programs more quickly while maintaining alignment with global messaging and product positioning.
For companies operating across many therapeutic areas and international markets, faster localization leads directly to faster capability building in the field.
Across these examples, one theme is clear.
Research on AI coaching in sales suggests that artificial intelligence is most effective when it augments educators rather than replaces them. Trainers remain essential for guiding discussion, providing strategic coaching, and helping learners apply knowledge in real-world scenarios. AI simply extends their reach (Luo et al., 2021).
AI knowledge tools answer detailed questions, allowing instructors to focus on higher-level discussions. AI role-play platforms offer scalable practice opportunities that would otherwise require extensive facilitation resources.
AI translation accelerates global training access, while regional experts ensure accuracy and contextual relevance. When implemented thoughtfully, these technologies amplify the impact of learning organizations.
Our early experience applying AI in commercial education has produced several lessons that may benefit other life sciences organizations.
Start with tangible problems. AI initiatives can meaningfully address specific operational challenges, such as limited coaching capacity or insufficient practice opportunities.
Focus on measurable outcomes. Demonstrating improvements in skill performance, learner engagement or operational efficiency builds credibility and support, ultimately yielding value for the business and for customers.
Engage cross-functional partners. Collaboration with marketing, data science and commercial leadership is often essential for successful implementation.
Position AI as a support system for educators. When framed as a tool that enhances training rather than replacing it, adoption tends to be stronger.
Learning leaders should recognize that practical AI applications are already available. Current research in AI-enabled sales processes and virtual sales training indicates that AI can expand coaching capacity, accelerate skill development and improve access to high-quality training when implemented thoughtfully (Rodriguez & Peterson, 2024; Friess, 2025).
As Johnson & Johnson continues exploring new AI applications in commercial education, one principle remains central: Technology should always serve the learner.
When AI supports educators and empowers learners, it enables stronger commercial capabilities and more effective global training organizations.
Elisa Torres is director, commercial education strategy & curriculum design, at Johnson & Johnson. Email Elisa at etorre23@its.jnj.com or connect through linkedin.com/in/elisa-torres7.
Mark Baldisserotto is director, commercial innovation and data science, for Johnson & Johnson. Connect through linkedin.com/in/mark-baldisserotto-bb38a119/.
Katia Leonhardt is senior manager of digital innovation & enablement for Johnson & Johnson. Connect through linkedin.com/in/katia-leonhardt-547879b4/.
