As businesses move faster, traditional training methods are struggling to prepare employees for real-world challenges. AI-powered simulations are changing this by giving teams practical environments to build skills, improve judgment, and become workplace-ready.
In today’s Analytics Insight Podcast, host Priya Dyalani spoke with Kumar Veetrag, Co-founder and CTO of Enaradigm, about how AI and simulation-based technologies are transforming enterprise learning and talent development.
The conversation explored the shift from traditional training to experiential learning, the use of AI in assessments and coaching, and how talent analytics can support better hiring and workforce decisions. They also discussed the importance of responsible AI, human judgment, and governance as organizations adopt these technologies. Here are the key excerpts from the interview:
Experiential learning focuses on practicing skills in realistic situations instead of relying only on theoretical knowledge. The podcast explains that employees often need to practice judgment, communication, and decision-making before applying them at work. AI-powered simulations can create these practice environments and help employees become ready faster.
AI is making simulation-based learning faster, more flexible, and easier to personalize. Organizations can create scenarios and AI avatars for employees to practice real workplace situations. Simulations can be adapted for different languages, accents, vocabulary levels, and roles. This allows enterprises to provide more relevant learning experiences at greater scale.
AI-based assessments can address several limitations of traditional evaluation methods, including time, cost, and scalability. Thousands of employees can participate simultaneously, while organizations can receive faster feedback and consistent scoring. Assessment data can also support coaching and development, helping employees identify specific areas where they need improvement.
Organizations should combine AI with human judgment and non-AI systems rather than allowing AI to make decisions independently. Clear guardrails, careful AI configuration, multiple AI systems, peer evaluation, and human calibration can improve reliability. Organizations should also protect sensitive information and follow responsible AI practices throughout the process.
The podcast suggests that competitive advantage is shifting from simply hiring the best talent to continuously increasing the capabilities of existing employees. As business needs change faster, organizations need adaptable people who can learn, practice, and change direction quickly. AI can support this through personalized simulations, coaching, and continuous skill development.