Digital learning assistant is an AI and Chat-bot based solution that
The key components of the Digital Learning Assistant is as illustrated below.
Inquiry-Based Learning: The best time to deliver training is when learner needs it in the flow of work. Natural language understanding and semantic search capabilities allow learners to get answers from multiple sources and types of contents distributed all across the organization.
Conversational Learning: Most field reps are looking for bite-sized content than sit through hours of training. AI-enabled automated chunking, sequencing and tagging of content can result in a highly engaging conversational learning experience.
Application Learning: Training provides 10% of learning support. 70% of learning happens on the job. Learning application is key to job performance. Chatbots can help learners apply learning via on the job application templates, step by step action recommendation and data-driven insights.
Practice based learning: Behavior changes can be attained only by the conscious practice of learning via role plays, reinforcement quizzes and activity logs. Chatbots can easily weave in this experience by prompting practice sessions at a regular interval or when informed by context and data.
Data-Driven Insights: Predictive analytics capabilities can help accelerate job productivity by providing data-driven insights on deals, accounts and quota success trends, action recommendation and relevant peer connection.
Peer Mentoring: A chat platform is perfect for connecting relevant peers, experts and coaches to have contextual discussions. The conversations can be mined for creating knowledge bases.
Coaching: Chatbots can have embedded coaching models that can trigger a set of conversations with learners that will help them identify issues and solutions by themselves. Like a real coach, it can follow up on action items and keep learners accountable to activities and results.