AI: Enhancing Learning Today and Tomorrow

Unlike the earlier technological revolutions which took years to spread, the digital revolution continues to enjoy explosive growth. In the enterprise, digitization has produced a transformational change in work, workforce, and workplace. Two of the biggest drivers of this change are Artificial Intelligence (AI) and Machine Learning (ML).

Of the many definitions that exist, one interprets AI as a field which combines computer science and datasets to enable problem-solving. A subset of AI, ML leverages data and algorithms to imitate the way human beings learn, improving accuracy through iteration. Both AI and ML find wide application in the new paradigm of blended workforces and human-machine collaboration, especially in training and development.

Why Learning Management Systems need AI

Traditional classroom instruction is outdated. Today’s learning is digital, accessible any time, at any place and on any device, and delivered in micro capsules exactly when required. For the best learning outcomes, enterprises should deploy high quality trainers, innovative pedagogy, great content, and a top-notch learning experience.

While enterprise Learning Management Systems meet many of these requirements, being designed for scale, they provide standardized content and a defined learning path to all learners, regardless of ability, need, or motivation. By applying AI and ML, organizations can make their learning programs engaging and personalized to the needs of every individual learner, at scale, which is quite infeasible with manual methods.

Here are some common use cases for AI and ML in enterprise learning management systems:

For a highly personalized learning experience: A prompt-based Generative AI tool curates content based on the learner’s skill level, persona, learning style and needs, in real-time. Every learner can choose their own path and method of learning.

For real-time, integrated learning: Instead of running training as a separate activity, AI integrates it within an employee’s work routine, delivering it when needed. Think of a programmer who is stuck while writing some code. AI can sense this and trigger an (AI-assisted) Tutor Bot to help resolve the issue.

For multimodal tutoring: Today, AI-based coaches are mimicking student-teacher interactions, answering questions, and proactively assisting learners. But it’s just the beginning of what AI and ML can do to deliver multimodal tutoring. Going forward, Augmented/Virtual Reality, humanoid robots, holograms of human teachers, and multimodal pedagogy will all be part of immersive learning experiences.

For engaging through gamification: When learners have unlimited access to content on learning management systems, learning outcomes are often lower than expected because of a lack of motivation among learners. AI addresses this by turning learning into an exciting, engaging, and enjoyable experience by using gamification to encourage learners to complete their assignments on time and aspire to higher learning goals.

Improving learning in so many ways

Evolution in AI technologies bodes well for enterprise learning. Today, the most advanced AI-enabled learning platforms boast sophisticated real-time data and analytics capabilities that help to further improve the experience of learners. Built for zero latency, they generate what-if scenarios and instant simulations to put each learner on the best path to learning. Some platforms also offer adaptive assessments that modify the level of testing based on aptitude. In fact, the most evolved AI-first learning platforms are so tuned to a learner’s context that they pick up cues from an ongoing conversation and respond accordingly.

Summing up

Advances in AI have already opened unimaginable opportunities in every field, including learning. By enabling their learning management platforms with AI-first principles, enterprises can impart personalized, adaptive, multimodal learning, through highly engaging experiences. At population scale, to boot.