Accelerating Learning through AI

As the rapid progression in the use of AI continues to scale, the workplace learning, and performance provides another spectacular set of possibilities for the combination of genius and automation to build better learning experiences at a faster pace while optimizing costs.

We see a few immediate opportunities and implications of AI in learning – in terms of use in the development processes and in accessing, managing and distributing knowledge. With the global skills gap increasing, we need to build better learning solutions designed and delivered faster efficiently, without…and AI will help us get there. Our view is that rather than reduce and eliminate jobs in the training market, AI and advanced tools will help unlock the potential of learning as a superpower for organizations as spend is optimized and the human effort can be scaled and better focused on critical strategic activities such as new skilling strategies, expanding content portfolios, on demand / faster delivery and enhancing the learner experience.

Let’s face it, for all of us in the learning space, we are always under resourced, and lacking the right time to deliver what’s needed.

Here are a few areas we see AI positively impacting learning. Note that some of these capabilities and tools are already available, and are expected to evolve further as learning professionals start using them in their workflow.

Requirement and Need Analysis

AI tools plugged in with an organization’s performance management system can analyze a vast amount of performance feedback data, and provide an objective view of employee strengths and development areas. This data can be used to continuously refine a learning function’s priority areas.

Content Creation

AI tools can generate training content with a high degree of accuracy in a fraction of the time. Open source and closed source options can be used to both draw upon the world’s knowledge, but also draw upon an organization’s specific and proprietary knowledge, while protecting its data.

Adaptive Learning

AI algorithms analyze the collected data to create a more robust and tailored learner profile. This profile includes information about the learner’s strengths, weaknesses, learning style, and preferences. Based on the learner’s profile, the adaptive learning system, powered by AI algorithms, can tailor content to be even more relevant, all with less manual effort. It can modify the sequence of topics, provide additional explanations or resources for challenging areas, and adjust the difficulty level of assessments.

Translation and Localization

The challenge for global companies to quickly translate and distribute content adds another layer of complexity, time and cost. While recent advancements in translation software have helped, AI now takes the process to a new level by more seamlessly and accurately translating content – and, going a step further can better tailor content for localized needs (for example In country policy, and cultural considerations).

Learning Data Analysis

AI can quickly and consistently analyze vast data on a learner’s performance, scores, and a number of additional metrics to produce more robust data sets that better inform the learning organization leaders about the effectiveness and ongoing needs of learners. This is most impactful in the skills analysis and mapping areas supporting the move to a more skills-based organization.

Content Management

As organizations have amassed high volumes of courses, effective management, classification and organization have become a big issue. With AI, entire libraries of courses can be better analyzed for gaps in content, duplication, and dating to ensure there is an efficiency in spend.

Training Delivery

This one will evolve significantly over the next few years – today, chat bots and virtual assistants quickly deliver on demand learning and coaching. As we progress and integrate technologies (like digital humans and XR) we will see AI-powered training assistants, capable of interacting with participants to provide more advanced, consistent learning experience.

Administrative Automation

AI tools can be applied in a number of ways in the support and enabling processes. Scheduling, tracking, and resource planning will be the focus to reduce cumbersome operational activities. This allows the training organization to focus more on strategies, content, and the learner experience.

While we have just begun the journey unlocking the next level of learning powered by AI, it is going to be an interesting journey of disruption and innovation.