About the author
Dieter is our Head of Technology and Innovation, he utilises his strategic leadership skills in Learning and HR to enhance the learning experience through streamlining processes. With over twenty years of expertise, Dieter has played a crucial role in harnessing technology to advance learning.
The realm of learning and people development has been profoundly reshaped by the pace at which Artificial Intelligence (AI) has gone mainstream in everyone’s lives, even if its only a talking point for you today there is no getting away from the subject. As the appetite for personalised and adaptable learning experiences grows, AI emerges as a transformative force in our learning journey. In this article, we'll delve into the fundamental elements of forging an AI-driven strategy for learning and development.
AI in Learning and People Development Technology
Machine Learning or Artificial intelligence (AI) has already revolutionised the way we approach learning and people development (seen in things as simple as “your recommended” content) however, with the increasing demand for personalised and adaptive learning experiences, AI has the potential to transform the way we learn even further. In this post, we will explore the key aspects of developing an AI-based tactical strategy in learning and development.
Where to Start
The first step in developing an AI-based strategy is to understand the business goals and learning objectives. This will help to identify areas where AI can be leveraged to improve learning outcomes. For instance, AI can analyse learners' performance data to find knowledge gaps and offer personalised learning suggestions. It can also be used to assess workforce demand needs (you might have heard about skills-based organisations operating models) and explore opportunities for new products and services, however, Hint: as any good data scientist would ask, you need to start with understanding “what the outcome is you are wanting to effect?”
Once the goals and objectives have been identified, it is important to evaluate the organisation's existing learning infrastructure and capabilities. This will help to determine what kind of AI capability needs to be developed to support the overall learning strategy. For instance, the organisation might have to use machine learning for personalised learning content or natural language processing (NLP) for chatbots. You may already have these tools but might not know how to use them effectively. Hint: Most large platform players will now have these in development or already have iterations of these live today, you might be able to move quicker than you think!
To successfully implement a simple AI-based learning strategy, here are two suggested principals led capabilities that we would suggest you need to consider (In the context of your afore mentioned outcomes):
As always, at the heart of all of this is the user journey, and experience is critical to the success of any learning system. AI-based learning systems need to be intuitive (activate recommended content purposefully), easy to use and provide learners with a seamless experience! Again, look to integrations between existing productivity tools and your learning technology stack, available out the box, at the very least, how you can make your front end as good an experience as it can be. Hint: sometimes this could mean not sending the user to the platform directly but integrating your platform elements into places the users already are!
Data, Data, Data and Data Management
Machine Learning (AI) relies on data to make informed decisions (The machine needs to learn). Therefore, it is important to have a robust data management system in place to ensure that the right data is collected, stored, and analysed. So, a great place to start is interrogating the data, what's in good shape, what's clean and complete, and equally important, what's missing? Do you find yourself in possession of surplus data that's not needed, or are there data gaps that you urgently require to drive better decision-making? Hint: Do you have a Data Dictionary? It’s sometimes amazing to me to see how much insight drops out of this simple exercise. Another question to answer would be how can the machine send the learner the right learning if it doesn’t know what the learning contains? Hint: Taxonomies of learning content, meta data or simply naming conventions and titles? Do they all make sense?
When to Start
The right time to start developing an AI (Machine Learning) - based tactical learning strategy is now. With the increasing demand for personalised and adaptive learning experiences, organisations that fail to adopt AI-based learning systems, risk falling behind their competitors in the space of a challenging talent marketplace not because having it will make them fantastic but if they don’t they could make it a poor employee experience.
In conclusion, AI has the potential to transform the way we approach learning and people development, and everyone will be at different stages in understanding its potential. By understanding the business goals and learning objectives, developing the necessary AI capabilities, and focusing on the user experience as a starting point, organisations can create personalised and adaptive learning experiences that drive simple, effortless, user experiences.
Always remember, never let better get in the way of best. Vitro work with clients to assist in the ideation and creation of an AI adoption as well as previously discussed subjects like EVP. We can help to create models ensure you are able to attract the best talent and find ways to retain your brightest stars! #AskVitro #VitroInspire