As we move into a world where content can increasingly be spun out at the click of a button with the adoption of Artificial Intelligence (AI) the question around how and what we produce to support workplace learning requires evaluation.

With the power to revolutionise traditional training methods, many support the idea that AI will pave the way for more efficient, personalised, and effective learning experiences for employees.

AI tools leave L&D nowhere to hide. And that’s a good thing.

 

While the benefits of AI in workplace learning are compelling, there are challenges to navigate. Privacy concerns regarding the collection and use of employee data must be addressed transparently. Additionally, the human touch in learning: empathy, critical thinking, and emotional intelligence, must not be overshadowed by technology. A further concern is the sheer volume of ‘learning’ content that may be produced. As interactive content becomes cheaper and easier to produce, organisations may be tempted to flood their learning platforms with vast amounts of content that do little to help achieve the business outcomes that L&D is there to support.

In a recent episode of the Learning While Working podcast ‘Rethinking workplace learning in an AI-Driven World’ Lars Hyland and Matt Linaker tackle how to shift from content-driven strategies to more context-based and collaborative learning environments. This episode questions a content-first approach to L&D.

Watch the full episode here:

 

 

As an industry overall we’ve been forced, but also readily accepted and defaulted to a very strongly content-led model which is about getting more content to more people more quickly, and then recording the fact that they’ve reviewed it and completed it, and assume that means something positive has changed.

However, simply providing people with more and more content is highly unlikely to ensure the delivery of focused business outcomes for your people. What really matters, and what has always mattered, is whether that learning experience truly supports the outcomes that you’re attempting to achieve.

In a recent Community webinar ‘Beyond content delivery: Empowering L&D for impactful outcomes’ we talked about how to move towards a performance consulting conversation and break out of the endless content creation loop.

 

MET OFFICE CASE STUDY  – How the Met Office Doubled Site Logins with ‘Infinitely Configurable LMS’

One organisation that is currently moving away from simply developing more and more content is the Met Office (UK weather forecaster). Using Totara Learn to facilitate its learning and development needs, the Met Office also use Totara Engage as a platform to enable in-the-flow of work learning for their communities of practice and Totara Perform to capture competency data to drive personal development and evidence-based decision making for L&D strategies.

Rather than simply focusing on content, our L&D teams need to sharpen their focus on outcomes. It’s a fact that producing more content more quickly using AI tools may be counterproductive.

 

Information indigestion

If there is no connection to outcomes, leadership will always ask that question, ‘okay well, why were we doing this in the first place?’ Maybe we’ll ask better questions of ourselves and there will be a better connection between the real outcomes we want to see.

If we’re going to improve performance at scale across an organisation then we need to achieve tight integration between learning, performance and engagement. We need to think about a balanced talent experience. Simply overloading your learning platforms with more and more content will end up leaving your people with a serious case of information indigestion. An approach that will likely leave them feeling sluggish, confused and unable to perform to the best of their abilities.

 

Lars Hyland 

CLO at Totara