How can AI solve problems for “learners”?

2023 was a groundbreaking year for AI in many respects. ChatGPT took the world by storm, Microsoft and Google launched their own chatbots, we saw AI assist with life-altering innovations within the medical field , and there was even an AI-assisted breakthrough in understanding the language of whales .?

Sometimes it truly feels like we’re living in the future - but in our recent The future of AI for learning and development whitepaper , we thought it was also important to consider the as-yet untapped opportunities AI can bring to the world of workplace learning.

The best place to start? Thrive customers, of course.

As a part of our new AI whitepaper , we surveyed a number of Thrive customers around the possibilities AI will bring.

The findings were interesting. One Global Training Manager commented that AI will not only be able to generate ideas, but will be integral to “supporting assessment of performance, developing skills through practice in a safe environment,” and creating “personalised and adaptive learning recommendations.”

What is evident from this - and the other comments shared with us - is that learners want more relevancy, better predictions, and a clearer understanding of what skills they should be developing.?

Taking this a step further, framing the problem that needs to be solved would always be our first step in developing any AI solution as a technology vendor. As a result, the top three problems we have noticed surfacing time and again are highlighted below.?

It’s worth bearing in mind that although these are prevalent issues now, with AI’s help it’s likely we’ll get to a place where we’re actually solving these quite quickly. Rather than overwhelming, insurmountable problems, they’ll simply be a part of the expected experience.?

These are real-world problems AI technology can help to solve, and they also resonate with the broader sentiment across the industry.

So, with all that being said, let’s dig into the top three problem statements we’ve identified amongst learners:

“Learning isn’t relevant enough to me and my role”

This problem shouldn’t come as a surprise to any learning team.

Effective experiences rely on end users immediately identifying what’s in it for them, but also understanding the real-world application to their specific role. It may seem like a distant pipe dream to one day reach a place of true personalisation based on who you are, how you interact, what your role is, and any other specific characteristics - but this is just one of the ways in which AI can truly help end users.?

In this regard, if AI can help surface the right information at the right time and facilitate a broader learner journey, you’ll automatically increase the amount of trust people place in your AI technologies. They can relax in the knowledge that they’re being served exactly what’s right for them, at the right time. The exact definition of “right” can include anything from who you are, to where you are, to how you prefer to access information. With all this factored in, accessibility is enhanced along with trust.

Therefore, AI has the ability to target content in ways that would have previously been admin-heavy.

“The tools I’m using to learn don’t predict what I need to do next”

The next step, after relevancy, is technology being capable of predicting what you need to do, see or know.?

During the “Putting the ‘I’ back in ‘AI” series of webinars we ran last year, we asked “Do you think there will be a generational divide when it comes to expectations for how AI is utilised by businesses?” and 83% of respondents said yes. It’s highly likely that people entering the workforce will have a different expectation when it comes to the way technology will enable them.?

If we look at sat navs, music streaming, and food delivery apps, one thing they all have in common is prediction. Sat navs can predict where you want to go based on the time of day you’re getting in your car, and where you usually drive to at those times. Music streaming services can predict what music you might want to listen to next. Food delivery apps know that you like certain food at certain times, so they send you clever alerts around those times.?

So the important question is: Do the technologies you use for learning also do this?

If the expectation is that they will, but they don’t, you’re creating a point of friction for your employees. Compared to the way people experience their world outside of work, your less predictive workplace learning experiences will feel lacklustre (which, I’m sure you’ll agree, is not what we’re aiming for.)?

Arguably, this problem statement could fall under both an end user problem, and an L&D team problem. If technology could predict the learner journey people need to go on, admin time would be drastically reduced, whilst engagement and learner experience would likely increase.?

“How do I know what skills I should be developing?”

According to the UK government’s latest statistics , 9.25 million people aged 16-64 are currently out of the workforce. As a result, talent pools are reducing and upskilling is becoming even more important. Organisations are turning to technology to help reduce manual tasks. Looking beyond this, technology can also be used to help individuals plan and identify their own upskilling opportunities.

If you’re an individual within a role who is focussed on progression and career development,? you’ll want to know the answer to the question “what skills should I be developing?” without having to work too hard to find these answers. Even if someone is not as focussed on career progression, it’s arguably still useful for them to have access to relevant skills development should they ever seek it out.

As L&D teams, we should be able to feed into conversations around talent mobility and make an impression on retention rates - particularly if these are metrics against which we can measure, and which are important to the business.

In this regard, AI can be the strategic partner you’ve always needed.

As an end user, understanding where you can get to within a business - and more importantly, how you get there - should be paramount to your experience.?

To wrap it up

At the time of writing, there’s an infinite number of possibilities as to where AI can take L&D - but only if we’re solving the right problems. It’s hugely encouraging to see the harmony between providers and L&D as we look towards the not-so-distant future.

The three core areas being personalisation, prediction and skills development means that there are tangible “problems” to identify and solve. In the meantime, while vendors develop solutions, we would encourage you to continue experimentation with your own tools in line with your organisational parameters.?

We can’t wait to see a more effortless future.

What do you think?

As always, we’re keen to hear your thoughts.?

• Do these problem statements resonate with you and your L&D team??
• Have you started to deliver more personalised experiences through AI??
• What does the future look like for you?
• What opportunities are there for AI to solve some of your learner’s problems?

Let us know in the comments or drop me a message on Linkedin .