How Might AI Change Employee-centric Learning Design?
I’ve always been puzzled by the question: What is employee-centric learning design? And I can’t help but pose my own question: “What else, besides employees, would we centre our learning design on?”
I’ve done a bit of research regarding the first question and have found three interesting answers – each carefully focused on employees and learning design – as well as a few interesting AI technical possibilities which may soon be ready to help.
1. Employee-centric targeting
When learning experts write of employee centric learning design, they usually put the employee at the centre of our design efforts, and focus on delivery of the right learning material to employees at the right time – when they need it. At the very least, companies for years have been motivated by their own employees to assist them in focusing more on their careers, to make the learning available anywhere, at any time, and to provide them with continuous learning opportunities.
Getting the right learning to employees at an optimal time, I think, is appropriate, it’s definitely focused on the employee at its centre, but is also perhaps a little one-dimensional.
After all, isn’t this what we L&D professionals have always done for our employees, at the very minimum? We tell them what they need to do, and for the most part, they do it.
2. Employee-centric personalisation
A second way we talk about centring learning on employees is to personalise the content and delivery of learning material for employees. “Put employees in charge of their own learning!” Deloitte shouted years back in “Learning – Employees Take Charge”.
For many years, employees have been increasingly thinking about learning-as-a-career-mover, and not just a job requirement. 93% of employees admit they would stay at a company longer if the company specifically invested in their career development. (LinkedIn Workplace Learning Report, 2023)
In this kind of employee centrism, we assess their preferred learning styles, involve them in what they think they need to learn, and offer lots of options – online, instructor-led workshops, experiential role plays, coaching and a variety of other diverse learning resources. This personalisation is moving more toward a curation of employee learning experiences, and tries to leave behind the old world of simply making learning content available.
This is very employee centric: personalisation is supposed to improve employee engagement, satisfaction, and retention of material. According to an e-Learning industry report in 2023, learners love interactivity, with 75% more likely to complete a course if it included interactive elements like quizzes, simulations, or gamification. (eLearning Industry, 2023).
But personalisation is also quite expensive (imagine the cost of packaging the same content delivered in four different ways), much more difficult to manage (individual learning plans become dissertations) and a bit more difficult to agree on metrics and measure. And the tools are not always up to the task.
Jane Hart, who wrote “Modern Workplace Learning 2020 ,” sees LMS-centric learning to be lacking, arguing for a need for a new employee-centric L&D model, in which employees privately own their own learning workspace and digital portfolio: “Whereas an enterprise platform might be relevant to keep track of (mandatory) corporate training, it is just not appropriate to use it to try to manage an individual’s professional learning.
We have plenty of learning technologies that have enabled more personalisation in past years, especially in providing easier to use learning portals, access to external content, and some very good collaboration tools, but generally, the tech has not kept pace with the speed of change, and the increasing demand for what employees need now, now, now!
We’ve never quite caught up, and it feels like we’re slipping further and further from the learning demand curve. Interestingly, some of the work being done now in some of the new AI models will likely help make personalisation easier and cheaper to implement – eventually.
And although our ability to deliver more personalisation has improved in past years, only a few large organisations, MasterCard being one, are able to reach this zenith of employee-centric learning.
3. Employee-centric psychology of engagement
Now, a third way to focus our learning design on employees is more fundamental and, in my opinion, doesn’t get enough headlines: centring our learning designs on the basic elements of employee psychology, and focusing on the employee as a human being, in different emotional states every day, attracted to engagement, meaning and reward.
I like to think about this kind of employee centrism, as it touches on the complex state we are in when we are trying to learn.
Think of all the things that can affect an employee’s readiness and ability to learn at a moment in time:
Motivation to learn – are employees motivated by job survival, career growth, or the assignment/requirement to learn something?
Preferred style of learning – are employees a visual learner or experiential – behaviourism, cognitivism, or constructivism? Are they flowing with the learning, or fighting it?
Social “place” in the workplace – are employees the new person, trying to prove themselves? How is their relationship with colleagues, with their manager?
“Position” in a particular learning cycle – are employees totally new to the topic, or have some prior knowledge?
Cognitive readiness – are employees able to focus for the time needed? Are they suffering from cognitive overload?
Biological “levels” – are employees rested or sleepy, have they eaten well recently?
Physical learning “place” – are employees in a busy workplace, their home office, or in a park having lunch?
Emotional state – how are employees’ stress and anxiety levels? Are they suffering from depression, are they feeling mindful? Are they a confident learner, or has learning something new failed for them previously?
Ability to perform at a specific moment in time – many of us know what performance anxiety is, and yes, it can reach to employees in the workplace and even in private learning experiences.
Of course, it seems impossible for an organisation to know all of this before an employee sits down to absorb some kind of workplace training. And imagine the expense of trying to assess it.
Now, we often think of an employee as a fairly stable human entity – in life, in the workplace, pretty much the same person every week, every day. But we only have to think back on times in our lives when we learned something important, and learned it very well. If we think about what distinguished that learning experience from all of the others in our lives, there are likely to be a complex set of factors.
We were probably in great need of that learning at the time, or we had an amazing teacher, or we just had one of those days when we were ready, willing and able. How much do you remember from your last Harassment and Workplace Bullying course? It’s likely your motivation was just because you had to.
So why focus on an employee’s psychological state to improve engagement and learning? Because we are not a single thing, we are often not stable, human entities – our readiness to learn is dependent on a complex set of factors at any moment in time. And we count ourselves lucky when we get that magic combination of psychology to learn something – something that sticks.
Let’s look at what works for many of us and our unique changing psychologies: what makes a learning environment optimal for most employees?
Of course, that’s a hard question, because we are all different and prefer different places and ways to learn. For many of us, a learning environment that suits our personal psychology benefits from being comfortable, relatively quiet, respectful and safe, where technical things just work, that we have everything we need at hand to learn what we need to learn.
Most of us prefer to be able to actively engage with their learning, to offer opinions, interpretations, and collaborate with peers within the company, and at times externally, in whatever way possible. As humans, we also seem to enjoy some kind of reward commensurate for what we’ve learned, as well as what we already knew (recognition of prior learning), in a style that suits us. No participation prizes, please.
What kind of kind of emotional and intellectual readiness might be desirable for learning?
Maslow’s hierarchy of needs works quite well with our range of employee motivations to learn:
Our basic needs: keeping our job;
Our psychological needs: getting some recognition in the workplace, advancing relationships with our colleagues, and attaining that critical sense of social belonging; and
Our self-fulfilment needs: sustaining our personal growth, occasionally obtaining mastery, and fulfilling our “purpose” in life (whatever that means).
And even though we’re all different, I think it helps our ability to learn if:
We are clear in our motivation to learn this material: whatever the reason is for doing the learning now – career advancement, curiosity, an assignment that helps us keep our job, recognition among our peers, qualification for a new role – it is clear to us;
We are in a suitable emotional and intellectual state to learn right now – we’re not overly stressed or pre-occupied with other things we have to do; and
We are able to identify with the material in some manner, and it seems relevant to our experience – if we’re a bricklayer, we are not likely to be drawn to scenarios of bank tellers.
How can we better focus on employee psychology and engagement?
Perhaps we can pay more attention to engagement strategies in the instructional design we are using;
Using clearer alignments between learning achievements and the growth in an employee’s immediate and future career prospects;
Using some of the elements of advertising to attract and maintain engagement and connection;
Thinking more about how to use team learning and collaboration;
Going to the effort of creating the right learning personas; and
Doing the hard work in creating interesting scenarios, branching structures.
Of course, these are all good things to aspire towards. But we need help to make this easier and more affordable.
Some very exciting things are happening in tech these days, and employee centrism in learning is a centrepiece of what AI models are increasingly improving on: the better these models mimic employee thinking processes, and increasingly, the employee’s psychological state at the time of learning, the closer we can get to truly personalised learning.
4. Employee-centric AI
What might an AI-supported learning engagement might look like?
When we attempt to learn something, especially for our work, we want to do it as quickly as possible – we want the experience to be pleasant, efficient and effective. We want it to work: we need to remember what we’ve learned, we need to be able to apply it to our job tasks, and we need to know how to get more information about it, should we need it.
The engines of current generative AI technology (these are the natural language programs, like Co-Pilot and ChatGPT which answer our questions) are intelligent systems, called “models,” which are able to learn:
1) A great deal about what is happening in the world in general, but can also learn – this is called unsupervised training;
2) Highly targeted information areas, such as secure enterprise data within an organisation (policies, organisational structures, project plans and updates, job descriptions, meeting minutes, performance reviews, etc.); as well as
3) Information about individual employees – their preferences, the way they like information to be delivered, the mood they’re in, the way the like to be talked to.
There is potential for these models to know a person better – at least as far as information about and relevant to them is concerned – than their friends or family, know them.
This gives L&D professionals a realm of new possibilities in finding ways to help employees upskill in the areas that they need and sometimes want, in ways they have never been able to do previously, or their companies to pay for.
According to LinkedIn Learning, this change is already happening: “Advancements in technology, particularly AI and machine learning, have revolutionized employee-centric learning. These technologies enable organizations to personalize content, recommend relevant courses, and track individual progress, creating a dynamic and responsive learning ecosystem.”
An AI-enhanced learning engagement might soon look something like this:
An employee – let’s call her Sarah – a Senior Customer Service Rep at a prominent insurance company, has been given a new Project Lead role in a project which is re-assessing the company’s policies in how it handles small claims from new clients.
Her manager, Melissa, has apologised for dumping this on her so suddenly, but she’s swamped with work and has to spend the day preparing for a Senior Management meeting. Sarah has her first project meeting in two hours.
Sarah has access to an online “Learning Assistant” from whom she can ask for help. She wakes the Assistant up and, deciding to use the voice option, asks for help putting together a quick outline of her role responsibilities, and a quick synopsis of where the project is currently – to the Assistant, this means how far along is the project, who is on the project team, what are their roles, what is the current project timeline, and what are the biggest challenges to the project. To ensure colleagues do not have to overhear her, she would like the Assistant to use on screen text, rather than voice, to respond to her. Sarah mentions that she would like this little training session to be kept just between them. The Assistance confirms.
The Assistant begins by asking how much time she has to get the Assistant’s help – Sarah says 15 minutes. The Assistant can detect from Sarah’s language and tone that she’s a bit panicked and asks Sarah if she’s OK, and tells her to take a few deep breaths, and then asks several qualifying questions to better understand Sarah’s situation: whether Sarah has any previous career leading projects, whether she knows any or all of the project team, or whether she knows anything about the project’s status at all. Sarah answers the questions one at a time. No, not sure, and no.
The Assistant, who has already been trained on the company’s role definition of Project Lead, as well as the current status of this project, starts by outlining the key responsibilities of the role, and highlights the aspects of the role that are most important to the Project meeting in two hours, as well as what Sarah might consider saying to the team at the start of the meeting.
The Assistant asks Sarah if she would like that summary in an email, text, or DM – Sarah picks email. The Assistant sends that, with an attachment of the full project role description.
The Assistant then outlines the current project timeline, the current team members, and current challenges facing the project, and a summary of the last project update written by the previous Project Lead. The Assistant asks if Sarah needs anything else at this time, and again, asks if she would like this outline sent to her via email, or another mode. She also asks if Sarah would like a learning plan for this role, once she has a bit more time.
Sarah feels much better – she can get through this meeting! In 15 minutes, she finds that she has more confidence in running the project meeting coming up in the afternoon, and resolves to start the learning plan later in the week.
Interesting, right? What this scenario outlines is a Learning Assistant using AI functionality, all of which is available in various forms today. It just needs commercial packaging into a coherent whole.
The Assistant offers range of ways to interact with it (voice, text, video), it is sensitive to Sarah’s current emotional state, it curates its personalised advice because of a number of things it has learned – Sarah’s inexperience in the role, and her previous lack of involvement in the project – it has agreed to be confidential, and it offers a variety of ways to get its advice to Sarah (email, text, DM) for later use.
How close is AI tech to this kind of reality? Six months ago, I thought we were years away. Now I think the technology is pretty much all there – closer than many realise – and it’s now just a matter of developers putting the pieces together to design and build deliverable products.
Of course, I’ve touched only lightly on the complex issues surrounding centring learning, at least partly, on employee psychology. But these are exciting times for employee centric learning design.
Watch this space.