The launch of ChatGPT on November 30, 2022 felt like a tipping point for the role AI (artificial intelligence) will play in the world of education and L&D. This year, learning professionals are likely to experience a drastic change in the way we work due to the explosive speed of technological advancements. This article describes three AI-powered trends that I anticipate emerging or intensifying in the near future.

1. Meta-learning

Meta-learning, in the context of this article, refers to AI tools that serve up experiences to learners based on their preferences, needs, and goals. It is the superstructure behind the content assets (e.g., programs, courses, articles, videos, etc.) that assembles everything in a coherent, and purposeful, body of knowledge to be accessed by the user.

These tools aren’t new but will become as ubiquitous as LMSs due to an accelerated rate of adoption. The most popular solutions in this arena are LXPs (learning experience platforms). A common reason that an organization acquires an LXP is to find a way to develop talent internally; this is often seen as a way to fill the gaps generated by the new jobs for which the market has, and will continue to have, insufficient supply.

Adopting an LXP also allows companies to leverage existing employees, who know the organization well, by upskilling or reskilling them and moving them from a job that won’t be required anymore to a new role that is in high demand. The savings and return on investment form this approach can be as high as 312%, according to a study by Forrester Consulting (and sponsored by Degreed).

The capabilities of these LXPs are wide and extraordinary; some common features include:

  • Tracking the skill level of the workforce
  • Providing pathways to move employees from their current role to the next one
  • Targeting skills that the organization needs and encouraging employees to learn them
  • Offering potential new hires opportunities to take part in mentorships, job shadowing, stretch assignments, and internal talent markets.

Depending on their philosophy and the tech environment where they originated, an LXP can include additional functionalities such as private content libraries, the ability to author and publish learning content, ability to replace LMS functions, or ability to function as a module within an existing messaging tool.

Some popular LXP names that you will be likely to hear include Degreed, 360Learning, Docebo, Viva Learning, Cornerstone, Udemy, and Learning Pool.

2. AI-assisted design and development work

This is the trend most likely to have a dramatic evolution this year.

Until recently, the use of AI in instructional design work was commonly restricted to searching text and images, using voice transcription tools, or leveraging machine learning capabilities embedded in authoring and design tools. All of this is about to change. A lot.

Solutions like large language models, speech generators, content generators, image generators, translation tools, transcription tools, and video generators, among many others, will transform the way IDs create the learning experiences our organizations use. Two examples are:

1. IDs will be doing more curation and less creation:

  • Many IDs will start pulling raw material from content generators (built using natural language processing platforms like Open AI’s GPT-3, Microsoft’s LUIS, IBM’s Watson, Google’s BERT, etc.) to obtain ideas and drafts that they can then clean up and add to the assets they are assembling. As technology advances, the output from these platforms will be more suitable to become final drafts, and the curation and clean-up tasks will be faster and easier.
  • Then, the designer can leverage a solution like DALL-E 2 (or a product developed based on it) to obtain visuals that can (or not) be modified with programs like Illustrator or Photoshop (see image below for Dall-E's “Cubist interpretation of AI and brain science.”)

Images created by Juan Naranjo using DALL-E2 

  • If the asset requires a video, IDs will be able to quickly create one by leveraging existing footage, without having to go through each video in a library (using a program like Pictory) or from scratch by feeding text to a video generator (as it is the case with Lumen5).

Once these types of tools become fully capable of connecting to the organization’s internal information repositories and libraries, the development of learning materials will take a fraction of the time it does today.

2. IDs will spend less, and in some cases no time at all, creating learning pathways:

  • Currently, L&D may be tasked with creating a curriculum for a specific audience, with the goal of upskilling those learners in a specific skill or skill set. It’s unlikely that L&D will do this manually anymore.
  • AI engines contained in LXPs and other platforms will select the right courses for employees and guide these learners from their current level of knowledge and skill to their goal state with substantially less human intervention.

3. Ultra-personalized learning

One way to understand personalization is in the context of meta-learning: An AI system understands the learners and the organization’s development goals; it serves content to each learner accordingly. In other words, the AI engine helps people find relevant experiences that will evolve their skills and careers.

But there is a second dimension to personalization that may start to become more popular this year. This level of personalization will involve an understanding of each learner’s biology—knowing when they are at their optimal moment for learning, for creative work, for focused activities.

This approach will involve wearables, like smart watches, that will tell the wearer where they are at in their circadian and ultradian rhythms and advise them on the best time to complete a bout of learning.

This represents personalization at an entire new level. It could optimize the learning process by improving each learner’s odds of retaining the material and consuming it faster. Today, there are already fitness wearables that can tell the user how hard to exercise and what type of workout is the best fit for any given day considering how the person slept, their heart rate, and other biometrics; 2023 may be the year when we start seeing similar applications for learning.

In summary

These AI-powered trends will have an all-encompassing effect on our industry. They will revolutionize the way organizations manage their talent’s development, through meta-learning; the way L&D creates its outputs, through AI-assisted D&D work; and the way learners consume content through leveraging data and brain sciences.

We have exciting and challenging times ahead, full of fast, dramatic change.

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