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How AI will change corporate training in the near future

A version of this post was originally published in Entrepreneur on February 1, 2022.

I’ve been in the education business for decades as a senior lecturer, trainer and CEO. When people ask me about the biggest challenge that learners face, the first thing that comes to mind is that learners see training as something they “have to do.”

Now, let’s think for a moment about this. How did we get here? Why aren’t we talking about “want to do” or “happy to have the opportunity to do?”

The answer is multifaceted, but I’ll try to make it simple: training can be demanding. For companies, it takes time to organize courses, curricula and other content; track progress, and demonstrate ROI.

Plus, employees don’t tend to enjoy standardized training that fails to cater to their needs and takes time from their already busy schedules.

These arguably onerous tasks take a fundamental business process and turn it into something many people are reluctant to participate in — a disadvantage for any company. I strongly believe that great learning keeps organizations from stagnation and irrelevance.

AI will change corporate training as we know it

I’m also a firm believer that we can and should do something to make learning more valuable and less of a chore for employees and companies alike. Artificial intelligence (AI) is already shaping and improving many business areas today, and learning activities should be no exception. With the rapid ability to process and analyze vast quantities of data, improve decision-making and personalize learning journeys, AI can expedite and improve learning processes and results — at large and small companies alike.

So here are five key ways in which AI will change learning in the near future.

  1. Optimizing learning recommendations

    Although we all have different needs and aptitudes, the truth is that training is rarely personalized to cover what individuals need. For instance, a rising trend is for companies to offer access to an extensive online course library, trusting that learners will just pick and choose what’s best for them.

    While choice is a good thing, having too many options often isn’t. Instead of assigning training manually or having an open “buffet,” an AI-based system is a happy middle ground for better, more personalized learning recommendations.

    Rather than confront a multitude of decisions, employees can make an easier one: set learning goals related to their careers. Then, imagine how much simpler it would be if each job role came with a series of related competencies, configured by the trainers. Assisted by AI, an intelligent learning platform can look at each learner’s skill map, pinpoint strengths and weaknesses, and instantly send recommendations based on what the learner has yet to master — taking guesswork, and all the time associated with it, out of the equation. Some technologies are starting to enable this today, and these capabilities are something that we will soon see happening on a bigger scale.

    Read more: What’s in store for the future of training: the intelligent learning platform

  2. Fine-tuning learning process 

    Effective learning professionals tend to mix and match training formats and modalities to suit employees' needs. They blend formal and informal learning, synchronous and asynchronous opportunities, and on-the-job training — often tapping into social learning too.

    A good AI system recognizes the complexity of learning and makes fine-tuning like this scalable. Recommendations can be honed and individualized on the fly (based on an employee’s latest training activities or performance) to suggest, for example, talking to an expert in the field, joining learning groups or watching how-to videos.

    And with AI, we’re shifting toward a new paradigm: learning technology as a hub for employee interaction, which is especially important for remote and hybrid teams. This technology will connect remote employees with the right mentors and experts, help them find professionals with the same interests, and subsequently find their place in their learning community. 

  3. Serving up highly-rated resources

    AI-based training recommendations can narrow down learners’ choices, so they see top-rated content first. In this way, AI tackles two serious problems.

    First, it lowers decision fatigue. In my experience in corporate training, people won’t prioritize learning if it comes with extra to-do lists. There’s just not enough time and motivation.

    Second, it enables learning systems to display highly personalized recommendations. As mentioned, even today, what we see business training isn’t individualized at all. There’s the same assigned, one-size-fits-all module for everyone, and quantity often comes before quality.

    Each recommendation — be it a resource or suggestion to contact an expert — could be rated by other learners. This is a plus from a trainer or a manager’s perspective, especially when grappling with a large course catalog since it ensures that learners get the highest-rated recommendations first, with the help of AI.

    Read more: 5 Ways an AI-powered LMS keeps your organization ahead

  4. Empowering employees

    Employees could have more control over what, how and when they learn when AI is infused into learning.

    Imagine having a goal dashboard where learners can see everything related to their chosen learning goal, including competencies, completion over time (and areas remaining) and recommended resources — and even participate in a gamified Q&A forum to clarify questions related to their goals. The individual learning path suddenly becomes clearer as each learner knows where they stand, which is hard to determine in traditional training settings.

    Having all this information readily available at a glance helps employees take ownership of their training. 

  5. Providing augmented training experiences

    We’re closer to simplifying and optimizing learning processes across industries. A key signal of this change is that learning technology is becoming more proactive (with suggested content and learning journeys), instead of simply reacting to what users do.

    Some domains need and benefit from an even more sophisticated training system, and this is where augmented reality can play a role. In the future, employees will be able to immerse themselves, virtually, in realistic scenarios — practicing safely and growing more confident in their skills. For instance, manufacturing companies use augmented reality to teach employees new technical skills with zero work-related accidents.

    Another exciting development is voice control through virtual assistant technology, such as Amazon Alexa. In the year ahead, we’ll likely see employees interact with learning technology on a deeper level, with their platforms able to proactively remind them of learning tasks, among many other actions.

    Read more: How the fourth industrial revolution is impacting L&D

Making AI work for better training

AI will be the biggest contributor to the evolution from standardized, cookie-cutter training to personalized learning. It will enable learners to get the right resources at the right time to advance their knowledge and skills, empower them to be more involved in their own learning, and give companies greater and immediate insights into learning effectiveness and next steps.

Cost and technical barriers continue to drop, putting personalized learning and other AI-based capabilities within reach of many companies. And while learning will remain something employees need to do, it will feel much less like something they have to do — becoming more fun and productive to engage with, and driving greater business growth.