The Future of Learning: Revolutionizing Personalized Learning Through AI
A report on the state of future jobs, published by the World Economic Forum (WEF), points to the fact that some of the hottest jobs today, in many industries and in many countries, weren't even in existence five or 10 years ago! What does that tell us about the future workplace? Well, it says there is likely to be transformational change to how people work, which will necessitate dynamic shifts to the future learning paradigm.
The rapid pace at which the demand for new skills is evolving is already obvious. In its Q2 2018 Skills Index, freelancing market-place creator Upwork noted that 70 percent of the skills in the latest index are new. And that underscores the training dilemma employers (and freelancers) face: How do you ensure that the workforce of tomorrow is equipped with the skills and knowledge they need to be more productive and work effectively?
The answer is enlisting the help of artificial intelligence- or AI-equipped learning solutions.
Harnessing AI for Impactful Future Learning
A decade or two ago, CD-based computer-based-training (CBT) was all the rage. But as learning needs changed, new learning paradigms evolved. Today, online learning, learning on-the-go, just-in-time learning, and microlearning are concepts both employers and employees are eagerly embracing. But as business environments change, the roles employees play are transforming, too:
- The role of the “specialist” will disappear, with “generalists” stepping in to fill that gap.
- The concept of a “full-time” employee will disappear, with contractors and temps taking over.
- There no longer will be an “office” as we traditionally know it, with the gig economy forcing workgroups, workplaces, and workspaces to constantly change and go where the work is.
Advances in AI and robotics will redefine the role human workers play in the workforce. That, in itself, will have a profound impact on the future of learning. Human workers will need to change how they acquire new skills and learn new trades to stay relevant and productive. Otherwise, employees quickly will become irrelevant to the organization.
Paradoxically, as advances in data analytics and AI change what tomorrow’s workplace will look like, they are precisely the disciplines that will help workers equip themselves to become more productive in that future workplace. How might that happen? By transforming how employees of the future learn:
1. Personalized Learning
Data aggregators, such as Google, Amazon, Facebook, and other social platforms, have assembled a lot of data about us. As a result, they engage in “targeted selling” and “upselling.” And that’s exactly what AI can do for future workers. Powerful learning engines, driven by data analytics engines, will be able to personalize what employees learn.
How will they do that? One way is by studying learning patterns and preferences, and then steering workers toward a learning path that takes those preferences into consideration. So if a worker excels at certain levels of learning, there’s no point in forcing him or her to follow a linear path to completing a learning program. The AI bot will sense that and recommended more advanced courses or subjects for such learners.
Not only will this result in customizing the learning experience, it will make employees productive much quicker.
2. Intelligent Content Creation
The future of learning also will be influenced by having AI and AI-enabled learning solutions go higher up in the learning food chain—into the domain where learning content is created. These tools can interpret the vast amount of seemingly disparate resources, such as videos, audio files, and images, and intelligently weave them into seamless learning content. And they can do it quicker—much faster than any human instructor can.
Content that otherwise would seem inconsequential—or irrelevant—for a particular curriculum will become a valuable component in lesson plans for learners. And as AI-driven learning tools “learn” how instructors and instructional designers work (their preferences, their style, their teaching approaches), the tools will “serve up” alternate content for teaching professionals to consider.
The outcome of this human-AI content collaboration will be that many more effective learning paths will be designed quicker than they are today. Course designers then will have more time to focus on providing the “human touch” to learners—one-on-one counseling and learner engagement.
3. Digital Learning Assistants
Because of the way the future workforce will change, compared to today’s standards, one can’t but envision the future of learning as one where employees are on a continuous learning journey. And what better way to go on a journey than to have a loyal, trusted assistant always by your side? That’s precisely the role AI-empowered digital learning assistants will play.
While AI-powered chatbots, integrated with tools such as Valamis’ Learning Experience Platform, already are empowering employees to learn in new and imaginative ways, those use cases can be expected to proliferate in the new learning paradigm. And the role of the digital assistant won’t just be restricted to serving up learning on demand.
As future employees in the workforce interact more closely with their digital learning assistants, these assistants will use predictive technologies to recommend learning paths today that an employee is likely to benefit from tomorrow (in a project or assignment that’s in the pipeline).
Measuring the Impact of Learning
What employees learn, when they learn, and how that learning takes place has a huge business impact. The role of AI on the future of learning cannot be viewed in isolation from the core objectives of a business—which is productivity and profitability. Where companies are productive, their profitability will follow. And a business’ productivity hinges on how well equipped its employees are to do their jobs.
The future business landscape will be driven by knowledge. Anything employers can do to arm knowledge workers with the tools they need to learn their jobs faster and perform them better will translate directly into productivity and profitability gains. By recognizing skills gaps and identifying personalized learning needs, AI-enabled tools help to influence the impact of organizational learning.
Marina Arshavskiy holds a Master’s degree in instructional design and eLearning. She is committed to helping organizations become more effective by creating groundbreaking, result-oriented learning solutions. Arshavskiy has consulted extensively with private organizations and government entities, both in the United States and abroad. Her course designs have won multiple awards and have helped take organizations to the next level. She has been passionately involved in instructional design and e-learning for almost 15 years, and is the author of “Instructional Design for ELearning: Essential guide to creating successful eLearning courses." Her major area of expertise is design of innovative eLearning courses that bring results and improve performance. For more information, visit: www.yourelearningworld.com or email@example.com