Whether shopping online for supplies or searching for a new TV show to watch, people are becoming increasingly accustomed to personalized content in their daily lives. Much of this personalization is being driven behind the scenes by artificial intelligence (AI) and machine learning (ML) technology, which can tailor products and services to the specific needs of each individual, based on their past behavior and preferences.

In essence, the more personalized an experience feels, the more we enjoy it.

ML is a sub-field of AI. Quite simply, it uses algorithms to help computers find complex patterns in data, and to learn on their own. ML can make training content more relevant and boost knowledge retention by ensuring that participants can put their learning to use immediately in their jobs.

Relevance + Practice = Retention

Within the learning and development (L&D) realm, AI and ML can be used to automatically adapt content and classes to the specific proficiency level, professional goals and personal interests of each learner.

Pedagogic engines can select content that is most relevant to the interests and needs of an individual learner and adapt the activities accordingly. For example, a learner who struggles with listening, can be offered visual or tactile content. AI-powered technology can also be used to track performance and continually adjust content, so that learners are working right at the edge of their abilities. This kind of adaptive, hyper-personalized approach is more efficient and more effective in many types of training, especially those involving hard skills, which require mastery in order to perform specific tasks.

In the 1880s, psychologist Herbert Ebbinghaus was the first in his field to observe what he coined “The Forgetting Curve,” which measured how much we forget over time. He concluded that, without any reinforcement or connection to prior knowledge, information is quickly forgotten — roughly 56% in the first hours, 66% after one day and 75% after six days.

However, putting new knowledge and skills into practice on the job can dramatically flatten that curve, especially if it happens within 6 days after the learning occurs.

For example, in language training programs, hyper-personalized courses can be built on relevant and interesting content delivered at precisely the right level of proficiency, using real-world materials taken from major media websites. By combining relevant content with activities designed around specific job roles, this kind of training captures the attention of learners, engages them more effectively, and motivates them to practice reading, listening, speaking and writing when the lesson is over.

Imagine a situation in which a U.S.-based global enterprise organization has a finance professional working in Latin America who needs to sharpen their English skills in order to better communicate and collaborate with corporate headquarters. Rather than enrolling in a generic course based on outmoded, traditional teaching techniques, AI and ML make it possible to design a curriculum specifically around accounting, insurance, securities analysis, and other types of financial services, and deliver it online, to be consumed in whichever way the learner prefers (e.g. desktop, tablet, smartphone, etc.). Lessons can be delivered in short, digestible bursts that are optimized for learner engagement and knowledge retention. This way, learners can immediately apply what they’ve learned on the job, practicing new skills within just a few hours, rather than waiting for days or weeks to use them.

The Human Touch Will Always Be Essential

Of course, it is important to emphasize that this kind of technology will never replace human beings. There is no algorithm in the world that can give the type of personalized feedback a trained professional can offer in a video call or in-person conversation. But utilizing technology to deliver just-in-time, personalized learning content can maximize the effectiveness of training professionals, freeing them to concentrate on the kind of interpersonal communications that cannot be outsourced.

Here are a few tips for training professionals who want to increase their efficacy through hyper-personalized content:

1. Set personalized objectives for each learner. Ask questions about their learning needs in order to select the right content that will help them to achieve real-world goals.
2. Select lessons dynamically, based on the career goals, personal interests and proficiency level. Include a variety of multimedia resources that are current and relevant, and adapt in real time, based on how the learner is performing.
3. Follow the individual progress of each learner. Don’t just follow a stale, predetermined path for learners to advance from one level to the next. Every learner deserves a unique experience that will maximize their chances of success.

Personalization is the key to effective training and using a combination of adaptive technology and experienced instructors is the most powerful way to make that happen.