6 Opportunities You Can Capitalize on Using AI-powered Adaptive Learning

Forecasts show the growth of Artificial Intelligence in the educational domain for the following years, including one of the key trends – AI adaptive learning. That is evidence of favorable market conditions for disruptive ideas, new AI-based educational startups, and new rounds of investments. In this article, we will consider which opportunities AI-powered adaptive learning uncovers for various organizations, including businesses, colleges, and schools.
***Faster Training Program Scaling*
*In the traditional learning model, a tailored approach is possible only for small classes. A mentor can’t dedicate time to each learner’s needs in big teams. When a company plans to increase its staff and scale the corporate training program for raised demands, it might be an inhibitor factor.
AI-based adaptive learning platforms enable companies to scale fast and without extra funding because they offer a personalized learning path without human mentoring in every interaction. A supervisor can be included in the learning process by request. This model doesn’t limit the number of employees, eliminating excess burdens for Learning and Development (L&D) departments.
**Optimized Costs for the Learning & Development Program
**People absorb information faster and easier when they have a teacher. A mentoring system is also important for acquiring new knowledge and skills in the corporate sphere. The National Mentoring Day survey proved that almost every responder considers this model to be effective. But imagine what happens when a company hires a personal mentor for each employee. Its expenses would increase at least two times.
By incorporating AI-powered adapting learning software in the corporate training program, companies can ensure each employee will have an individual digital mentor. Moreover, this teacher will know everything about a trainee in advance because of prompt analysis of their profile in a Learning Management System (LMS) or Learning Experience System (LXP). That is why its learning path will be adjusted for a learner’s current progress, interests, and goals.
**Enhanced Upskilling and Reskilling Process
**The well-built and smooth upskilling and reskilling process helps companies win the competition in the ever-evolving job market. New professions appear, and previous hard skills turn out to be outdated. The talent pool is limited because the market doesn’t manage to adapt to changing conditions.
An AI-based adaptive learning system allows organizations to follow trends and adjust their training programs for new challenges. The system is able to update the curriculum by parsing various databases and sources. For example, a legal training course can be improved by an up-to-date case law, which provides a company with a competitive edge in similar situations.
The government sector is also actively leveraging this opportunity. A US-based government agency created a 20-year forecast, keeping in mind such factors as demographic changes, innovative solutions for public transport, and self-driving car development. The project includes predictions about talent pool gaps in this domain. For example, the transport sphere might need more AI analysts, urban/rural mobility managers, or autonomy engineers. Being aware of such demands in advance, the organization can start optimizing its workforce already now.
**Boosted Learning Engagement
**An outdated educational system provides a unified learning format for whole classes. But the point is that each learner has their level of progress. When we talk about business, even people in the same positions might have different grades of competencies.
An AI adaptive learning platform enables people to follow their bespoke training path, filling in their gaps without rushing. For example, developers can address coding tasks according to their knowledge of the particular programming language. If they set a goal to learn a new language, the system will create an appropriate learning path to satisfy their interests and professional ambitions.
The system adjusts the learning process to trainees’ performance, turning back or moving forward based on individual results. Thus, people won’t get bored with the standard curriculum.
Attention to people's needs, interests, and individual advantages builds a rapport between employees and an organization. Thus, companies get more loyal and engaged personnel, ensuring the in-house culture of continuous learning.
**Accelerated Process of Acquiring Knowledge
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Studying irrelevant learning materials can cause procrastination if people prefer to dedicate time effectively. Ultimately, people aim to avoid unpleasant learning processes, likely losing useful information as well.
The research found that organizations might decrease time for Learning and Development (L&D) by 50% on average by adopting AI adaptive learning systems. Firstly, employees don't waste time on already acquired knowledge and skills. Secondly, a tailored approach boosts their motivation, as described above.
Yet, the core competencies need periodical revising, because repeatedly accrued gaps are inappropriate in this case. To eliminate this risk, AI adaptive learning software uses algorithms to spot knowledge breaches and suggest learners refresh tasks. Ultimately, they consolidate their competencies and can apply them promptly when needed.
**Improved Assessment Process
**Both learners and mentors often don’t see tangible outcomes from assessment systems. The reason is that they assign grades without a step-by-step guideline of what and how to improve effectively.
In this case, leveraging an AI adaptive learning platform also can be helpful, because it provides mentors with detailed information about the weaknesses and strengths of their mentees. Learners get a thorough plan on where to move further. For instance, the United States Air Force and the United States Army implemented the system when each learner gets a training program tailored to their strengths.
Bottom Lines
Nowadays, the educational landscape demands new approaches to acquiring knowledge. Both public and private sectors face many challenges, such as scaling limitations, rapidly outdated competencies, low engagement, a poor assessment system, etc. By implementing adaptive learning AI technology in education, organizations can successfully overcome these handicaps.