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About This Paper

Association of Training & Development researched that a well-performing training program can enhance an employee (trainee) productivity by 5.62%. However, most of the organizations report very less productivity improvements on their T&D investments. ATD has observed that this low ROI is because of 3 important factors – one of which is related to the job support from managers by providing adequate resources / tools and opportunities to apply what has been learnt.

This whitepaper talks about how organizations could benefit from their T&D investments by using Artificial Intelligence, which can provide both pre and post training support while on the job with personalized learning based on the individual employee learning needs / abilities.


Progressive organizations typically do what is called as a Training Needs Analysis (TNA) annually to identify the knowledge and skill gaps of employees vis-a-vis the business strategy.

Interestingly, the whole of HR function in pioneering organizations is being transformed to a business partnership model, where HR is more about managing talent rather than handling day-to-day employee grievances and other mundane administrative tasks. After completing a TNA, organizations plan respective training programs that could abridge the identified skill gaps.

However, most of the training programs that are offered by organizations to their employees – either in a classroom or online formats (LMS or Video sessions) – do not factor in the unique learning needs and capabilities of each employee.

This is where Artificial Intelligence could be put to most effective use. Additionally, AI tools can offer post-training support at any time and thereby, enhance the RoI on T&D investments.

Challenges of Traditional Training Programs

Content designed for factory model of production: The traditional training programs are designed to address the needs of factory model of production, where the emphasis is on the mass to ensure process compliance against a set of standards. Hence, most of the content built for a training program is common to train alike all the employees who work on similar tasks.

Lack of personalization and adaptability: The traditional training programs can not identify varying knowledge levels of each trainee attending the program. And, the content is usually built without factoring the individual employee learning capabilities or his / her ability to innovate.

Complexity in content navigation: Some of the Learning Management Systems (LMS) implement functionality which makes it complex to navigate
the training content and thereby, leading to poor learning experience.

Difficult to measure training RoI: In traditional training programs, it is difficult to collect accurate data of employee’s learning outcomes and hence, a challenge in calculating the return on investment of these programs.

Using AI to Address the Limitations

Personalized Learning: It is about empowering the learner acoss four dimensions – time, place, pace and path. Further, technology is used to facilitate this personalization by tailoring the content and creating a learning plan specific to the learning needs of each trainee (employee). Using AI for personalized learning further enhances the quality of learning, and thereby increases the RoI of AI-based L&D systems that facilitate the training programs. When compared with humans, AI can easily gather large volumes of data, analyze and interpret it. AI-based L&D system can identify patterns and help managers by giving actionable advice.

Implementing non-AI based personalized learning for every employee to abridge the respective skill gaps demands a bigger T&D budget. And, using AI to facilitate personalized learning of an individual in multiple skills helps reduce these costs at a fraction of the budget.

Also, AI helps in giving more personalized learning experiences as trainees (employees) can learn at their own pace, path and time based on their respective learning capabilities. AI removes the concept of one-size-fits-all.

Shortening employee learning process: A smart AI-based L&D system allows the trainers to break the large training modules into chunks / small lessons, wherein the individual can easily understand and learn. Small quizzes, surveys, and feedback are part of the training process. AI helps in giving greater insights into these surveys by telling who is truly engaged in the learning. Task-based on-boarding has proved to be more effective rather than asking people to sit for hour-long lectures.

Training accessibility for all employees: AI can be used to drive virtual training more effectively and efficiently. For instance, in a study it was found that remote workers are likely to be more productive than the workers in the office who follow a proper work-day schedule. Further, large companies with head office and divisions / branches dispersed geographically across the globe find it difficult to train all employees at one time and in one place. AI-powered virtual training programs not only solves this problem, but also
can measure employee learning needs and deliver content for the best learning outcomes using virtual assistants. These training sessions can be attended by anyone – either sitting at home or the office.

How We Can Help

We build and host scalable, budget-friendly proxies (chatbots, virtual assistants and enterprise search applications) that can be seamlessly deployed either on the organizations website or Learning Management Systems (LMS) like Moodle or portals like Oracle HRMS etc..

Together with a good LMS, these proxies can not only help in improving the RoI on T&D investments, but, also could deliver best possible learning Outcomes.

Further, the proxies themselves can be built and deployed incrementally. For e.g., initially a virtual assistant can be created for one training course and deployed for 24×7 access to employees. Later, it can be trained to include all the courses in a specific division in the organization and finally, it can be expanded across the organization. Also, the virtual assistant can be trained to conduct scheduled assessments and generate grading reports post-assessment of the employees to measure the overall RoI of each training program.