The Game-Changing Potential of Generative AI in Employee Training

This article was originally published on Spiceworks. 

Ramesh Ramani of ExpertusONE explores how generative AI and NLP are reshaping employee training, offering personalized learning experiences that enhance skills and retention.

It’s an understatement to say that artificial intelligence (AI) has transformed how we live and work. When businesses adopt AI or ML solutions, they often do so through the lens of monetization, seeking optimization and efficiency gains to bolster their margins and streamline their operations. That’s fine, but as generative AI, natural language processing (NLP), and tools such as ChatGPT push AI capabilities to new heights, new use cases that are easy to overlook are emerging. One such case is the application of generative AI in employee training and development.

By leveraging AI technologies such as NLP, trainers and managers can enhance the learning experience and improve the efficiency and accuracy of training programs beyond what was previously thought possible. More than two-thirds of workers in 2023 consider corporate training their organization’s most important feature. At a time when staff churn is on the rise and retention is proving challenging, nearly 4 in 10 employees (38%) cite career advancement and learning opportunities as an important factor when considering their future at an organization.

Businesses should, therefore, focus on training and development, not just to increase their staff retention but to streamline their operations more generally and make training and learning a seamless part of day-to-day work rather than something modular, bolted-on, and easily forgotten. Believe it or not, that’s where generative AI and NLP come into play.

The Rise of Conversational AI

NLP is a relatively new subset of AI focusing explicitly on the interaction between computers and human language. NLP can analyze language and scan for various elements – not just topics and keywords but sentiment, meaning, and context. It can generate summaries and automatically produce reports based on interactions, “get to know” individuals, and provide personalized recommendations based on their needs and requirements, and – with generative AI now coming into view – it can even produce human-like content based on the data it gathers or is given.

The possibilities are seemingly endless, but this technology is best served to augment something already established – an existing product, service, or function. ChatGPT, on its own, is a useful tool. Still, if we take generative pre-trained transformer models and use them to enhance an existing service – such as a learning management system (LMS), the results have the potential to be game-changing.

Take a large retail company, for instance. It might want to train its employees on customer service skills, but traditional training methods such as reading manuals or attending class-based sessions aren’t producing the desired results. Instead, the company can leverage conversational AI to provide a more interactive and engaging learning experience.

A chatbot can be created, accessible via any device, or integrated into the company’s current software ecosystem, allowing employees to ask questions, raise concerns, and get valuable on-the-job feedback. The chatbot could analyze customer-employee interactions in real-time and evaluate employees’ customer service skills based on predefined criteria, including empathy and tone, product knowledge, and problem-solving.

The chatbot could also double up as a training tool, allowing employees to engage in dummy conversations with the AI, which would “learn” responses from prior engagements to test the employees’ capabilities. The chatbot would also adapt its responses based on employees’ progress, adjusting its suggestions based on their current level of knowledge or how well they handle certain scenarios.

The AI could also summarize employee engagements, offer real-time reporting and training recommendations to managers, and build regular reports on the training progress of individual employees. This retail example is basic, but it demonstrates NLP and generative AI’s role in even the most basic employee training environments.

See More: Leveraging AI to Manage Work

The Use of AI in Training and Development

Let’s break down the uses of conversational AI that we referenced in the previous paragraph and apply them to training and development. One of NLP’s main benefits is its ability to analyze human language and sentiment in real-time. That means employers can use it to continuously gather employee feedback as part of their training, identifying areas that cause confusion or fail to meet an individual’s needs. This real-time sentiment analysis can optimize training materials in ways that manual feedback processes fail to deliver, at least not without great cost and application of human resources. In a team of hundreds of workers, it would be too time-intensive for a trainer to home in on the specific needs of one individual and adjust training course parameters to suit their needs. With NLP and generative AI, this can happen automatically, giving employees what they need, often when needed, so that everybody can learn at their own pace.

But NLP can do more than just help to analyze and optimize training programs. It can aid with the delivery of the training itself. For instance, collaboration in corporate training can be enhanced through better communication and understanding driven by NLP technology. Real-time translations can break down language and cultural barriers, allowing training sessions to be delivered to employees worldwide without the risk of anybody feeling disadvantaged. Automated chatbots can be implemented to answer employee queries during live seminars or pre-recorded training exercises, giving learners more control and allowing them to fill in the gaps in their knowledge at their own pace.

See More: How NLP Will Unlock the Value of Data for Businesses

Generative AI can also assess individual employees’ capabilities and knowledge levels, even tailoring courses to suit specific needs. With generative AI, there’s very little reason two employees of different experience levels with different learning requirements should have to undergo the same training course – instead, they will each receive a version of that course that’s more in tune with their learning needs.

One of the greatest aspects of integrating generative AI capabilities into an LMS is the ability to facilitate seamless on-the-job training. Instead of taking a day or a week out of their busy schedule, an AI-powered LMS can provide a real-time, modular approach to learning that works with employees as they carry out their day-to-day tasks. For instance, if the system detects that an employee lacks experience in a given application, a module can be embedded within that application to offer a brief tutorial or answer any questions that are likely to arise. Similarly, context-based learning modules can appear in digital environments where employees most frequently spend their time, giving them more exposure to tailored learning materials. At the same time, they go about their working day.

Exploring AI Offerings Beyond Sevice and Monetization

As we continue to explore the applications of AI, it’s becoming increasingly clear that its potential extends far beyond the realms of service and monetization. In particular, using conversational AI and NLP in employee training and development can potentially revolutionize learning.

By leveraging these technologies, employers can gain real-time insight into employee sentiment, optimize training materials, and tailor courses to suit individual learning requirements. Moving towards a future where career advancement, self-pacing, and self-service are becoming increasingly important to a distributed workforce, businesses that prioritize training and development, with the help of AI, will be better positioned to retain talent and remain competitive in the coming years.