Generative AI is by no means a new technology; it has been around since the 1950s. However, it came into the limelight in the early 2020s when significant strides and breakthroughs were made in deep learning technology. It was the launch of ChatGPT in late 2022, however, that made generative AI a part of everyday conversations.

Today, generative AI is used in many sectors, from manufacturing to architecture and engineering, and is now a $10.5 billion industry (as of 2022).

One sector where this technology holds tremendous promise and is gaining traction is learning and development. This blog will walk you through everything you need to know about generative AI in learning and development, along with its potential benefits. 

Table of Contents:

• What Is Generative AI?
• Generative AI in Learning and Development: Possible Use Cases
  
  1. Generate Learning Content
  2. Impart Personalized Training
  3. Use NLP to Summarize Content
• Challenges With Generative AI in Learning and Development
  
  1. Data Quality and Accuracy
  2. Ethical Considerations
  3. Data Security
• How Do You Address the Challenges That Come with Generative AI?
  
  1. Use the Right Data to Train the Generative AI Model
• Summing It Up

What Is Generative AI?

Generative AI is a subset of artificial intelligence (AI) that can create new and realistic content, such as images, text, music, or code, using machine learning techniques.

Unlike traditional AI, which can only perform specific tasks based on predefined rules and instructions, generative AI can learn from data and generate original and diverse content that resembles human-created content.

AI-powered learning initiatives can harness this ability and help learning and development professionals in numerous ways.  

Generative AI in Learning and Development: Possible Use Cases

Corporate training is not a field that can afford to be lagging. Whichever sector it may be, technology advancements are rapid, and rules and regulations surrounding compliance change constantly. 

To reskill employees, L&D professionals must stay on par with these changes and develop training content accordingly. This is where artificial intelligence in corporate learning can be a lifesaver.

Here are a few use cases where Generative AI in learning and development can improve learning initiatives. 

1. Generate Learning Content

Any form of training requires the development of content in some shape or form. Traditional methods of doing so are labor and time-intensive and incur significant costs in terms of human resources required. 

Generative AI in learning and development can address this problem with its ability to generate detailed and comprehensive training material in a multitude of formats at a fraction of the time and cost.  

2. Impart Personalized Training

Personalized learning has emerged as one of the top trends in corporate training. Its “adaptive” nature allows it to impart the best possible learning at a pace and complexity that works best for each employee. 

This personalization, made possible by using AI in e-learning, has a proven track record of improving knowledge retention and engagement levels. The same technology can be used to introduce gamification into your training program. 

In conjunction with the data analytics capabilities of AI, L&D professionals can also get valuable insights into the current state of competency of their internal teams and plan for additional training exercises accordingly. 

3. Use NLP to Summarize Content

Generative AI works on the fundamentals of Natural Language Processing. L&D professionals can harness this capability of AI in corporate training and incorporate a feature into their training content that can summarize complex concepts clearly and concisely. 

Doing so can help L&D professionals:

• Shorten training sessions, thus imparting effective training with minimal impact on employee productivity. 
• Improve comprehension of complex topics without information overload and enhance retention of the knowledge imparted. 

Also Read: Generative AI in Education: Know Meaning, Benefits & Challenges

Challenges With Generative AI in Learning and Development

While AI in training and development holds tremendous potential, it poses a few challenges.

1. Data Quality and Accuracy

Generative AI “learns” from existing data, so any inconsistencies, noise, or outdated information tends to reflect in the output of these models. This technology is also prone to hallucination- in simple terms, it can make up facts and confidently assert them.

Any biases in the training data will also tend to reflect in the output of these models, which can have a negative impact by ingraining said biases during training. 

2. Ethical Considerations

Generative AI models tend to infringe on copyrights and sometimes plagiarize when generating content. The infamous high-profile case of Getty vs. Stability AI is a prime example. 

3. Data Security

Generative AI models can create content that may be sensitive or confidential for corporate training purposes. For example, they may generate content that contains personal or proprietary information or that reveals trade secrets or strategies. 

How Do You Address the Challenges That Come with Using Generative AI?

Technology can be both a curse and a blessing, and it all comes down to how one uses it. That said, generative AI in learning and development ticks all the boxes L&D professionals need to stay on top of the dynamic environment they work in. 

The challenges mentioned above can be overcome or mitigated to a certain degree by sticking to a few best practices. 

The first and foremost practice to implement when using AI in corporate training is to have a system of checks and balances. 

You could use third-party tools to verify the output of the generative AI model used for your training content. 

As we have already established, technology isn’t perfect, so do not eliminate the human element as an additional layer of oversight. L&D professionals should establish a system that regularly audits and monitors this technology. 

1. Use the Right Data to Train the Generative AI Model

Verify the data used to train the AI model you intend to use for your corporate training. Ensure that the data is accurate and free of bias. 

That said, you should also establish a practice of retraining and fine-tuning your Generative AI model to improve its accuracy and to ensure that it is updated with the most recent information to generate relevant and up-to-date training content. 

Also Read: Challenges and Opportunities of Generative AI in Assessments

Summing It Up

Generative AI in learning and development brings with it a multitude of advantages L&D professionals can harness to improve their learning initiatives. As this technology is still in its nascent stage, it does carry with it a few potential concerns.

That said, following the best practices above can help mitigate those potential concerns. Ultimately, if you want to stay ahead in the corporate training game, generative AI is the way forward. 

Hurix Digital is at the forefront of providing digital content solutions that can help you take your corporate training initiatives up a few notches. With over 20 years of industry experience, we can help you develop a wide range of training solutions to match your unique specifications and needs. 

Book a consultation with us to know more.