Welcome to a three-part blog series on the role – and potential – of AI in Human Resources, specifically Learning and Development (L&D). We sat down with Erik Duindam, Head of Engineering for Everwise, who recently published a white paper on AI’s potential for L&D. Erik provides informed and informative thoughts on the direction of AI in learning and development, and we’ve worked to capture his thoughts and share them with you. The next two articles address the role of AI in L&D programs, and facilitating learning experiences with AI.
According to Bloomberg, Artificial Intelligence (AI) is likely to be the most disruptive force in technology and HR in the coming decade. It’s also critical to the evolution of learning and development (L&D) in organizations worldwide. AI may still be in its infancy, but basic AI software and tools are already beginning to impact the workplace. Companies are rethinking their organizational charts, hiring practices, training methods and more.
What is AI?
In the business and technology worlds, AI is an umbrella term for autonomous machines, software and algorithms with learning or problem-solving capabilities. Computers can understand natural language to communicate with humans. They can make predictions based on data. They can analyze physical surroundings to drive a vehicle. They can simulate neural networks of the brain to recognize images or translate text. In short, they can figure things out for themselves.
The Importance of AI for HR
As AI begins to change every aspect of how a business works, companies must also reevaluate their L&D strategies. AI and smarter software is already being used to offer a more tailored learning journey. Smarter software powers personalization, social interaction and higher content relevance for users. And it gives L&D professionals the tracking and analytics they need to measure program effectiveness across multiple audiences.
However, many companies are still training for skills that don’t match their actual or future needs. Why? Because they are not able to collect and interpret valuable data to identify employee skill gaps and drive business outcomes. This is where AI will prove especially useful. A machine can easily analyze and combine data from various sources, such as different learning programs and HIRS systems.
“If you can combine all that data and run AI machine learning algorithms over it, then you could draw all kinds of conclusions,” says Erik Duindam, Head of Engineering for Everwise.
AI-powered innovations by companies such as IBM are leading the way to solve these problems. IBM can now predict future skill gaps and performance. With this information, organizations can create more effective, self-optimizing learning programs. AI-powered platforms can make employee-specific predictions and recommendations for skill development, future performance and collaborative learning experiences by analyzing various data sources.
How AI can predict the future
In order to adapt to the changing technologies, organizations are moving away from a traditional hierarchical structure. And L&D departments will have to change how they help those employees learn and grow in their career paths as well. It will be more difficult for management to see what skills need to be developed in a more fluid, cross-functional environment. Obtaining and listening to employee feedback will become even more valuable in the new environment.
“To actually understand what people should be learning or what skills are lacking, you are going to have to listen to employee feedback more than was necessary in the past,” says Duindam.“You’re going to have to collect intelligence from all of your employees not just data from systems and managers.”
Machine learning, more specifically, deep learning will help with gathering and interpreting the various sources of data. Deep learning is a technical concept based on artificial neural networks that makes computers able to learn automatically without introducing hand-coded rules. Machine learning and deep learning algorithms are widely available via open source software libraries and cloud computing platforms such as IBM Watson, Amazon Web Services, Google Cloud, and Microsoft Azure. That means any company with the right set of data should be able to make AI-powered predictions.
“If you can use a lot of data from different sources to identify what the skill gaps are and if you can predict what your skill gaps will be in the future, then you can offer better learning programs,” says Duindam.
To learn more, read Erik’s white paper on “The Role of Artificial Intelligence in the Evolution of Learning & Development.” And look for parts two and three of this AI series in the coming week. Thanks for reading!