AI Offers Consistency to Learning & Development

Have you ever encountered an organizational challenge that sort of snuck up on you? This

seems to happen often! In today’s growing organizations, AI in learning and development is increasingly being explored as a way to support consistency, quality, and scale across training initiatives. Let’s consider one quick example from the Learning and Development meets HR world. The organization is growing and more people are needed - new team members begin to join the company and now the onboarding process gets people started. All ok so far. The obvious need was getting people into the organization and trained in enough areas that they can effectively contribute. If this represents an obvious initial challenge to address, the focus of this particular blog post can sometimes come along as a hidden challenge for L&D leaders, one that can actually get worse with scale and is a sign that increased complexity has entered the system. That challenge is summed up by the word “consistency”. 

For L&D leaders, the challenge of consistency is one that shows up in a few different ways: 

• Are all employees getting the same level and quality of training?

• Is training delivered equitably?

• Is the evaluation of learning consistent across the organization?

• Is compliance training delivered as consistently as needed?

• Are core skills being taught consistently to the same level?

• Is the organizational culture always presented consistently? 

Training has always had some level of variability - this is sometimes considered to be the “human element” in training. We might add here that 100% consistency and uniformity within

Learning and Development is not reasonable as an aspiration. Yet, in this post, we consider if AI can help us to reach greater levels of consistency that help elevate the overall quality of Learning and Development for an organization. 

Here are 3 areas to consider where AI can offer consistency:

1. Standardized Content & Structure

   AI can help deliver the same quality and structure to every learner. While some variability will likely persist across training, AI can help to minimize how much this occurs through the delivery of training across multiple teams, regions, in different languages, and all done according to the specific needs of the organization. This is especially important where there is a shortage of capacity for training from local trainers in different areas of the organization.

2. Personalization With Structure

   AI can adapt learning paths based on role, behavior, and performance. This provides a way for learners to grow in their roles in ways that align with their specific learning needs, yet ensures that this is balanced with the structure needed in meeting overall organizational goals. 

3. Evaluation Insights and Feedback 

   AI has the power to provide analysis and feedback on learning that is scalable. It can provide individuals with feedback on their learning and manage the adaptability of personalized learning within an organizational evaluation structure. This offers additional capabilities that can enhance the work of HR and L&D professionals, especially in scaling evaluation efforts and making updates to training based on a data-informed approach. 

In sum, AI can help L&D work to become more effective through establishing greater consistency in the design, development, and evaluation of learning. L&D leaders can have greater assurance that quality and standards are being met more effectively and frequently, and learners can benefit from knowing they are receiving training and feedback that is consistent with the organizational structure and their individual needs