In a 2023 World Economic Forum report, surveyed companies predicted that 44% of workers’ skills would be disrupted in the following years

Demand for new skills is growing, accelerated by technology advancements, industry changes, and macroeconomic forces. Technology-related skills gaps, meanwhile, harm innovation and competitiveness. Companies may decelerate a new AI or cybersecurity program simply because their people need to gain the skills to run the program.

Learning and development (L&D) teams have been experimenting with addressing these skills gaps, but traditional approaches must catch up to the growing demand. A survey from Manpower shows that 57% of employees are pursuing training outside of work because they believe “company training programs don’t teach them relevant skills, don’t advance their career development, or simply don’t help them stay competitive in the marketplace.”

Embracing Generative AI can help L&D teams bridge these skills gaps more effectively and keep pace with changes across all industries. GenAI capabilities are growing day by day and are well positioned to play a significant role in developing L&D programs that are more efficient, effective, and engaging.

Opportunities for GenAI in Learning and Development

Opportunities to infuse GenAI into L&D programs will continue to grow. Right now, the following three use cases will be particularly advantageous:

1. Outcome-Based Needs Analysis
Training needs analysis is an essential yet time-consuming part of any learning and development program. Teams need to identify the skills gaps, build the training necessary to develop those skills and find a way to measure the success of this training. 

GenAI can fast-track these tasks by automating KPI analysis and market research. L&D teams can upload relevant documents — everything from standard operating procedures to company policies, design documents, guidelines, protocols, and notes from interviews and discovery sessions — and GenAI can scan these documents and generate insights based on specific queries from the team.

In this way, GenAI can reduce the time required to conduct a baseline training that drastically needs analysis, which the teams can validate and enhance as required. Beyond just a faster turnaround, GenAI promises more in-depth analysis by allowing teams to spend less time gathering information and more time analyzing it.

2. Content Development
Developing content is another time-intensive task. The average L&D content development cycle requires a coordinated effort from visual and instructional designers, programmers, content developers, and team leads. Each of these teams needs input to guide their content development, time to work on the project, review it, incorporate feedback, and review again. All this adds up. As organizations seek to create more personalized content, teams may need help keeping up with requests.

GenAI can help with nearly all aspects of content generation, including scripts, audio, video, and assessment questions. Teams can use this GenAI-created content as starting points for their projects, refining as necessary. They can also use GenAI to translate content into other formats to accommodate the varying learning needs of different individuals — translating text to image, for example, or using more user-friendly language to describe highly technical concepts.

Human involvement is still significant to ensure content is relevant, accurate, and aligned with company standards. Even if teams only use GenAI to brainstorm concepts, that support can help teams provide more varied, personalized learning materials faster.

Platforms like Canva, Powtoon, and Adobe Firefly already use GenAI capabilities to generate content based on prompts. L&D teams can get more from these tools by using them to develop bite-sized content that is easy to engage with, evaluate, and adapt as needed. Other platforms like Smart Sparrow combine this rapid iteration capability with machine learning or data analytics capabilities to help teams deliver content tailored to the unique needs of teams or individual users.

3. Program Roll-Out
There are two primary approaches to rolling out learning and development programs: a push approach, which is common to most traditional learning management systems (LMSs), and a pull approach, which is characteristic to learning experience platforms (LXPs) like Fuse, Edcast, and Degreed — all of which are using GenAI to enhance functionalities.

The push approach “pushes” learning courses on individuals based on needs defined by the business or by another team acting on the business’s behalf. Think of a company-wide training for cybersecurity best practices or workplace conduct. These programs tend to be very generalized. They may deal with a specific topic (cybersecurity or proper behavior in the workplace) but they are designed to work for many individuals across a large group. Unfortunately, this can lead to material that is less effective for many individuals than tailored content. (Think back to that earlier statistic: 57% of employees don’t believe company training programs will provide them the skills they need).

A pull approach, on the other hand, analyzes an employee’s daily activities and creates learning content based on those activities. What platforms is the employee using? What systems? Where is this employee succeeding and where are they struggling? Employees can then engage with the most helpful recommended content at their own pace (i.e., “pull” it toward themselves, rather than have it “pushed” on them).

GenAI can support the pull approach by making it easy for L&D teams to analyze a learner’s past performance along with preferences and career objectives to create customized learning paths. This is typically a time-consuming manual process done by the Learning Lead. By incorporating GenAI into that process, Learning Leads may be able to draw deeper insights faster and run different scenarios to offer more personalized content suggestions. Teams can use GenAI to administer exams and check responses, track learning progress, and suggest related content based on performance. GenAI-based LXPs can also automate various administrative and onboarding tasks for new hires, such as learning program enrolment, training/exam scheduling, and reminder prompts.

These GenAI-enabled interventions currently operate independently of one another. They should build on each other, but are not currently unified by a single platform. As GenAI continues to advance, there’s an opportunity for companies to integrate these tools into a single platform or partnership network. The result will be a more seamless user experience for learning and development teams that will help empower employees to keep pace with innovations throughout their industries.
For now, learning and development teams can make great strides in advancing their programs by employing GenAI for needs analysis, content development, and program rollout. In the long run, as GenAI capabilities expand, L&D teams will leverage this technology to continuously make L&D efforts more personalized, responsive, and data-driven. 

About the Author

Abhishek Nag
Senior Manager, Global Talent and Development

Abhishek is a Learning and Development Practice Leader and brings a wealth of experience in designing and implementing learning strategies that drive organizational growth and individual skill development.