Artificial intelligence (AI) has been a learning and development (L&D) tool for longer than most realize. Considering that the eLearning market is predicted to reach a value of $44.6 billion by 2028, it’s easy to see what a huge part of corporate training and development AI has been and will continue to be. AI in corporate L&D shapes how we design, deliver and measure training.

AI is used in content curation, adaptive learning platforms and predictive analytics, leading to higher levels of individualization. However, beginning to use AI in your company’s L&D processes can seem daunting. The good news? Achieving AI fluency doesn’t mean your team members need to become some version of a data scientist.

Here are the steps that L&D teams can follow to adopt practices that are supported by AI and ultimately guide their teams to become more competent regarding training in an ever-more AI-enabled world.

AI Myth Busting Starts With Common Ground

It’s important to create a shared level of fundamental understanding about AI amongst your team members before exploring tools or pilots. AI misunderstanding could lead to fear, opposition or unreasonable anticipation. Begin with the basics of what AI actually is. What are the differences between machine learning and automation? What risks, limitations and ethical considerations are there? Organize a group learning event or prepare an in-house course.

You can find a curriculum that best fits your company from places like Open Learning Library of MIT or IBM SkillsBuild. Use case studies of AI in L&D to make abstract concepts relevant to your company. Pay attention to the practical side of the subject to make it as relatable as possible to the team. The goal should be to provide your L&D team with basic AI literacy so they will be curious about what it can do and not worry about what it could do.

Find High-Impact, Low-Barrier Use Cases

Attempting to apply AI in all areas of L&D simultaneously is not feasible. Start instead with a small number of opportunities where AI will deliver results in simple but useful and impactful ways. There are two ways to get quick wins and gain momentum.

The first is in content curation. Use AI GPTs to help recommend software or in-depth readings and ongoing learning paths. You can then create your basic outlines and ask a GPT to write one-sheets or full training documents. This lets you take generic learning pathways and tailor them to your company and each specific team that L&D touches. Then, you can deploy learning analytics in the form of AI-based dashboards that can track learner engagement, identify skills gaps and forecast performance trends. These applications provide fast, accurate and actionable returns and do not need massive development by a tech team.

Start with each of these by selecting initial AI use cases that respond to obvious business requirements and that are as practical as possible for your teams.

Conduct an Audit of Your Existing Systems for AI Readiness

The foundation of any AI adoption effort is infrastructure. Before beginning any build-out or deployment, conduct an audit of your systems, data and team’s skill level. Consider:

• Data: Is the data you’re basing your team’s learning on clean, readily available, and able to be interpreted as needed? You can’t create and conduct impactful training with AI if the curriculum and learning path AI creates is based on bad data.
• Systems: Can your learning management systems (LMSs), eLearning platforms and/or human resources (HR) systems integrate AI or have APIs? If not, this needs to be built out before you begin.
• People: Do you have any team members that have worked with AI in any capacity at another company? If so, use them as your subject matter experts. They can speak the language and will be more adept at knowing if the AI is performing as it should. Lean on them for feedback at every step of the process.

Use this audit to detect gaps that might impede the use of AI and upgrade foundational areas as required.

Pilot AI in a Sandbox Environment

After you have decided what areas of L&D you will use AI for, and have conducted your audit, do your first deployment in a sandbox environment. Identify a particular project or a group of learners who you can test an AI tool in a real setting.

In this pilot, you must determine clear metrics to evaluate the users’ experience. For example, you can measure engagement rates of the training, time for completion, learner satisfaction and final scores on knowledge checks. Post-pilot, have full in-depth feedback sessions with all users. Ask: Was the process smooth or clunky? What did they actually learn? You need to ensure the AI is user-friendly and is teaching exactly what you need the people to learn.

Encourage Experimentation

What works today will be outdated soon enough. Your company’s goal for deploying AI in training needs to be to develop a culture based on learning and experimentation. Continuously have your team experiment with new tools, speak up on what they have learned, and ask questions. To make it work, it might be a good idea to assign AI champions to an L&D organization (i.e., those who are eager to test the tools, document the processes and assist colleagues).

Be transparent about the use of AI and what your decisions are based on. Continually remind your team that AI is always under strict human control and is here to help the team, never to replace it. A psychologically safe environment fosters adoption, innovation and adaptability to change.

Commit to Organizational Ethics in AI Use

Align your AI programs with your greater business and moral aims. Collaborate with IT, HR and compliance to address how your L&D activity complies with legislation on data privacy, diversity, equity and inclusion (DEI) principles as well as internal culture and ethics. This broad level of cross-functional alignment increases your credibility with the larger team and guarantees that L&D gets a seat at the table when AI strategies develop across the company.

AI is not new in L&D, but it’s a paradigm shift in the learning process. The capability to embrace AI is not only a powerful tool for L&D leaders, but embracing it also gives the team influence on its use in the future of work. Start small, remain curious, and give more attention to people than tools and you will be able to lead your organization through a thoughtful and effective AI transformation.