How AI is Transforming Corporate Learning

Artificial intelligence (AI) is rapidly reshaping the Learning and Development (L&D) landscape, but its impact is still evolving. Today, AI is widely used in learning and development (L&D) to generate content such as course outlines, learning materials, video scripts, interactive components, and assessment questions.

Rather than starting from scratch, AI provides L&D teams with more coherent and organized first drafts that follow instructional design formats. As a result, L&D professionals and instructional designers have less of a creative burden, spend less time on structural editing and more time refining content, enhancing engagement, and aligning materials with learner needs.

With the right tools, AI can also integrate evidence-based suggestions that draw on learning science best practices and instructional design models like ADDIE. It can also customize learning materials to suit specific audiences, tones, or learning objectives, making it a powerful tool for creating pedagogically sound and targeted training experiences.

L&D teams using AI today

More forward-thinking L&D teams now have AI tools as a standard in their technology stack.

For example, OpenText uses LEAi by LearnExperts to convert conference presentations into self-paced courses 31% faster and live training videos into engaging courses 57% faster than traditional methods. It also uses AI to accelerate the translation process by eight times for rapid rollout of compliance training in multiple languages, including complex ones like Chinese and Japanese.

Wise, a global financial technology company, uses AI-generated videos to enhance its training program. The technology has reduced the time required to update training materials by 20% and achieved a 5% increase in learner engagement.

The Naval & Maritime Consortium noted that it uses AI-enabled Scribe to eliminate the need for manual screenshots and video editing, which previously consumed hundreds of hours. The tool’s automated guide generation and voice-over capabilities more efficiently generate polished, step-by-step materials.

Finally, by leveraging HeyGen's AI avatars and multilingual capabilities, Sibelco's Learning & Development team has significantly reduced training video production costs by €1,000 per minute. This adoption has enabled the company to produce more training content faster and made the training process more efficient and accessible.

Beyond content creation

AI is now making its way in other aspects of the L&D lifecycle.

OpenText uses an AI-powered assistant to facilitate conversational search, content discovery, summarization, and translation. This allows employees to access relevant information swiftly, automate repetitive tasks, enhance productivity and ensure valuable data is consistently utilized across projects.

J&J uses AI to analyze multiple internal data sources such as job titles, project work, tech usage, and supervisor feedback to map skills, provide personalized learning recommendations and inform senior leadership on hiring, retention, and internal mobility strategies.

Similarly, DHL uses AI to analyze employees’ skill sets against open positions and recommend targeted training to bridge the gap. This facilitates internal recruitment, allows faster and more cost-efficient filling of roles with a better fit, and supports employee development.

Finally, Bank of America use AI-powered simulations to rehearse complex client conversations in a secure, virtual setting. It provides feedback on tone, pacing, and confidence and gives managers insight into performance trends so they can focus on coaching on weak points.

Managing risks with AI

While AI offers significant potential for L&D, it also presents a range of risks that teams must navigate carefully.

One of the most pressing concerns is the risk of reinforcing ineffective practices. If L&D teams use generic AI tools solely to automate existing workflows, such as rapidly producing large volumes of generic content, they may unintentionally scale poor instructional design. This can result in learners receiving more content faster, but with little improvement in learning outcomes or performance impact.

Another critical risk lies in data privacy and security. Many generic or public AI tools operate on cloud-based platforms that may store, process, or analyze sensitive business data. If L&D professionals input real employee data, internal problems, or proprietary information into public AI models, there’s a risk of exposing confidential details. Organizations must intentionally choose enterprise-grade tools and implement proper data handling protocols, especially in regulated industries.

Loss of human judgment and expertise is also a concern. While AI can assist with content generation, analysis, and strategy guidance, it lacks the nuanced understanding experienced learning professionals bring. Over-reliance on AI without critical human oversight can also lead to contextually inappropriate recommendations or low-engagement content.

Solution to address AI risks

To prevent L&D from becoming overly focused on execution rather than strategy, it should rely on enterprise-grade AI tools to augment expertise, reduce mundane tasks in the instructional design process and support analysis and strategy. This will help L&D teams build stronger foundations for learning experiences that improve performance.

When considering an AI tool for course development, ensure it is purpose-built for training content creation. The tool should support a range of formats such as e-learning, videos, microlearning, and instructor-led training. Assess the breadth of its features—especially its ability to generate diverse types of content and assessment questions—and determine whether it includes automation or content update functionalities that streamline course creation.

Protecting proprietary and sensitive information is another critical area. Choose AI tools that allow you to control the base content used for generation, enabling company- and product-specific training creation. Prioritize tools that support data privacy through access controls and compliance with data protection regulations. Also, ensure compatibility with your existing infrastructure by verifying integration capabilities with learning management systems (LMSs) and support for standardized output formats such as SCORM.

Finally, look for tools that offer comprehensive support through documentation, training, or direct assistance. Scrutinize the cost structure, factoring in not just licensing fees but also the potential ROI in terms of time saved and the strategic value of timely training delivery. Always pilot the tool using your content to evaluate its speed, quality, and reliability before full implementation.

AI is no longer an option

AI tools are part of L&D’s future and offer significant advantages in accelerating the L&D process. However, using the technology requires careful evaluation to mitigate potential risks.

By selecting purpose-built L&D solutions, organizations can ensure strong data privacy controls and focus on usability and long-term value. Taking the time to assess each tool against specific training needs and infrastructure will help ensure that the technology supports, not compromises, learning goals and organizational standards.

About Sarah Sedgman, LearnExperts

Sarah Sedgman, CEO of LearnExperts.ai, started her career as a course developer. She eventually owned some of the largest and most profitable learning businesses at companies like Cognos, IBM, PTC, and Kinaxis. As founder of LearnExperts and board member of CEdMA and TSIA, Sarah’s vision is to help customers build great and effective learning programs.