Learning and development (L&D) teams are under increasing pressure as organizations expect faster onboarding and continuous upskilling to meet increasing workload demands, often with decreasing headcount and budgets. With U.S.-based employers cutting 83,387 jobs in April, up 38% from cuts recorded in March, employees are expected to do more with less. This creates a demand for training content to grow in volume and also be accessible, engaging, and easy to update at scale.
Artificial intelligence (AI) can help meet those demands, but success depends less on adopting AI than on using it strategically. TechSmith’s recent study found 75% of people were receptive to instructional videos created with AI assistance, suggesting organizations can expand production without sacrificing learner acceptance. Scaling content does not require building massive production operations; L&D teams must be smarter about the resources teams already have. The challenge today is no longer whether AI should be used within the content, but how to use it effectively.
Turn Existing Meetings Into Training Assets
One of the biggest mistakes L&D leaders make is assuming every training video must be created from scratch. Organizations already have enormous amounts of instructional content at their disposal through recorded virtual meetings and product demos, with subject matter experts (SMEs) regularly explaining workflows and processes and answering commonly asked questions. This makes recorded video conferencing platform meetings some of the largest untapped content libraries.
Today’s video creation tools can integrate with conferencing platforms such as Zoom to automatically:
- Identify key moments
- Remove filler language
- Improve audio quality
- Generate captions
- Summarize discussions
This changes the creation of training videos entirely. Instead of scheduling additional recording sessions or pulling already overworked SME’s away from tasks for formal shoots, these leaders can repurpose conversations already happening naturally.
Use AI Avatars and Voices Strategically
Repurposed recordings solve only part of the scaling challenge. Organizations also need efficient ways to produce consistent training across large content libraries.
AI avatars and synthetic voices allow L&D teams to create video content without the need for camera setups or on-screen talent, update scripts or content without reshoots and maintain consistent narration, branding and presentation across programs.
Learner acceptance, however, depends heavily on quality.
In another TechSmith study, 92% of participants believed a high-quality AI voice stood out as the most professional sounding compared to other voices evaluated. On the other hand, learners noted that poor audio quality made content harder to follow and more distracting. The same results applied to AI avatars. When avatars appeared in a picture-in-picture format, 72% of participants rated the avatar quality positively. But when the avatar filled the viewer’s entire screen, that number dropped to 55%, with participants noticing robotic traits in full-screen avatars.
It’s important to note that AI-generated voices and avatars are not appropriate for every training scenario. They should not replace authentic human communication in situations such as:
- Leadership messages
- Welcome videos
- Culture-building initiatives
- Emotionally-sensitive topics
Using AI selectively allows organizations to gain efficiency without sacrificing trust or authenticity.
Expand Visual Content Faster With Generative AI
Image creation is another area where AI can dramatically reduce workload for training teams. Traditionally, creating graphics, illustrations and scenario-based visuals required either design expertise, outsourced support, stock image libraries.
Generative AI significantly shortens that process by allowing instructional designers to create custom visuals from simple prompts. Teams can quickly develop workflow diagrams, conceptual illustrations, software mockups and scenario-based graphics tailored to specific learning objectives.
The technology still requires human oversight.
AI-generated visuals can still contain noticeable inaccuracies, such as distorted hands, inconsistent objects, unreadable text or unrealistic environments. Training professionals should always review generated images carefully before publishing them. Organizations also need to pay attention to licensing and intellectual property considerations. Some free image-generation platforms limit commercial usage rights, while enterprise-grade AI platforms often provide stronger legal protections As AI-generated media becomes more common in workplace learning, governance and compliance processes will become increasingly important.
AI Supports Better Content Scaling — Not Better Instructional Design
AI does not replace instructional design expertise. It removes many of the production barriers that have historically limited how quickly L&D teams could create and maintain learning content.
Organizations that combine AI efficiencies with sound instructional design can update training more quickly, produce content more consistently and expand learning programs without compromising quality or learner trust.
The most successful AI strategies will continue to pair automation with human judgment, ensuring that technology enhances the expertise that effective learning experiences require.
