Artificial intelligence in learning design: practical use cases across sectors

Practical examples show how Artificial Intelligence speeds instructional design and content development workflows without replacing human creativity.

Large language models changed the game for learning teams almost overnight. ChatGPT now draws roughly 5.2 billion visits per month, and a 2025 Pew Research Survey found more than half of workers are worried about future impacts of Artificial Intelligence at work, with 32% specifically concerned about job opportunities. Against that noisy backdrop, the authors Lucas Marshall and Jason Braun lay out concrete ways learning professionals are folding generative tools into everyday course production and content pipelines.

Instructional designers use generative tools as practical workflow partners rather than replacements. Common tasks include resource alignment checks that flag disconnects between readings, activities and assessments before subject-matter experts spend time rewriting content. Designers also prompt models to draft formative assessments, complete with distractors and feedback, and to produce framing texts that stitch together module content. There are more technical uses too, like stylometry to maintain a consistent training voice across programs, and using models to quickly get up to speed on new subject areas so designers can focus on pedagogy instead of initial research.

Content developers find value in closed, on-brand sandboxes and evolving template libraries. Feeding internal style guides into IT-managed chat systems centralizes brand voice and protects IP, while snippet libraries reduce repetitive copywork. Reusable design templates democratize production and let teams meet competing deadlines with fewer revisions. The article highlights generative video tools such as Synthesia as an example of how motion and template-based animation can be added by resource-strapped teams, then proofed by visual designers to ensure brand consistency.

The authors also push back on hype. Generative tools are disruptive, they say, but historical analogies to the printing press and the loom remind us that technology often scales skill rather than obliterate it. Generative Artificial Intelligence will not miraculously revolutionize every role, nor should it be relied on to produce flawless work. Used selectively, these tools reduce friction, accelerate early drafts and free creative professionals to pursue higher-value instructional strategy and design.

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