The ROI of AI in Learning and Development

Recently, I spoke with a finance professional who works for a major investment bank. He shared that corporations are starting to achieve significant efficiencies by integrating AI into a variety of tasks, ultimately boosting their profit margins. Since he spends more time with corporate balance sheets than I do, I took his observation seriously.

This conversation led me to reflect on the current state of Learning and Development (L&D). For decades, it's been standard wisdom that developing one finished hour of traditional eLearning content requires on average about 100 hours of work—sometimes as much as 300 hours for a particularly robust course. Despite the emergence of new technologies and tools, this number hasn’t changed significantly over time.

Now, a key question emerges: Can the array of new AI tools—so numerous they’re almost impossible to keep track of—help us achieve notable gains in efficiency and return on investment (ROI) in L&D?

Here is a partial list of AI-native tools (not exhaustive, and not an endorsement) that are reshaping the field. It’s worth noting that most legacy learning platforms have incorporated some AI, but these tools are built with AI at their core:

·         Learning Management Systems/LXPs: LearnWorlds, Sana

·         Authoring Tools: Courseai, Mindsmith

·         Research: Perplexity

·         Podcasts: Google NotebookLM

·         Writing/Idea Creation: Claude, ChatGPT, Gemini

·         Slide Creation: Gamma, Slides AI

·         Text to Audio: ElevenLabs, Speechify

·         Text to Video: Synthesia, EaseMate

·         Graphics, Charts, Visuals: Napkin

·         Avatar Creation: Synthesia, Collossyan

·         Study Guides: Google NotebookLM

These tools can now accomplish in minutes tasks that once took days or weeks—and often required hiring a variety of domain experts and specialists. If it cost $50,000 to develop a course five years ago, shouldn't those costs now be significantly lower?

I decided to pose this question (where else?) to ChatGPT. Here’s the prompt and its response:

Prompt:

I am an expert instructional designer. In 2020 I developed an online course for a pharmaceutical company to train their sales representatives on a new product. It took me 20 days to create this course. If I developed the same course today using AI-enabled learning tools, how long should it take me?

ChatGPT’s response:

Great question—one that highlights the profound changes in instructional design and eLearning production workflows since 2020 due to AI. If you were to develop the same course today using AI-powered learning tools, your time could be reduced by 40%–70%, depending on your level of automation and reuse. Here’s what that might look like:

Estimated Time Today: 6 to 12 Days

Compared to 20 days in 2020, here’s where the time savings occur:

Phase	2020 (Manual)	2025 (AI-Enhanced)	Time Savings	How AI Helps
Analysis & Research	3 days	1 day	66%	AI instantly summarizes medical journals, product data, and competitor materials.
Design	4 days	2 days	50%	AI drafts learning objectives, maps content to outcomes, and suggests interactions.
Storyboarding	4 days	1–2 days	50–75%	Tools like ChatGPT or Synthesia AI co-create storyboards or scripts.
Content Development	6 days	2–3 days	50–70%	Rapid asset creation with platforms such as Articulate Rise, Vyond, Pictory, or D-ID for voice and animation.
Review & Revisions	2 days	1 day	50%	AI automates QA checks, proofreading, and version comparisons.
Final QA & Deployment	1 day	1 day	—	Minimal change unless using automated testing.

It’s fair to say people might debate these estimates, but it’s clear that the L&D field is entering a new era—one where instructional designers can increase their efficiency by 30% or more.

For clients, this means that expecting to pay less for an equivalent course today compared with 2020 is reasonable. For instructional designers, while your expertise is still needed as the human-in-the-loop, your role is evolving rapidly in this changing landscape.