AI in Corporate Training: A Revolution Gone Wrong

AI is Flooding L&D with Junk Learning – It’s Killing Skill Development!

AI was supposed to transform corporate learning. It was supposed to personalize education, enhance skill-building, and create more competent workers. Instead, it has fueled a race to the bottom.

In the rush to cut costs, cut corners, and cut workers, companies have embraced AI-generated training that is hollow, superficial, and ineffective. Instead of elevating skill development, AI is being used to mass-produce low-quality courses prioritizing speed over substance.

The Future of Learning Should Look Like This:

AI-powered training should be a rigorous, interactive experience, not a content factory. Imagine a system where AI actively challenges learners, forcing them to engage deeply with material rather than just clicking through slides.

• “Why do you think that’s the right answer?”

• “What real-world evidence supports your choice?”

• “How would your reasoning change if this variable shifted?”

This Socratic method of AI-driven learning could embed critical thinking, problem-solving, and adaptability into every lesson. AI should be a thinking partner, guiding professionals through real growth—not just an automated content dump.

But That’s NOT What’s Happening Right Now.

Instead, AI is being used to flood the learning and development (L&D) industry with garbage.

Corporate training should be about proving competency, not just consuming content. But AI-generated courses are a joke.

A recent study by Davis, Evans, and Foster (2024) found that while AI-driven learning paths can enhance training when done right, the overwhelming trend is toward AI-generated “course factories” that emphasize scale over depth. (Davis et al., 2024, ResearchGate)

What Does This Look Like?

For instance, I recently took a Six Sigma White Belt course through an AI-powered platform.

• What I expected: A structured, hands-on course with real-world applications.

• What I got: A dull, AI-generated slideshow with zero depth, zero interaction, and zero value.

I already use data analysis, statistical modeling, and learning trend identification. But instead of recognizing my experience and skipping redundant material, the course forced me through the same generic slides everyone else got. This is the problem with the AI course factory. Companies use AI to create thousands of fast, cheap courses that measure completion rates instead of competency.

The 5 Biggest Failures of AI-Generated Learning

🚩 No Pre-Assessment = Wasted Time

AI-driven training doesn’t adjust to learners’ skill levels. It forces professionals to waste time on irrelevant content instead of accelerating their learning.

🚩 AI Content is Superficial = Wikipedia Lessons

Many AI-generated courses feel like Wikipedia dumps—all information, no teaching. AI compiles data but doesn’t explain, demonstrate, or challenge learners. (Harris et al., 2024, ResearchGate)

🚩 No Real-World Application = No Transferable Skills

AI-generated courses lack exercises, case studies, and practical challenges. Research shows that people learn best when applying skills to real-world scenarios. (Fosu et al., 2024, ResearchGate)

🚩 Completion Over Competency = Worthless Certifications

Too many companies measure training success by how many people finish a course, not by whether they can apply what they learned. This results in a workforce full of credentialed but unskilled employees. (Vishvapujita et al., 2024, ResearchGate)

🚩 AI Bias & No Quality Control = Inaccurate Information

AI-generated content is often inaccurate, biased, or misleading—and there’s no one validating it. Poor AI training could lead to misinformation, bad decisions, and compliance failures in regulated industries. (Bathala et al., 2024, ResearchGate)

AI Should Prove Competency—Not Replace It

The Problem: No One Is Held Accountable for What They "Learn"

Right now, AI-generated courses give people credentials without proof of ability. There’s no accountability, no validation—just a digital badge.

The Solution: AI-Driven, Data-Backed Performance Assessments

Training should be like a driver’s license renewal.

• Annual skill validation – Employees should prove they can still do their job, not just once but yearly.

• Data-driven skill assessments – AI should evaluate actual performance, not just quiz answers.

• Job simulations & real-world tasks – AI should generate custom assessments reflecting workplace challenges.

• No more arbitrary “observations” – AI-driven data should measure competency based on hard evidence, not subjective opinions.

The Future of AI in L&D: Smarter, Not Cheaper

AI should not be a shortcut for mass-producing content. It should be a tool for proving, strengthening, and verifying skills.

For L&D leaders investing in AI-powered courses, ask yourself:

• Would you take this course and feel confident applying the skill?

• Does it test real-world ability or just provide information?

• Would you trust an employee who learned from this system?

If the answer is no, then fix the system.

AI Can Elevate Learning—But Only If We Hold It Accountable

AI in learning is at a crossroads. We have the power to demand better. We can let AI continue to flood the market with subpar training or push for higher standards and better AI-driven learning solutions. The choice is ours.

Have you taken an AI-generated course that felt like a waste of time? Let’s talk in the comments.

About the Author

Beth Pennington is an instructional designer, learning strategist, and AI enthusiast. With extensive experience creating transformative leadership and educational experiences, Beth specializes in helping professionals upskill, adapt, and thrive in today’s rapidly evolving workplace. She is available as a consultant to design custom, capacity-driven learning experiences on a contract basis.

Beth regularly shares insightful newsletters, practical tools, and thought leadership to empower professionals and organizations. Connect with Beth through her portfolio, follow her insights on LinkedIn, or support her work with a coffee.

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• Bathala, Naresh Kumar. (2025). IMPACT OF ARTIFICIAL INTELLIGENCE TOOLS ON JOB SATISFACTION OF SOFTWARE EMPLOYEES. 

• Davis, J., Evans, R., & Foster, D. (2024). Personalized Learning Paths: How AI is Transforming Employee Training.

• Fosu, C., Daniel, O., & Amoateng, S. S. (2024). The Role of AI in Transforming Construction Innovation and Enhancing Safety Standards in Ghana.

• James, Charles. (2025). Personalized Learning Paths: How AI is Transforming Employee Training. 

• Karibeeran, Sathyamurthi. (2025). AI-Driven human resource management: Enhancing talent acquisition, employee relations, and workforce development. International Journal of Research in Management. 7. 320-327. 10.33545/26648792.2025.v7.i1d.294.