The Hidden Risks of Using AI to Create Learning Content

AI can create learning content at lightning speed, but faster doesn’t always mean better. From generic courses to sneaky inaccuracies, there’s more to consider than simply hitting "generate." Let AI do the heavy lifting, but keep human expertise in the driver’s seat. After all, we want better learning, not just more content collecting digital dust.

Hazie Halim

10/22/20265 min read

Let’s start with a confession. If you’re creating learning content in 2026 and you’re not using AI in some capacity, you’re probably working much harder than you need to. AI can draft scripts, generate quizzes, create learning objectives, suggest activities, write assessments, build scenarios, summarize research, even generate voiceovers and visuals.

For learning teams facing increasing demands and limited resources, it can feel like discovering a secret productivity superpower. And to be fair, it is.

But like most superpowers, it comes with responsibility.

Because while the conversation around AI often focuses on speed, efficiency, and cost savings, far less attention is being paid to the hidden risks that emerge when AI starts creating learning content at scale. The danger isn’t that AI will replace instructional designers. The danger is believing it already can.

The Content Creation Problem Has Been Solved

For years, one of the biggest challenges in L&D was content production. Creating quality learning experiences took time. Lots of it. Research, storyboarding, writing, reviewing, designing, testing, and publishing.

AI has dramatically reduced many of those barriers. What previously took days can now be done in hours. What previously took weeks can now be drafted in minutes. The bottleneck is no longer content creation. The bottleneck is content quality. And that’s a very different challenge.

Risk #1: Content That Sounds Smart but Says Very Little

One of AI’s greatest strengths is also one of its biggest weaknesses. It is exceptionally good at generating language that sounds convincing. Unfortunately, sounding convincing is not the same as being useful.

Many AI generated learning materials suffer from what might be called “corporate wallpaper syndrome.” The words look impressive. The structure appears professional. Yet learners finish the module and remember almost nothing. Why? Because effective learning isn’t simply about information. It’s about relevance, content, application, and behaviour change.

AI can generate content. It cannot automatically generate meaningful learning experiences. At least not without skilled human guidance.

Risk #2: Generic Learning for Specific Problems

Imagine asking AI to create a course on leadership. You’ll likely receive a perfectly reasonable leadership course. The problem is that your organisation is not a perfectly reasonable generic organisation.

Your managers face unique challenges. Your customers are different. Your business priorities are different. This is where many AI-generated learning experiences fall short. They tend to default towards the average. The middle. The generic. The safest possible answer.

But business challenges are rarely generic. The most impactful learning often addresses specific organisational realities. And that level of contextualisation skill requires human insight.

Risk #3: Inaccuracies That Slip Through

AI has become significantly more reliable. It has not become infallible.

Learning content carries an important responsibility. Employees trust it. Leaders rely on it. Compliance programmes depend on it. Business decisions can be influenced by it. Even small inaccuracies can create problems, particularly in areas such as compliance, legal requirements, health and safety, financial regulations, technical procedures, and industry standards.

The challenge is that AI-generated errors often appear highly confident. They don’t arrive wearing labels. This is why review and validation remain critical. Especially for high-stakes learning content.

Risk #4: Losing the Human Voice

Have you noticed something about AI-generated content? After reading enough of it, everything starts sounding strangely familiar. The same structures, the same phrasing, the same polished but slightly generic tone.

This creates a risk for organisations. Learning content starts losing its personality. It’s culture. It’s authenticity.

Employees connect with stories. Examples. Experiences. Humour. Real-world situations. The best learning often feels like it was created by someone who genuinely understands the audience. Because it was.

AI can support content creation, but organisations should be careful not to automate away the human connection that makes learning memorable.

Risk #5: Faster Content Doesn’t Automatically Mean Better Learning

This may be the biggest misconception surrounding AI in L&D. Faster content production does not automatically translate into better learning outcomes. In fact, the opposite can sometimes happen.

When content becomes easier to create, organisations may unintentionally produce more learning than employees can realistically consume. The result? Content overload. More courses. More modules. More noise.

Employees don’t need more information competing for their attention. They need learning experiences that solve meaningful problems. AI can accelerate production, but strategy must determine what deserves to be produced in the first place.

Risk #6: Intellectual Property and Data Concerns

As organisations increasingly use AI tools to generate content, questions around governance become more important. Questions such as what information is being shared with AI platforms, are confidential documents being used as source material, who owns AI-generated content, how is sensitive data being protected, and are there copyright implications.

These concerns are particularly relevant for organisations operating in regulated industries or handling proprietary information. The technology may be moving quickly. Governance still need to keep pace.

Risk #7: Mistaking Technology for Expertise

Perhaps the greatest risk of all is assuming that AI can replace expertise.

An AI tool can help generate content. It cannot replace instructional design principles. It cannot fully understand organisational culture. It cannot independently identify capability gaps. It cannot determine the most effective learning strategy. Those responsibilities still belong to people.

The organisations seeing the greatest success with AI are not replacing expertise. They’re amplifying it. They use AI as a tool within a well-defined learning strategy rather than treating it as the strategy itself.

How Nixfon Learning Helps Organisations Use AI Responsibly and Effectively

At Nixfon Learning, we believe AI has the potential to transform how organisations design, deliver, and scale learning. But successful AI adoption requires more than technology. It requires strategy, governance, expertise, and a clear understanding of what great learning looks like.

Our team works closely with organisations to help them integrate AI into learning ecosystems responsibly and effectively. We help HR and L&D leaders evaluate opportunities, establish governance frameworks, strengthen learning design practices, and ensure that AI-generated content remains aligned with business objectives and learner needs.

By combining learning strategy, instructional design expertise, content development experience, learning technology consulting, workforce capability planning, and change management support, we help organisations embrace AI without losing sight of the human elements that make learning impactful.

Because the future of learning content isn’t about replacing people with AI. It’s about helping people use AI to create learning experiences that are smarter, more relevant, and ultimately more valuable for the workforce they serve.

And that’s a future worth building.

Till we meet again in the next episode!

About the author

Hazie Halim has more than 15 years of experience in Talent Management Solution and L&D Tech. Her approach has never been about the technology; it has always been about the people in the industry. She understands HR & L&D, she understands the pain and the stress, and she understands the fear and reluctance of system integration drama. Combining these has allowed her to be compassionate when sharing her experience and knowledge during project implementation. She is passionate about making the HR & L&D experts look good in front of their stakeholders. Their win is her win.