You’d be hard-pressed to find anyone who would deny the potential of AI in learning and development. 

You might also find it hard to find someone who can articulate exactly how that potential impacts learners. 

This article discusses how artificial intelligence helps organizations deliver more compelling, dynamic, and personalized training at scale. 

Key Takeaways

• Artificial intelligence has fundamentally changed how we learn.
• Personalization is the core of AI-driven learning, making training both more effective and more accessible.
• The benefits of incorporating AI into employee training include increased engagement, dynamic content, and more cost-effective delivery.
• It’s important to understand both the basic functionality and limitations of AI before using it for training.

Human Intuition Meets Machine Intelligence

It’s no secret that personalized learning is non-negotiable for software companies. However, it can be challenging to deliver personalization at scale. Traditionally, instructors had either to severely limit themselves or settle for templated materials.

Generative AI has changed that. 

Instead of relying on a one-size-fits-all approach, organizations can now automatically evaluate each learner’s strengths, weaknesses, and professional background. By combining this knowledge with behavioral analytics, they can then deliver training that’s tailored to what an employee knows, how they learn, and what they struggle with. 

If you need an example, picture a SaaS company that just released a cybersecurity-focused product. It needs to train both its security team and its sales engineers on how the product works. While the core content of that training remains the same, the focus is vastly different for each group:

• Security professionals would likely focus entirely on the product’s features, requiring very little in the way of cyber education.
• Sales engineers would need to understand the product’s core features while also mapping them to cybersecurity pain points and best practices.

Even within each department, there’s bound to be some variance. A fresh hire in the company’s security operations center, for example, will probably appreciate a refresher a great deal more than a veteran analyst. Similarly, a sales engineer with a background in cybersecurity wouldn’t need as much coaching as their colleagues. 

So how does AI fit into all this? What are the advantages of using AI to deliver personalized learning as opposed to relying on a more traditional approach? 

Simply put: efficiency.

Rather than tailoring content to each user group, instructional designers can produce a single course and then leverage AI to deliver the most relevant parts to each employee. In addition to considerably reducing training overhead, this streamlines both knowledge and skill acquisition. 

In other words, the technology makes L&D programs smarter, better, and faster. 

The DNA of an AI-Driven Learning Experience

Having explored how AI can enhance employee learning and development, it’s time to talk about how. It all comes down to a few core attributes of the technology: 

• High-volume data analysis: even relatively simple AI models have the capacity to ingest and produce insights out of a massive quantity of information — far more than any human analyst.  
• Real-time adaptation: continuously feeding data on performance and engagement to the AI allows it to dynamically adjust each learner’s experience as they progress. The AI can also provide learners with immediate feedback. 
• Ongoing improvement: provided an organization has the right guardrails in place to prevent issues like bias and hallucination, its model will become progressively more accurate and effective. 
• Accessible intelligence: training-focused AI models leverage natural language processing (NLP), allowing them to simultaneously analyze course content and respond to queries from both participants and instructors.
• Proactive learning: through predictive analytics, AI can identify the potential roadblocks, bottlenecks, and quit points in each learner’s journey. An organization can then use those predictions to adjust its training, ensuring the best possible learning outcomes.  

The most exciting thing about the feature list above is that it represents the current baseline. Moving forward, artificial intelligence will only grow more sophisticated. That said, it’s essential to remember that the technology isn’t perfect — and that deploying it carelessly can result in wasted time and resources.

Best Practices for Delivering AI-Powered Training

You likely already understand both general best practices for creating effective virtual training and the key elements of an effective training environment. 

Now the focus is on unlocking the full potential of AI. Here are a few best practices to keep in mind.

Recognize That AI Has Limits

AI is revolutionary and incredibly disruptive. At the same time, it’s not a silver bullet for all your L&D needs.

AI isn’t on the same level as a human being when it comes to practical expertise. It can certainly learn to recognize the patterns in its training data. But knowing that an employee with a security background prefers training focused on product features rather than general cyber knowledge  isn’t the same thing as understanding the day-to-day application of that knowledge, especially when human error is a factor.  

AI also lacks emotional intelligence, interpersonal skills, and even a baseline understanding of ethics. It simply does what it’s been trained to do, for better or for worse. 

Don’t Try to Train Your Own Model Right Away

For organizations with greater AI maturity, an internally trained LLM is a game-changer. For everyone else, though? It can be more of a hindrance than a help. 

Unless you operate in an extremely specialized field, there’s bound to be at least a few AI tools that can be adapted to your training. There are plenty of vendors who will actively help you with the adaptation.  

Design AI-Friendly Training

You cannot simply plug existing training content into an adaptive learning platform and expect it to start personalizing. You need to design content specifically for AI. The good news is that the process isn’t all that dissimilar to developing content for microlearning — so chances are, you’re already familiar: 

• Keep modules short, with each one focused on a single concept or skill.
• Where possible, structure modules so they can be delivered independently of one another and in any order.
• Incorporate varied, interactive formats alongside activities broadly tailored to specific backgrounds.
• Embed frequent learner assessments into your training so the AI can collect data for additional personalization.

Clean Your Data

What does data hygiene have to do with artificial intelligence? The short answer is everything. Even the most sophisticated AI models are nothing without training data. 

As a general rule, you’ll want to make sure you complete the following steps before you start using AI, even if you’re running a pre-trained model: 

• Establish a single source of truth for all relevant training data.
• Ensure you have a process in place to address redundancies, informational gaps, and errors.
• Consult with a compliance specialist on the matter of AI data privacy and security.
• Continually review your data to guarantee quality.

Learn How to Write a Prompt

You’ve probably heard the phrase “prompt engineering” before. Don’t let the name intimidate you. It’s ultimately just jargon for the different ways you can provide an AI model with context. 

Rather than focusing on different engineering techniques, we recommend simply writing each prompt to be as concise as possible while still covering every detail of what you want the model to do. 

Making AI in L&D Work for Your Customer Training

AI is no longer an emerging idea in corporate learning — it’s a core capability. But adopting it isn’t as simple as flipping a switch. To see real value, you need a thoughtful strategy that aligns AI’s strengths with your business goals, your learners’ needs, and the content you deliver.

That means choosing the right tools, designing for adaptability, and building a data foundation that fuels smarter personalization. It also means understanding where AI fits in — and where human insight still matters most.

With the right setup, AI can help you scale personalization, reduce time to competency, and make your learning programs measurably more effective. But none of those benefits happen by accident. They’re the result of deliberate choices and continuous iteration.

Take the Next Step Toward Smarter Training

AI-powered learning doesn’t stop with internal teams. 

The same capabilities, real-time adaptation, personalized experiences, and scalable delivery can transform how you educate your customers.

Explore how leading organizations are using AI to boost engagement, reduce churn, and drive product adoption through smarter customer training programs.

Check out our webinar Artificial Intelligence: The New Imperative for Advancing Customer Education to learn more.

And if you’re ready to see what this looks like in action, book a demo to see how CloudShare is transforming customer training.

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