
Finding The Right AI Training As An L&D Pro
From automating tasks to helping us make smarter decisions, AI tools are becoming must-haves in all industries. As more companies begin integrating AI, the need for AI literacy is growing fast. This is the job for no one but your L&D team, which must now create effective AI training programs for the whole workforce, including leaders and upper management.
Let's explore AI training in the workplace. It doesn't mean one thing. For some, it might involve understanding how AI tools like ChatGPT can help with content creation or support customer service. For others, it could mean building technical skills like Machine Learning or AI prompt engineering. Overall, AI training's main goal is to help people become AI-aware, confident, and capable of using new tools responsibly. AI training can take many forms. It can help people improve their skills in their current jobs or train them for new roles. For example, HR teams might learn to use AI for recruitment, marketing teams for campaign personalization, IT staff for automation or AI security measures, and customer support for learning to use AI chatbots. Regardless of the department, the goal is to use AI to work more efficiently and make better decisions.
Therefore, AI training focuses on giving people digital skills and the confidence to use AI to boost productivity. This works best when the training matches your goals, though. Just placing people in generic courses won't work. The most effective AI training aligns with your company's objectives, your learners' needs, and the pace at which your organization is growing. This is why your L&D team needs to lead the way as organizations change. This includes helping employees adjust to new tools and promoting digital awareness. However, finding good AI training courses is challenging. Some of them are too technical, others are too general, and many do not meet your workplace needs. That's why it's crucial to find the right AI training programs.
This article is here to help with exactly that. You'll find practical tips on what to look for in an AI course and how to avoid common mistakes. Whether you're exploring AI training for the first time or changing your current strategy, this is the place for you.
5 Practical Tips That Will Help L&D Pros Deliver The Best AI Training
1. Assess Skill Levels And Goals
When it comes to AI training, one of the biggest mistakes L&D teams can make is choosing courses without first understanding who they're training and what those people actually need. That's why the first and most important step is to assess your learners' current skill levels and define clear learning goals. What does this mean? In most companies, learners will have different levels of understanding of AI. Some may not know what AI means, while others might have used basic tools like Gemini. If you provide the same training to everyone, it will be frustrating. A generic approach won't work for them. So, you'd better start by segmenting your audience. You might have:
- AI beginners who need to understand the basics, such as what AI is and what it can do.
- People who might already use AI tools but want to learn more.
- Tech-savvy people, who are ready for advanced content, maybe even basic Machine Learning or AI prompt engineering.
This is strongly connected to learning goals. What do you want learners to gain from training on AI tools? Do you want them to feel comfortable using these tools? Should they learn to apply AI to specific tasks? Or do you want them to feel confident to experiment? Setting clear goals helps you choose the right courses later and allows you to evaluate the effectiveness of AI training.
2. Prioritize Practical Content
AI's technical terms can seem intimidating and may repel people from wanting to train on AI literacy anyway. That's why a practical approach to AI training works best. Instead of choosing the most complex course, stick to what's useful for your learners. If they finish the course feeling confused about how it relates to their roles, the training isn't successful. The best AI training explains not just how AI works but also how people can use it in their jobs right away. For instance, if you're training a marketing team, a course full of Machine Learning details might be too much. Instead, a module showing how to use AI for customer insights would be much more relevant.
Remember that people learn better when they can connect information to their current work. So, AI training with use cases and examples boosts the learners' understanding and encourages them to use what they learn. Plus, practical courses are more interactive. Look for training that includes scenarios, hands-on tool walkthroughs, or exercises where learners can try AI features themselves. Learning by doing helps people remember more than lectures. A good practical AI training course will also relate to your industry. This is because AI works differently in different sectors. When choosing training options, look for those that focus on your industry or allow customization.
3. Evaluate Course Providers
When choosing an AI training course, it's crucial to consider who is offering the course. You should keep in mind that not every provider offers what your team needs. Therefore, carefully evaluating course providers can save you time and money. First, check the provider's credibility. Trusted platforms like Coursera, edX, and LinkedIn Learning host courses from top universities and tech companies, meaning you'll most likely get good-quality content. Next, look at learner reviews and ratings. But don't just focus on the star rating, because you also want to read the comments. Are learners completing the course? Can they apply what they've learned at work?
Also, check if the course includes hands-on learning. As we mentioned above, the best AI training goes beyond theory and helps learners practice what they learn. So, look for courses that offer real-life case studies, exercises, or projects. And don't forget about support. Does the provider offer mentors, discussion forums, or office hours? These resources can be very helpful, especially for newcomers to AI who may need more assistance. Lastly, consider your organization's needs. Is the provider flexible for team or company-wide training? Will they allow customization? These details are important and play a role in your team's learning process.
4. Find Courses That Cover AI Ethics
AI can increase productivity, automate tasks, and speed up data-driven decisions. However, this comes with responsibilities. So, in AI training, learning about the ethical use of AI should be one of your priorities. Even advanced AI systems can create problems if not used carefully. Issues like biased algorithms, privacy concerns, and a lack of transparency can lead to harmful results. For example, a recruitment tool might exclude qualified candidates due to biased data, such as gender, color, and even name if it's foreign.
Since you can't afford to face these issues, choosing AI training that includes modules on responsible AI use is important. Look for courses that cover topics like algorithmic bias, data privacy, fairness, accountability, and explainability. Even if employees won't create AI models from scratch, they should still understand the ethical risks and how to spot them in the tools they use. Customers, clients, and team members are increasingly aware of these issues, too, and they want to see that companies use AI fairly and transparently. Hence, training employees on ethical AI practices helps build trust and shows that your organization takes these responsibilities seriously.
5. Choose Flexible Delivery Methods
When teaching AI, how you deliver the training is just as important as the content. A major mistake in L&D is choosing a good course that only a few people finish. Why does this happen? Often, the format doesn't match the learners' needs or schedules. To fit different needs, some of your options are self-paced courses, where learners complete the material at their own pace; Instructor-Led Training, which is live and scheduled; blended learning that mixes both; and cohort-based learning, where groups of learners work together with deadlines and teamwork.
Each method has its benefits. Self-paced learning is ideal for learners who like flexibility, but it may not be suitable for those who need more structure or group interaction. Instructor-Led Training, on the other hand, promotes engagement and allows for active participation. This format can help clarify complex AI topics, but scheduling can be a challenge, especially for remote or global teams. Now, blended learning often balances the freedom of self-paced study with important live interactions, which tends to improve completion and retention rates. Lastly, cohort-based learning is especially helpful for cross-functional teams looking to understand how AI will be used throughout the organization.
Conclusion
AI training is not just about learning tools. It is also about helping people think smarter, work better, and feel confident. It's important for L&D teams to understand what people really need, rather than just what is popular. The best AI courses empower learners without overwhelming them. So, how do you start? First, check your team's readiness for AI. Then, create a learning plan that's all about growth. When training is relevant and supportive, everyone benefits.