Find the right AI training as an L&D professional
From automating tasks to helping you make smarter decisions, AI tools are becoming an essential item in every industry. As more companies begin to integrate AI, the need for AI literacy is growing rapidly. This is not a job for anyone other than the L&D team. This requires creating effective AI training programs for the entire workforce, including leaders and senior management.
Explore AI training at work. That doesn’t mean one thing. For some, it may involve understanding how AI tools like ChatGPT can help you create content or support customer service. For others, it means building technical skills such as machine learning and AI prompt engineering. Overall, the main goal of AI training is to enable people to recognize AI, be confident and responsibly use new tools. AI training can take many forms. It helps people to improve their skills in their current job or train them for new roles. For example, HR teams may 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 department, the goal is to use AI to work more efficiently and make better decisions.
Therefore, AI training focuses on giving people the confidence to use digital skills and AI to increase productivity. However, it works best when training matches your goals. Putting people in a typical course doesn’t work. The most effective AI training is consistent with the company’s goals, learner needs, and the pace at which the organization is growing. This is why L&D teams need to lead the way as organizations change. This includes helping employees adapt to new tools and promote digital awareness. However, finding a great AI training course can be difficult. Some of them are too technical, others are too common, and many do not meet your workplace needs. Therefore, it is important to find the right AI training program.
This article is here to help you do just that. You can find practical tips on what to look for in your 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 to help L&D pros provide the best AI training
1. Evaluate your skill level and goals
When it comes to AI training, one of the biggest mistakes that L&D teams make is choosing a course first without understanding the person they are training and what those people actually need. Therefore, the first and most important step is to assess the current skill level of the learner and define clear learning goals. What does this mean? In most companies, learners have different levels of understanding about AI. Some people don’t know what AI means, while others have used basic tools like Gemini. Providing the same training for everyone will be frustrating. The general approach doesn’t work for them. So it’s better to start by segmenting your audience. You may have:
Beginners of AI need to understand the basics, such as what AI is and what it can do. Those who may already be using AI tools but want to know more. High-tech savvy people ready for advanced content, perhaps basic machine learning and AI prompt engineering.
This is strongly related to learning goals. What do you want learners to gain from training with AI tools? Do you want to feel comfortable using these tools? Should they learn to apply AI to specific tasks? Or do you want them to feel confident in experimenting? Setting clear goals will allow you to select the right course later and assess the effectiveness of your AI training.
2. Prioritize practical content
The technical terminology of AI may seem intimidating and could repel people who want to train AI literacy anyway. Therefore, a practical approach to AI training works best. Instead of choosing the most complex course, stick to what is useful to the learner. If you finish a course where you are confused about how they relate to their role, the training will not be successful. The best AI training explains not only how AI works, but how people can quickly use it at work. For example, if you are training your marketing team, there may be too many courses full of machine learning details. Instead, modules that show how to use AI for customer insights are much more relevant.
Don’t forget that people learn better when they can connect information to their current work. Therefore, AI training in use cases and examples enhances learners’ understanding and encourages them to use what they have learned. Plus, practical courses are more interactive. Look for training that includes scenarios, walkthroughs of hands-on tools, or exercises that allow learners to try and test AI to work on their own. Learning through doing it helps people learn more than just lectures. Excellent practical AI training courses are also relevant to the industry. This is because AI behaves differently in different sectors. When choosing your training options, look for people who will focus on the industry or allow customization.
3. Rate course providers
When choosing an AI training course, it is important to consider who is offering the course. It’s important to remember that not all providers will provide what your team needs. Therefore, careful evaluation of course providers can save you time and money. First, check the reliability of your provider. Trusted platforms like Coursera, Edx and LinkedIn learn hosted courses from top universities and tech companies. This means you’re likely to get good quality content. Next, look at learners’ reviews and ratings. However, I would like to read the comments as well, so please don’t focus solely on star ratings. Have learners completed the course? Can they apply what they learn at work?
Also, check if the course includes hands-on learning. As mentioned above, the best AI training goes beyond theory and helps learners practice what they have learned. So, look for courses that offer real case studies, exercises, or projects. And don’t forget to support us. Does the provider offer mentors, discussion forums, or opening hours? These resources are extremely useful, especially for new AI employees who need more support. Finally, consider the needs of your organization. Are providers flexible in training your entire team? Do they allow customization? These details are important and play a role in the team’s learning process.
4. Find a course that covers AI ethics
AI can increase productivity, automate tasks, and speed up data-driven decisions. However, this comes with responsibility. Therefore, in AI training, learning about the ethical use of AI must be one of your priorities. Even advanced AI systems can cause problems if not used carefully. Issues like biased algorithms, privacy concerns, and lack of transparency can lead to harmful outcomes. For example, recruitment tools may exclude qualified candidates due to biased data such as gender, colour, and even foreign names.
As you cannot afford to face these issues, it is important to choose AI training that includes modules on responsible AI use. Find courses that cover topics such as algorithm bias, data privacy, fairness, accountability, and explanationability. Even if employees don’t create AI models from scratch, they still need to understand ethical risks and how to find them with the tools they use. Customers, clients and team members are also increasingly aware of these issues and want to see companies using AI fairly and transparently. Therefore, employee training on ethical AI practices helps build trust and demonstrates that organizations take these responsibilities seriously.
5. Choose a flexible delivery method
When teaching AI, how you provide training is just as important as content. The big mistake for L&D is to choose a good course that only a few people finish. Why does this happen? In many cases, this format does not match the needs and schedule of learners. For different needs, some of the options are self-paced courses, with learners completing the material at their own pace. Instructor-led training scheduled live. Learning to mix both. Cohort-based learning. Groups of learners work together with deadlines and teamwork.
Each method has its advantages. Self-paced learning is ideal for learners who like flexibility, but may not be suitable for those who need more structures and group interactions. Meanwhile, instructor-led training promotes engagement and enables active participation. This format helps clarify complex AI topics, but scheduling can be a challenge, especially for remote or global teams. Currently, blended learning often balances self-paced research freedom with important live interactions, which tends to improve completion and retention. Finally, cohort-based learning is particularly useful for sensual teams trying to understand how AI is used across the organization.
Conclusion
AI training is more than just learning tools. It also helps people think smarter, work better and feel more confident. It’s important for the L&D team to understand not only what’s popular, but what people really need. The best AI courses empower learners without overwhelming them. So, how do you get started? First, check your AI team’s preparation. Next, create a learning plan for growth. Everyone benefits when training is relevant and supportive.
