A team of smart, skilled, and dedicated employees is the backbone of every successful company. Their collective effort turns your vision for the business into reality.
So, you must hone their skills with advanced L&D programmes. It keeps them fluent in current industry norms and improves their expertise — all contributing to innovation and the company’s success.
However, the same old employee manuals, generic handbooks, and other traditional L&D methods aren’t enough for personalised employee training.
The solution? AI-powered software. Since they are adaptive and time-efficient, you can:
- Offer custom training to suit different learning patterns, experiences, and proficiency levels
- Deliver real-time feedback for faster improvements
- Identify and fill skill gaps quickly and accurately with internal talent.
In today’s article, we show you the top 7 ways of using AI to advance your L&D programme.
7 ways to use AI for employee learning and development
Here’s how you can implement AI in training to build a highly-skilled and agile workforce:
PersonaliSe learning paths for employees
There is no specific method of learning. Some of us retain information through textual resources. Others often learn better through audio-visual experiences. You must meet their learning preferences if you want your employees to absorb all the knowledge in your training session.
Plus, each employee has different proficiency and expertise levels in different fields. So, a one-size-fits-all approach won’t really work, right?
Personalised L&D programmes engage employees because the method is relevant to their experience and learning preferences. You can customise the learning paths for each employee and upskill your team with personalised, on-demand training relevant to their journey. It ensures they learn new things and are not kept behind with generic training modules.
AI assistants can scan employee information and build learning profiles. The AI algorithm can recommend fields, courses, and personalised training suggestions.
You can invest in an enterprise LMS platform for convenient, personalised training delivery. It streamlines and automates learning paths, ensuring employees get the exact resources and support fit for their existing skills and learning patterns.
Use AI-powered chatbots for on-demand support
Suppose an employee is trying to work out a newly-learned programme. They may get stuck somewhere and seek assistance. But superiors don’t always have the time to provide instant support. The employee’s workflow gets hampered, impacting engagement and productivity.
You can deploy AI-powered chatbots to solve this problem. They can hold human-like conversations, offer round-the-clock support, and answer employee queries instantly. Your team can access any module, guidelines, or strategies they need to practice and apply their skills.
Plus, since they don’t have to run to their mentor or supervisor with every little question, the process is quite time-efficient, too.
Automate skills gap analysis and training recommendations
You may think all is well with your company’s workflow. However unforeseen challenges often reveal a different picture. You may notice that while your employees work hard, your company has a skill gap. Had you noticed them earlier, targeted training could have prepared your team to tackle sudden problems.
That’s why frequent skill-gap analysis is important. You can run AI algorithms across employee profiles, measure performance, and assess where they can improve. This helps develop targeted training interventions to deliver continuous and relevant learning.
A report also pointed out that 55% of employees believe that more training is necessary for them to do a better job. 76% also said they would likely stay with a company that offers continuous learning.
For example, Johnson & Johnson identified 41 future-ready skills and implemented a large language model to assess their tech team on each using a 0-5 scale. The company also asked employees to rate their skills on the same scale.
This helped them understand where their workers could use additional training. Based on their findings, the company developed J&J Learn, a centralised learning system where employees and contractors gather the necessary skills to meet the company’s needs.
Enhance micro-learning with AI-driven content curation
What good will your overtly technical and jargon-filled training resources do if the employee doesn’t absorb the knowledge? Suppose the employee isn’t proficient in that specific field. Such complex modules will overwhelm and disengage the worker, rendering your L&D programme ineffective.
However, if you break down complex topics into clear and concise sources of information, employees can understand and retain the knowledge much more efficiently. This process is called microlearning — and AI tools can help you.
You can run ML algorithms to understand the employee’s proficiency level and learning patterns. Then, the system can generate content that dissects each topic into smaller chunks of comprehensive information.
For example, you can curate audio-visual content along with textual resources for employees who are visual learners. They can absorb the knowledge through videos and infographics and use the text-based module as a reference to deepen their understanding.
Blend real-life context into the micro-learning process to improve knowledge retention. For example, you can suggest best practices for personal branding on LinkedIn in the context of an employee’s profile. Or suppose they recently handled a project. Your AI system can use their performance as an example and break down the steps to an alternative method of operation.
You can use AI to gamify each microlearning level with points, badges, and leaderboards. Think Duolingo’s step-based learning but for your corporate training programme. Plus, the AI system can analyse performance and upskilling levels and enhance the difficulty levels accordingly.
Leverage AI for predictive learning analytics
Organisations often fail to deliver tangible results even after investing substantial funds in their L&D programmes. One reason is that they rely on retrospect rather than focusing on future needs. This prevents the workforce from being agile and handling changing customer and industry needs.
Solution? Tap into AI-driven predictive analytics to:
- Gauge the most crucial skills required in your industry in the upcoming years (to design L&D strategies that make employees future-ready)
- Track changes in customer preferences and predict demands (to prepare employees to meet them)
- Forecast when specific learners may face difficulties in applying their knowledge (to offer timely training interventions)
You can also enhance skill-gap assessment with predictive skill supply. This will help create a benchmark in skill positioning, allocate an accurate training budget, and curate targeted learning modules on skills that actually matter.
For example, Tanya Moore, a partner with IBM’s Talent and Transformation organisation, and Eric Bokelberg, an Associate Partner in IBM’s Talent and Transformation Center of Competency, shared how the company uses predictive analytics for employees.
They say that IBM has an extensive AI-based training strategy powered by predictive analytics. They use machine learning algorithms to predict skill supply and upskill teams accordingly. Based on those insights, they forecast skill gaps and plan internal mobility and peer-to-peer coaching opportunities.
However, since you are profiling the employee’s learning patterns, the AI system will also process sensitive employee information. To prevent data leaks and potential compliance issues, it’s crucial to implement robust security practices, such as AppSec, to protect the integrity of your data and systems throughout the AI process.
Provide real-time feedback and performance insights
A 2024 Gallup Report noted that managers can boost engagement by setting relevant goals, delivering regular and meaningful feedback, and ensuring accountability. However, as your workforce grows, it becomes increasingly difficult for managers to keep track of each employee manually and deliver individual feedback regularly.
With AI-powered workplace analytics, your managers can measure each employee’s performance in real time. They can see where individual workers excel and where they can improve, paving the way for instant feedback delivery.
You can set up AI assistants on automation to monitor performance and deliver feedback without human intervention. The assessments will be purely objective and impartial, letting employees assess and improve their performance.
Also, managers often harbor unconscious perception biases which can hinder employee recognition. Implementing AI ensures fair recognition, boosting employee retention, engagement, and satisfaction.
Use AI-driven simulations for immersive training
Theoretical training is crucial for foundational knowledge. However, your employees must be confident about implementing the newly acquired skills — and that’s only possible through hands-on experience. Now, since they are still learning that particular skill, they might make mistakes if you let them test it on your operations.
So, how do you allow them immersive training without hampering your workflow? Apply AI-powered virtual reality and simulations. Here, employees can test their readiness in different industry-relevant situations in a safe space.
AI-driven immersive learning is also ideal for virtual training programmes for remote employees. AI algorithms will identify their mistakes and show them exactly what they can do better. This will create a more meaningful and engaging learning environment.
Let’s say you run a custom apparel business and want your team to learn to use print-on-demand tools in real scenarios. You can create simulations where they can practice using the software to complete demo projects.
For example, Bank of America offers “The Academy”, an AI-driven training platform for immersive learning. Here, employees can access on-demand personalised training and master acquired skills in VR simulations.
Conclusion
AI can’t replicate the nuanced abilities your employees can bring to the table. However, it can improve employee engagement with smoother, more efficient, and more effective training methods.
With AI-powered training systems, you can personalise learning paths for better retention and engagement. NLP models can facilitate real-time interactions and solve employee queries through chatbots. You can gamify lessons to create healthy competition encourage progress and offer immersive learning with VR and simulations.
Plus, predictive analytics can show you the most required skills for your company to stay competitive in the long run. You can design microlearning materials and instant feedback mechanisms to fill skill gaps.
Finally, don’t forget to take proactive data security measures to prevent data breaches. Use AI responsibly to enhance employee training programmes, and your workforce will drive you to your goals no matter the industry’s challenges.
Author: Mehdi Hussen – Head of Marketing, ZoomShift
Photo credit: StockCake
