Streamline employee learning: AI prompts for L&D leaders

Most organizations are already using AI to improve their tech skill development efforts in some way. 

According to the 2025 Tech Skills Report, more than half (51%) are using it to automate training administration, like reminders, scheduling, and progress tracking. A good number are also using it to recommend skills to learn (45%), personalize learning paths (43%), and identify relevant content or training resources (43%).

There’s no shortage of ways to use AI for tech skill development, and working with an AI assistant is only one of them. In this article, you’ll discover various AI prompts you can use to personalize learning at scale, close skills gaps, and make your life easier.

Before we dive in, let’s cover some prerequisites and disclaimers.

If you’re unfamiliar with generative AI, prompt engineering, or AI assistants, we recommend learning the basics in these Generative AI Foundations and Prompt Engineering learning paths.

In the following scenarios, we use Pluralsight Iris, our AI learning assistant. There are benefits to using an AI assistant embedded within your learning system, but you can also use tools like ChatGPT, Claude, and Gemini.

While an AI learning assistant can be a helpful partner, you can’t trust it with everything.

If you're using tools like ChatGPT or Claude, use your organization’s private LLM instance. If you have to use public chatbots, don’t share sensitive, proprietary, or personally identifiable information.

And when you get an output, be sure to verify it before running with it. Even with well-crafted prompts and best practices, AI can hallucinate and make mistakes.

Prompt engineering delivers the most useful results when you set clear expectations and constraints. Before using AI prompts for learning and development, it can be helpful to define the following information for LLMs:

• Role: What persona should the chatbot take on?
• Goal: What do you want the chatbot to do? 
• Audience: Who will ultimately use the AI’s output?

If you put all of these elements together at the most simplistic level, you might end up with something like this:

Act as a ROLE. Your job is to GOAL for AUDIENCE.

Example: Act as an L&D manager for a mid-size financial services company that wants to leverage generative AI. Your job is to create a 30-day generative AI learning plan for business professionals or employees in non-technical roles.

Tip: You don’t have to type everything. You can copy and paste information or upload existing files. Just be careful not to share sensitive data.

Learning platforms contain thousands of courses and learning experiences. Generative AI can surface the most relevant content for your people and learning goals so you spend less time sifting through extensive libraries, and more time on actual strategy and execution.

These prompts will help you identify relevant courses for your needs. Copy, paste, and tweak to suit your organization’s needs and goals. 

• Your job is to upskill entry-level software developers in Python. Identify the five most important courses and labs for this topic.

• Create a 30-day generative AI learning plan for business professionals or employees in non-technical roles. Identify the 5 most important topics they should learn. Then, select a mixture of courses, labs, and projects to augment their learning.

Tip: Is the AI assistant sharing courses or labs that don’t exist? Try adding the statement, “Cite real sources and courses. Do not make them up.” to your prompt.

Personalized learning paths compile all of the resources someone needs to learn a certain skill. These learning journeys are tailored to someone’s role, experience, and/or goals.

These prompts will help you build custom learning paths at scale. Copy, paste, and tweak to suit your organization’s needs and goals. 

• Create a personalized learning path for a developer. It should give them the skills they need to build AI agents for Kubernetes. The total learning path time should be no more than 8 hours.

• Develop a personalized learning path for a junior cloud security analyst who wants to become a cloud security architect.

• Create a personalized learning path for data analytics, including 3 different difficulty levels to progress through. 

Learn more about using AI to create personalized learning paths.

Quizzes and quick knowledge checks can help learners validate their skills, uncover topics to revisit, and reinforce their knowledge. 

Use these prompts to create simple learner quizzes for different topics. Copy, paste, and tweak to suit your organization’s needs and goals. 

• Create a 5-question quiz with multiple choice response options to assess learners on AWS cloud networking. Provide the correct answers separately.

• Create a workplace scenario related to cloud cost optimization and develop 3–5 questions that ask employees to make decisions based on the scenario.

• Create a micro-lesson on data analytics. It should be no longer than 5 minutes and include a knowledge check question.

Developing comprehensive learning plans for multiple teams and departments can involve a lot of moving parts. An AI assistant can give you a starting point so you don’t have to create everything from scratch. 

These prompts can help you develop learning plans for different needs. Copy, paste, and tweak to suit your organization’s needs and goals. 

• Develop a cross-departmental upskilling plan for generative AI literacy. It should take each department’s goals into account.

• Develop a 30-day cloud computing learning plan for cloud engineers to support cloud transformation and adoption of a multi-cloud strategy that uses both AWS and Azure.

• Generate a 3-month plan to drive continuous learning engagement for a large healthcare company. They’re going through a digital transformation to harness the power of generative AI.

Which skills are most critical? These prompts can help you prioritize the right skills and align training with organizational outcomes.

Copy, paste, and tweak these AI prompts for learning and development to suit your organization’s needs and goals.

• Our team has a goal to reduce mean time to respond by 10%. Identify the skills needed to achieve this goal.

• Look at these business goals and determine the skills needed to achieve them. 

• Analyze this job description and determine the most important skills someone needs to be successful in this role. Identify training materials that will help them build this knowledge.

• Look at the list of our team’s skill assessment scores and determine where we have skills gaps. For each skills gap identified, suggest one course and one lab to fill the gap.

Generative AI can be a helpful tool if you know how to use it. LLMs can’t replace your L&D expertise or the unique knowledge you hold about your organization, but they can be handy assistants that help you become more productive and strategic.

Looking for more tech upskilling inspiration? Get the Tech Upskilling Playbook for strategies to close skills gaps and help your teams deliver faster.