Generative AI for Learning and Development: Getting Started

In 2024, organizations spent $401 billion globally on corporate training⁽¹⁾, yet 70% of employees report feeling unprepared for the future of work and seek reskilling or upskilling⁽²⁾. The disconnect isn’t surprising when you consider that most L&D teams are stretched thin—creating personalized, engaging content for thousands of learners while racing to keep pace with rapidly evolving skill requirements is not an easy feat at all. t’s a common challenge that’s pushing many L&D leaders to explore a powerful solution: generative AI. The emergence of generative AI isn’t just another tech trend. It’s promised to be a paradigm shift in how we approach learning and development. According to McKinsey’s 2024 State of AI report⁽³⁾, 65% of organizations surveyed were actively using AI, almost double from the previous year. If we were look at these applications by industry, “professional services” that includes Human Resources, Learning and Development, consulting, research and training, we will discover the biggest increase in adoption and meaningful cost reduction. The potential is enormous: AI can now create customized learning content in minutes, deliver personalized coaching at scale, and generate data-driven insights about learning effectiveness. This comprehensive guide will show you:

• How generative AI is transforming traditional L&D approaches
• Real-world examples of organizations successfully implementing AI-powered learning
• A practical framework for getting started with generative AI in your L&D strategy
• Key considerations and best practices for maximizing impact while managing risks

Whether you’re AI-curious or ready to dive in, you’ll learn how to harness this technology to create more effective, scalable, and personalized learning experiences for your organization.

Understanding Generative AI for Learning and Development

Let’s talk about what happens when artificial intelligence meets the messy, beautiful reality of how people actually learn. Not the sanitized version we see in tech demos, but the real deal – where some days you’re sharp as a tack, and others you can barely remember your coffee order. Generative AI for learning and development isn’t just another buzzword to add to your toolkit. It’s more like having a ridiculously observant teaching assistant who never sleeps and somehow remembers everything about how your team learns best. The kind that notices when someone’s eyes glaze over during technical training and thinks, “Hmm, maybe we should try explaining this differently.” Here’s the thing: While traditional training programs lumber along like cargo ships – massive, slow, and hard to redirect – AI-powered learning dances. It pivots. It adapts. When someone’s struggling with a concept, it doesn’t just repeat the same explanation louder (we’ve all had that teacher, right?). Instead, it reshapes the content, finding new angles until something clicks. How? Check out this conversation with an AI coach to see it live:

But let’s be crystal clear about one thing: This isn’t about replacing human connection with cold algorithms. Rather, it’s about amplifying what makes learning deeply human – curiosity, adaptation, and those wonderful “aha!” moments when knowledge finally sticks. Read further: 7 Easy Ways to Use AI in Learning and Development

Pros & Cons of Generative AI for Learning and Development

Think of it as giving your L&D team superpowers. Not the flying-through-the-air kind (sorry), but the ability to truly meet each learner where they are, when they need it most. But before moving into the applications of generative AI for learning and development teams, let’s explore the pros and cons in greater detail.

Advantages of Using GenAI for L&D	Risks in Using GenAI for L&D
✅ Adaptive Learning Paths: Creates personalized learning journeys based on individual progress, style, and pace – no more one-size-fits-all training	❌ Human Connection Gap: GenAI misses nuanced emotional cues and complex interpersonal dynamics that human facilitators naturally grasp
✅ Time-Saving Content Creation: Generates first drafts of training materials, quizzes, and assessments in minutes rather than hours	❌ Data Privacy Concerns: Raises questions about information security and confidentiality of learning data
✅ 24/7 Learning Support: Offers round-the-clock assistance for learners across different time zones and schedules	❌ Quality Consistency: Can produce uneven or generic content that needs significant human refinement
✅ Consistent Feedback: Provides immediate, standardized feedback while maintaining objectivity across all learners	❌ Integration Challenges: May not seamlessly fit with existing learning management systems or company processes
✅ Data-Driven Insights: Tracks learning patterns and identifies skill gaps with precision that manual monitoring can’t match	❌ Over-Reliance Risk: Could lead to decreased human involvement in critical developmental conversations

The bottom line: Think of generative AI as a powerful assistant, not a replacement for human expertise in L&D. The key is finding the right balance where technology enhances rather than diminishes the human element in learning.

With this mind, let’s explore what L&D pros are doing with GenAI in the next section.

How are L&D Teams Using Gen AI for Their Work?

Between the AI cheerleaders and the skeptics, there’s a sweet spot where real work happens. Let’s cut through the noise and look at what L&D teams are actually doing with generative AI right now.

Johnson & Johnson’s AI-powered Employee Assessments

Johnson & Johnson needed an efficient way to assess employee skills and align them with evolving business needs.

• Implemented AI-driven skills inference technology to evaluate employees’ competencies.
• Enabled personalized career development by identifying skill gaps and recommending targeted training.

This lead to:

• More accurate skills assessment for leadership development.
• Improved training effectiveness, leading to enhanced workforce capabilities.

DHL – AI-Driven Career Marketplace

DHL wanted to improve employee retention and career progression by offering tailored development opportunities.

• Developed an AI-powered internal career marketplace to match employees with relevant positions.
• Recommended upskilling programs based on individual strengths and career aspirations.

The result?

• Boosted employee engagement and retention by providing clear career pathways.
• Created a more agile and skilled workforce through AI-guided training.

Best Friends Animal Society – AI-Powered Leadership Coaching

Best Friends Animal Society needed scalable leadership development for managers across different locations.

• Used Risely’s AI-powered leadership coaching for personalized feedback and growth plans.
• Integrated experiential learning, including equine-assisted leadership training, for a hands-on development approach.

The impact?

• Strengthened leadership culture within the organization.
• Increased engagement in leadership development initiatives.

Virti – Immersive AI-Driven Training

Organizations needed realistic, risk-free training environments to prepare employees for high-stakes scenarios.

• Built an immersive AI-powered platform using VR/AR for hands-on leadership training.
• Simulated real-world decision-making scenarios to improve leadership skills.

The result:

• Improved knowledge retention and decision-making abilities among trainees.
• Scaled immersive leadership training cost-effectively across organizations.

Getting Started with Generative AI for Learning and Development

Your AI implementation doesn’t need to be perfect – it needs to be practical. If you’re ready to transform your L&D efforts, here’s your step-by-step guide that cuts through the complexity and gets you started.

Step 1: Know Your Ground

You’ll want to start by taking a hard look at your L&D ecosystem. What’s eating up your team’s time? Where do you see your content creators struggling? Map out exactly where your resources are going – you might be surprised to find that 80% of your effort goes into tasks AI could handle.

Look at your content creation workflows, how you’re delivering training, and where your assessment bottlenecks are. When you quantify these pain points, you’ll have solid data to guide your AI investment decisions.

Step 2: Pick Your Battle

You don’t need to revolutionize everything at once. Instead, zero in on one area where you’re feeling the most pressure. Suppose you are in charge of leadership and manager development:

• Are you spending weeks adapting content for different regions? Then your effort needs to focus on ensuring that localization is easier with generative AI for learning and development. For example, teams with leaders spread out across different geographical territories use Risely’s AI coach Merlin to provide them support in their native languages.
• Is your team drowning in assessment creation? Then something like Risely’s in-built set of leadership skills assessment will help you.

Pick a project that will give you quick wins and clear returns. You’ll want something concrete enough to measure but significant enough to matter to your stakeholders. At the same time, you do not want to put hours into experimenting without a promise of results.

Step 3: Tool Up Smart

When you’re choosing your AI tools, think practical, not flashy. You need solutions that will play nice with your existing systems and won’t require a computer science degree to operate. You should also consider that your team will first have to spend some time learning these tools before it starts to show results. If that sounds like a big ask, don’t be afraid to go for free trials, demos and pilots with vendors until you are sure. Ask yourself:

• Will this tool actually solve your specific problems?
• Can your team learn it quickly?
• What’s the real cost when you factor in training and maintenance?

Don’t let fancy features seduce you – focus on what you’ll actually use. We have compiled a list of easy to start with L&D tools that can get you going:

Step 4: Set Your Guardrails

Before you dive in, you’ll need clear rules of engagement. Set up straightforward guidelines for how you’ll use AI – think of it as your safety net. You’ll want to establish who reviews AI-generated content, how you’ll protect sensitive data, and what quality standards you’ll maintain. Make these guidelines clear enough that anyone on your team can follow them without second-guessing.

Step 5: Measure What Matters

You can’t improve what you don’t measure, but you also don’t want to drown in metrics. Focus on numbers that tell your success story: How much time are you saving? Are your learners completing more programs? Is your team able to support more training initiatives? When you track these metrics consistently, you’ll spot patterns and opportunities for improvement that you might otherwise miss.

Remember: Your goal isn’t to win awards for the most innovative AI implementation – it’s to solve real problems that make your L&D function more effective. Start with what’s right in front of you, use the tools that make sense for your context, and build from there. You’ll find that even small improvements can lead to significant impacts when you approach them systematically.

Key Takeaways

• Generative AI is transforming L&D by enabling scalable, personalized learning experiences through automated content creation, adaptive pathways, and data-driven insights. Organizations can leverage this technology to deliver consistent, on-demand leadership development while reducing costs and time investments.
• Successful implementation of generative AI for learning and development requires a balanced approach combining AI capabilities with human oversight. Focus on clear strategic alignment, robust data governance, and comprehensive change management while maintaining the crucial human element in leadership development.
• Start small but think big – begin with specific use cases like personalized microlearning or AI-powered coaching, measure results, and scale based on success. Integration with existing L&D systems and establishing clear metrics for success are crucial first steps.
• While generative AI offers significant benefits, organizations must actively address challenges around data privacy, potential biases, and system integration. Regular monitoring, validation of AI-generated content, and ongoing optimization are essential for long-term success.

References

1. Size of the Global Workplace Training Industry, Raphael Bohne
2. Workforce of the Future Report, PwC
3. McKinsey’s 2024 State of AI report
4. Employers look to AI tools to plug skills gap and retain staff