What Businesses Need to Know.

For learning and development (L&D) leaders, AI offers both disruption and opportunity. It’s reshaping how organizations design, deliver, and personalize learning programs.

But AI isn’t just a tool; it’s a catalyst. It’s shifting the role of learning from a static curriculum to a dynamic, context-aware ecosystem. That change requires thoughtful leadership and a strategic lens.

Here’s a closer look at the trends shaping AI-enabled learning, the pros and cons, and practical guidance for those looking to deliver the very best to learners.

TREND 1: The Rise of Agentic AI in Learning

Imagine an AI agent that watches a learner do an activity in a work simulation, adjusts the activity’s difficulty based on what the learner does, and offers custom feedback pulled from the organization’s best practices.

That’s not science fiction. Organizations are already using agentic AI: autonomous agents powered by large language models (LLMs, like Chat GPT) that can perform complex tasks with minimal human direction.

These AI agents can do things like:

• Serve as personalized virtual coaches or tutors.
• Simulate decision-making scenarios in real time.
• Guide people through learning paths based on their performance and preferences.

Cool. But why use them? AI learning agents can reduce the burden on human facilitators, increase scalability of learning programs, and enable more just-in-time, responsive learning.

But they also require oversight — both ethical and instructional — to make sure the learner’s experience aligns with learning objectives and organizational values.

TREND 2: Generative AI for Content and Graphics Creation

Instead of spending weeks developing a deck, what if your instructional designers could prompt AI to create a first draft, then refine it based on audience needs?

Generative AI — tools like ChatGPT, DALL·E, and others — has unlocked new ways to design and develop learning programs.

For example, L&D teams are using AI to:

• Draft learning objectives, course outlines, and microlearning content.
• Generate infographics, diagrams, and training visuals.
• Translate and localize learning materials faster and more affordably.

This saves time and money. It’s especially good for fast-moving organizations that have to train employees on tools, policies, or compliance issues that are constantly changing.

Teams should use Gen AI carefully, though. If you lean on it too heavily, you get generic, impersonal learning. You need human instructional designers to assess learning needs and ensure relevance, nuance, and tone. AI can create content and , but it can’t (yet) think like your learners or reflect your culture.

Why are organizations leaning into learning AI?

1. Speed and Scale: AI helps learning teams move faster and serve more learners without increasing L&D headcount.
2. Personalization: AI enables content and experiences to adapt in real time to learner needs, improving engagement and retention.
3. Data-Driven Insights: AI can turn learning analytics into actionable conclusions. For example, it can identify where learners struggle most and why.
4. Cost Efficiency: Automating lower-value tasks (like building quizzes or frees up humans to focus on high-value learning strategy, planning, and design.

What should we watch out for?

1. Technical Quality: AI-generated content can be inaccurate or misleading. It needs a human reviewer. This is a big risk for programs like compliance or technical training.
2. Image Quality: Some tools also have a long way to go before they can generate custom images that match your needs. You might get two-tailed dogs or graphics that come close, but aren’t what you want, even after a lot of direction.
3. Equity and Bias: AI tools can reflect and amplify bias present in training data, potentially reinforcing stereotypes or excluding certain learner perspectives.
4. Over-automation: Delegating too much to AI can diminish human connection, which is critical in programs like leadership development and behavior change.
5. Data Privacy: As AI tools collect and process learner data, organizations must stay vigilant about data security and compliance.

Here’s our advice.

AI has incredible potential to enrich learning, but it also raises critical questions. Here’s how to approach it strategically:

Start with purpose.

Avoid the trap of adopting AI for AI’s sake. Ask: What learner experience are we trying to improve? What business outcome are we driving? Then explore how AI can accelerate that result.

Keep humans in the loop.

AI should augment, not replace, the expertise of learning professionals. Use AI for generating ideas, content, and information, but leave strategy, design, reviews, and facilitation to the humans.

Do it ethically.

Build a governance model for AI in learning. This should include guidelines on transparency, accuracy, bias mitigation, and data use. Involve a variety of voices to pressure-test your standards.

Upskill your teams.

AI is here to stay, and L&D professionals need new skills like prompt engineering, AI tool evaluation, and content curation. Invest in upskilling your team so they can get the most of their AI tools.

Focus on behavior change.

AI can support learning, but it doesn’t drive behavior change on its own. Organizations still need thoughtful change management solutions to translate knowledge and skill into sustainable performance.

AI is not replacing strong learning leadership from humans. As tools evolve, the real differentiator will be your team’s ability to connect new technologies with timeless principles: clarity of purpose, learner empathy, and behavior-based design.

AI can help you write the script faster, but you still need to direct the play.

From Training to Performance.

Every year, government agencies invest heavily in training. They develop courses, fill their LMS platforms, and send employees through hours of instruction. Yet many leaders still ask: Why aren’t we seeing better performance results?

They’re seeing the gap between learning and doing.

In high-stakes, high-accountability environments like government, this gap isn’t just frustrating, it is lost opportunity to truly develop people potential and deliver on the promise of exceptional government services.

Agencies don’t just need people to know policies, systems, and processes; they need them to apply that knowledge accurately and consistently.

So, what’s getting in the way and how can we fix it?

The Challenges

Training in a Vacuum

Too often, government training is disconnected from daily work. Employees learn about systems or policies in theory, not in the context of real scenarios. That abstraction makes learning easy to forget and hard to apply.

Over-reliance on Information Transfer

We often assume that knowing leads to doing. But behavior science says otherwise. Knowing the steps to a process doesn’t guarantee following them correctly under pressure. Training that emphasizes knowledge over performance misses the point.

Lack of Reinforcement

Learning fades without follow-up. When there’s no coaching or accountability, people quickly revert to old habits, especially when those habits feel faster or safer.

Cultural and Systemic Barriers

Sometimes the problem isn’t training—it’s the environment. Employees may be trained to collaborate, but if performance systems reward individual output, they won’t change. When systems, leadership behaviors, and training are misaligned, progress stalls.

Bridging the Gap

Training and performance support must be designed with work performance in mind, from the start. Here are five ideas and two technologies to make that shift:

Meet people where they are.

The Five Moments of Need model by Bob Mosher and Dr. Conrad Gottfredson reframes learning as a continuous process. It identifies five key moments when people most need support: when learning something new, wanting to learn more, applying knowledge, solving problems, or adapting to change. The key is to align learning strategies to the moments of need. Formal training is important when learning something new, while on-demand performance support helps with application and change.

Example: A federal HR specialist uses formal training to learn a new hiring system (New), quick reference guides while processing applications (Apply), and updated resources when policy guidance changes (Change).

Build for behavior, not just knowledge.

Start with the end in mind: What do we want people to do differently? Define the critical behaviors, then design training that helps people practice and get feedback.

Example: Instead of lecturing on conflict-of-interest policy, simulate real scenarios where employees must make judgment calls and receive feedback in real time.

Align training with systems and culture.

If training teaches one thing but systems reward another, behavior change won’t stick. Before designing new learning, ask: What are we rewarding?

Example: Review performance metrics, SOPs, and feedback loops to ensure they reinforce the new behaviors, not the old ones.

Ground training in the real world.

Learning should feel familiar and actionable. Use real cases, language, and systems employees recognize.

Example: Partner with front-line managers to identify everyday challenges and build your training activities around them.

Reinforce with coaching and feedback.

Learning is a process, not an event. Incorporate follow-up discussions, manager coaching, and check-ins that show the behavior still matters.

Example: Create a “learning transfer plan” for supervisors to reinforce key behaviors during team meetings.

Make learning and performance support personal.

A Learning Experience Platform (LXP) delivers personalized, just-in-time learning tailored to each employee’s role, goals, and recent activity. It moves learning from compliance-driven to performance-focused. These systems are more affordable and capable than ever and provide a flexible, mobile resource tailored to the individual.

Example: A Contract Officers Representative (COR), updating a contract record might receive a recommendation for a short video on managing vendor performance — right when it’s most relevant.

Remove friction wherever you can.

A Digital Adoption Platform (DAP) provides step-by-step, on-screen guidance inside the applications employees use every day. This helps them perform tasks accurately without leaving their workflow.

Example: When a federal employee logs into a new acquisition system, a DAP can guide them through creating a requisition, explaining each field along the way. The result: faster adoption, fewer errors, and greater confidence.

The Opportunity Ahead

Government agencies face complex challenges, policy shifts, tight budgets, legacy systems, and evolving missions. But they also have a tremendous opportunity to lead with intention.

When agencies shift their focus from training delivery to performance enablement, they close the learning–doing gap. They create not just informed employees, but capable, confident professionals ready to deliver excellence where it matters most: on the job.

Want to explore the topic in more detail with John? Hop on his calendar: Book a meeting with John

What CEOs Should Really Expect from L&D (and from AI).

The pace of change is brutal. Tech evolution, shifting customer demands, workforce expectations, economic pressure. Strategy is no longer just about picking the right path. It’s about having a workforce ready and able to walk it.

So, what’s the lever that drives speed, consistency, and alignment across your people?

Learning.

Not learning just for learning’s sake. Learning as a strategic investment with a measurable return.

Learning sits at the heart of every business operation. It needs deliberate integration. For example, every company strives for innovation, but that won’t occur without change and change never sticks without learning.

Here’s the issue through another lens: the number one driver of turnover (especially in younger generations) is a lack of career and growth opportunities. One way to counter this is a continuous learning environment with dedicated competency models and role-based curricula.

In other words, learning enables strategy and change, while also helping to keep your A-players in-house, fortifying your future.

Let’s look at what this all means for CEOs, and how AI can elevate the value without replacing the effort.

Is learning a good investment?

CEOs are rightly focused on business outcomes. So, when they invest in learning, they expect results. The smartest leaders tie learning to their top business priorities:

• Faster execution of strategy – A roadmap doesn’t move itself; people do.
• Improved productivity and performance – L&D should uplift KPIs, not just report completion rates.
• Leadership pipeline – Developing leaders internally beats expensive external hires and maintains culture more consistently.
• Cultural alignment – Learning reinforces values, creates clarity, and shifts behavior.
• Customer experience – Upskilled teams create brand consistency and stronger service.

Having a deliberate learning focus elevates every facet of a strong, sustainable operating model. Learning isn’t a perk or a perk-up. It’s how you future-proof your organization.

Can AI help?

When it comes to AI, the temptation is real: “Can’t we just use AI to build the training and get it out there faster?”

Yes and no.

AI is a powerful tool in the L&D arsenal. It can speed up content creation, personalize learning at scale, surface insights from learner behavior, and provide just-in-time support in the flow of work. It can help answer questions like: Who needs what? Where are our skill gaps? How do we tailor this for different learners?

But AI can’t do everything. It doesn’t replace the hard work of intentional design, alignment to business strategy, and change leadership. And it certainly doesn’t replace the human connection needed for coaching, accountability, or cultural transformation. Without a human in the loop, training can be built faster, but does that matter if it’s not any good, or not relevant to your people?

So, while CEOs should expect their L&D teams to integrate AI, they shouldn’t expect AI to replace the investment in learning. In fact, AI takes time and a thoughtful strategy to be effective. When done right, AI should amplify the ROI of your investment in learning by lowering barriers, increasing relevance, and helping learners succeed faster through on-demand support and reinforcement.

Don’t think of it as getting the same with less investment; think of it as getting more with a similar investment.

If we do it right, what should we expect?

Here’s a simple way to think about it.

Outcomes CEOs should expect from AI-powered L&D:

• Faster time-to-competency
• Smarter prioritization of learning needs
• More engaging and adaptive learning journeys
• Scalable performance support tools
• Actionable insights from learning data

Outcomes CEOs should not expect:

• Cultural transformation without human leadership
• Engaging training without cultural context and relevance
• Behavior change without reinforcement and practice
• Strategic alignment and organizational impact from disconnected training
• Automatic ROI from AI-only solutions

If your goal is a workforce that’s ready to execute at the speed of strategy, you have to build, test, and embed learning. AI helps you scale brilliance, but it doesn’t create it.

What’s the elevator speech?

The organizations that win with AI aren’t the ones that cut the most L&D costs. They’re the ones that scale the smartest. Learning isn’t just a cost; it’s the path to capability, resilience, and competitive advantage. AI simply helps us walk that path faster.

Don’t fall into the trap of thinking AI is your L&D strategy. Instead, build a strategy that AI can elevate. One that ties to business goals, prioritizes behavior change, and invests in your people.

Because learning isn’t overhead. It’s infrastructure.

It’s not an expense. It’s a growth engine.

And when done right, with the help of AI, it’s one of the most future-ready investments a CEO can make.

Four Practical Tips for Lasting Behavior Change.

Artificial intelligence is no longer a futuristic concept; it’s a present-day force reshaping industries, job functions, and workflows across the board.

Organizations often invest heavily in technology but overlook the most important part of successful adoption: people. The trouble is, while AI tools evolve at lightning speed, human behavior doesn’t change overnight.

To make AI truly work for the business, companies must help employees shift how they think, work, and collaborate.

That means addressing the fears, habits, and uncertainties that often accompany technological disruption.

Here are four practical ways to lead your workforce through this transition, building confidence, capability, and commitment along the way.

Involve employees early and often.

Change is easier when people feel seen and heard. Involve employees early, during the design, testing, and rollout of AI initiatives.

Ask what they need, what gets in their way, and how they imagine AI enhancing — not replacing – their talents and contributions. Co-creation builds trust and fosters ownership, turning skeptics into champions.

Give them ongoing, practical education.

Demystify AI from the start. Many employees hesitate because they don’t understand what AI is or how it applies to them.

Provide hands-on learning that lets people explore AI tools within the flow of their actual work. Encourage experimentation in low-risk environments and embed education into everyday tasks. When people understand the tools, fear gives way to curiosity, and resistance turns into engagement.

Highlight tangible, everyday value.

People adopt new behaviors when they see clear benefits. Don’t leave AI as an abstraction — show how it solves real problems.

Demonstrate how it reduces repetitive tasks, or speeds up decisions, or frees time for creative and strategic work. Use whatever example resonates with the employee. Connect AI directly to day-to-day responsibilities and you’ll build momentum from the ground up.

Anchor AI to strategic goals.

Behavior change sticks when it’s aligned with the company’s broader mission.

Tie AI initiatives to strategic goals like improving customer experience, boosting productivity, or accelerating innovation. And communicate that alignment clearly. When employees see how AI supports the company’s direction, they’re more motivated to adapt and contribute.

AI disruption doesn’t have to feel like a threat. It can be a powerful catalyst for growth when paired with intentional, human-centered change strategies.

By equipping your people with the knowledge, tools, and context they need, you’ll not only ease the transition, but you’ll unlock the full potential of your technology investment. The future of work isn’t just automated. It’s collaborative, strategic, and deeply human.

Here’s how to be a force for proactive capability-building.

If you were to describe your L&D strategy as a profession, would it be a firefighter or an architect?

Don’t get me wrong – firefighters are essential to the health and safety of any community. They are also professionals; there is a science to effectively extinguish a structure or landscape engulfed in flames. But firefighting is a fundamentally reactive job. They have to wait until something bad happens, then solve it as best they can.

Too often, learning and development professionals feel like firefighters.

How do we break out of this endless cycle of putting out one “fire” after another? Is there another way?

Yes. You can move toward being a trusted, proactive partner with the business. You can anticipate business needs, support strategy, and get the workforce ready for what’s next.

Understanding Reactive L&D

Consider this: How many times has your organization encountered a skill gap or compliance issue, then rushed to find or develop training? Reactive L&D is characterized by short-term fixes that address urgent problems but rarely contribute to long-term growth.

Does your team suffer from reactivity? Here are some of the symptoms.

• Crisis-Driven Initiatives: Training programs are launched in response to an immediate challenge, such as an audit or a sudden new regulation.
• Lack of Strategic Alignment: There is little connection between training programs and the long-term goals of the organization.
• Inconsistent Outcomes: Rapid, one-off training sessions often fail to create lasting change, resulting in a cycle of recurring issues.
• High Operational Costs: Continuously responding to crises can be much more expensive than investing in a sustainable, forward-thinking strategy.

It can feel like being in a perpetual state of emergency—always putting out fires and rarely planning ahead.

Why Proactive L&D Matters

Shifting to proactive L&D means becoming the architect of the organization’s future capabilities. Proactive L&D integrates strategically with business goals, ensuring that employees are equipped to handle current demands and prepared for tomorrow’s challenges.

What do you get from a proactive approach?

• Agility: Employees have the skills they need before a challenge arises, making the organization more nimble and ready to adapt.
• Cost Efficiency: By investing in long-term capability-building, companies can reduce the recurring costs of emergency training.
• Higher Employee Engagement: Training programs that align with career growth and strategic goals naturally boost motivation and job satisfaction.
• Future Focus: Building capabilities proactively ensures that the organization is equipped to fulfill its strategies, like innovation and industry dominance.

The benefits cannot be overstated: Proactive L&D organizations have higher credibility and value to the business than reactive L&D organizations. A proactive L&D team does more than prepare the workforce for change—it actively shapes the future of their industry.

How To Shift from Reactive to Proactive

We would all love to be on that L&D team, right?  So, how can your L&D organization break free from the cycle of reactivity and start paving a path toward proactive capability-building?

Here’s a roadmap:

1. 1. Align with strategic goals.
      • Collaborate with leadership. Make your case for a seat at the table. L&D as a strategic partner is in everyone’s best interest. When L&D is involved in long-term vision and strategic priorities, learning efforts will support them and investments will align with them. At a minimum, understand your organization’s long-term vision and strategic .
      • Define key competencies. Identify the skills and capabilities that will be critical for achieving future goals.
   2. Conduct a comprehensive needs analysis.
      • Develop data-driven insights. Use performance metrics, employee feedback, and market research to anticipate future skill gaps.
      • Conduct future-focused surveys. Regularly assess emerging trends and technology shifts that might impact your industry.
   3. Embrace flexible learning design.
      • Create modular programs. Develop flexible and scalable training modules that can be updated as trends evolve.
      • Use blended learning. Combine digital, self-paced modules with interactive, instructor-led sessions to cater to diverse learning needs.
   4. Establish continuous feedback loops.
      • Establish ongoing evaluation. Implement learning analytics dashboards that provide real-time insights into program effectiveness.
      • Make iterative improvements. Use feedback to continuously update and refine training programs, so they stay relevant and impactful.

By following these steps, L&D teams can shift their focus from “fighting fires” to fueling sustainable, strategic growth.

Practical Tools for Proactive L&D

To truly transform your L&D strategy, use modern tools and frameworks. Here are a few to consider:

• Capability Maps: Visual representations of the skills and competencies required at various organizational levels.
• Skills Assessments: Regular evaluations that identify both current proficiencies and future needs.
• Learning Analytics Platforms: Tools that collect and analyze data to measure learning impact, engagement, and retention.
• Predictive Analytics and AI: Technologies that forecast skill trends and help personalize the learning journey for each employee.

Embracing these tools will boost training effectiveness and make sure training supports your business strategies and outcomes.

So, are you ready to transform your L&D approach? Shifting from reactive training to proactive capability-building requires a fundamental change in mindset and a commitment to long-term strategic thinking. Instead of waiting for crises to force your hand, design learning programs that anticipate challenges, foster innovation, and empower your workforce for the future.

Be the architect of your organization’s success—not just its problem-solver. Step toward a future where every training initiative is a strategic investment in your people and the organization’s long-term growth.
 

Want to explore the topic in more detail? We’d love to chat: Grab a virtual coffee together

It’s a partnership, not a replacement.

In the ever-evolving world of Learning and Development (L&D), artificial intelligence (AI) is no longer a futuristic concept; it’s here, and it’s reshaping the way we deliver training, support employee growth, and drive organizational success.

But let’s get one thing straight: AI isn’t coming for your job. Instead, it’s here to augment human capabilities, empowering L&D professionals to focus on what they do best: connecting with people and fostering meaningful learning experiences.

Use AI as an assistant.

One of AI’s most practical uses in L&D is automating time-consuming tasks. Tools like ChatGPT or xAPI-driven analytics platforms can summarize learner feedback, generate initial course drafts, and even provide 24/7 learner support.

For instance, imagine an AI-powered chatbot answering routine questions about a leadership development program, freeing up L&D teams to focus on creating impactful curricula.

This isn’t about replacing human expertise; it’s about using AI to handle the mundane so humans can tackle the meaningful.

Personalize at scale.

AI also excels at personalization, something L&D professionals have long sought but struggled to implement and manage at scale.

Platforms like Docebo or Cornerstone OnDemand use AI to analyze learner behavior, recommend relevant content, and even adapt learning pathways in real time. This ensures employees receive the right learning at the right moment, creating a tailored experience without requiring L&D professionals to sift through mountains of data manually.

Make smarter decisions.

AI’s analytical power can transform how L&D measures success. Tools like Degreed or learningpool use AI to analyze complex datasets, such as skill gaps and learning outcomes, and translate them into actionable insights.

These insights enable L&D professionals to refine programs and align them with business goals, ensuring a direct impact on organizational success.

Keep the “human” in human capital.

The secret to using AI with L&D is remembering that AI thrives when paired with human expertise.

While AI can process data and generate solutions, it lacks the emotional intelligence and cultural sensitivity to create impactful learning experiences. L&D professionals understand organizational nuances, foster empathy, and build trust. Those are things AI just can’t replicate.

The most successful L&D teams of the future won’t be those who fear AI, but those who embrace it as a partner.

By automating repetitive tasks, personalizing learning experiences, and providing actionable insights, AI allows professionals to focus on what really matters: enabling human potential.

The challenge isn’t whether or not to adopt AI. It’s how we, as L&D leaders, integrate it thoughtfully to elevate our impact. It’s time to shift the narrative: AI isn’t a replacement for humans. It’s the ultimate collaborator.

Use AI to improve, assess, and promote your learning programs.

Artificial Intelligence (AI) is kind of a big deal these days. It has revolutionized data-driven decision-making. Companies can now handle way more data, make faster and more accurate predictions, and even automate much of the analysis.

AI-powered models are so much better at managing complex, large-scale, and unstructured data than the old methods, which helps companies be more agile, precise, and deliver more personalized experiences.

Have you ever noticed that once you finish watching one episode of your favorite Netflix shows, a recommendation appears that you just can’t ignore? That’s because Netflix deploys AI/ML and data science to match your preferences with existing content on the platform. And it delivers results for Netflix; they are now connected with 260 million engaged users, accounting for a total revenue of $33.724 billion in 2023.

“But Sadé,” I’m sure you are asking, “what does that have to do with learning and development?”

Here are a few questions.

• What if you could create a truly personalized learning experience by tracking each learner’s journey and adapting content based on their interactions and progress?
• How much more valuable would your course be if you could track learning experiences across multiple platforms and even offline activities?
• What if you could easily integrate learning data with other business systems like CRM or HR platforms to get a more complete picture of a learner’s journey and performance?
• Would you like to capture the real-world application of learning (like learners using those skills on the job) and then use those data to measure the effectiveness of your course?
• What if you could quantify your learning program’s benefit to the organization?

Would detailed learning data help you make decisions and improve your learning organization’s programs?

xAPI can help.

xAPI, or Experience API (sometimes called Tin Can API), is a way to track and record learning experiences. It lets you capture learning activities from all kinds of platforms and situations, whether they’re happening online or offline. With xAPI and AI working together, you can track exactly how learning experiences impact job performance, identify which training activities deliver the most value, and make data-driven adjustments to your programs.

This means you can clearly demonstrate the effectiveness of your L&D efforts, tailor learning experiences to each individual, and ensure that your investment in training is driving real business results.

Here’s an example.

A global sales organization wants to improve the effectiveness of its sales training program. They want to know which training modules are most impactful, how long it takes for new hires to become productive, and how to tailor training to individual learning styles. And, of course, they want better sales performance.

They track learning:

• Formal Training. xAPI tracks traditional e-learning courses, webinars, and classroom sessions, capturing data like completion rates, quiz scores, and time spent.
• Informal Learning. xAPI monitors social learning interactions, knowledge sharing, and peer-to-peer mentoring in collaboration tools.
• On-the-Job Learning. xAPI tracks real-world sales calls, customer interactions, and performance metrics captured by the company’s CRM.

They use AI-Powered Insights:

• Predictive Analytics. AI analyzes xAPI data to identify patterns and predict future performance. For example, the system flags learners who are struggling with a specific module and recommends alternatives and new training.
• Personalized Learning Paths. AI creates custom learning paths based on individual learner needs, preferences, and performance data.
• Real-Time Feedback. AI-powered chatbots give fast feedback and guidance to learners, helping them stay on track and address knowledge gaps.

And they get results:

• Better Sales Performance. Learners are directed to the most effective training modules, and they get a tailored learning experience – what they need, when they need it. This means faster onboarding and upskilling, which boosts productivity.
• Data-Driven Decision Making. xAPI and AI help the organization decide on training investments and assign resources to training efforts.
• Enhanced Learner Experience. Learners get the right learning paths for them and get personalized feedback while they’re learning.

But how? Here are some next steps.

1. Find your why. Consider the highest priorities for your company, your business, and the learners you serve. How is L&D enabling these priorities? Can you measure that? What measurements are you missing? What compelling stories of the value of L&D would you like to tell? Asking yourself these questions will help to build a business case for data-driven learning programs.
2. Start making connections. Many companies have already begun embracing a data-driven culture and started exploring Artificial Intelligence, even in its infancy. Your company is likely one. Tap in. Find out who works with data in your company. Connect with that person, team, or department within your company. Introduce yourself, find out what they are working on, and what synergies are possible — now or in the future. Making these connections will help you begin to plan and organize around the work to come and your people.
3. Assess your current tech. What are the capabilities of your LMS? Does it support xAPI? Does your company already have a Learning Record Store (LRS) in place? What information can be pulled from your company’s LMS? Is it connected to employee data? Is your company using a unified Enterprise Resource Planning (ERP) suite such as SAP or Oracle? What about a CRM? Consider all the places you could gain information about the employee experience and their work performance. We’ll need this information later so we can begin to feed the AI models targeted information to receive helpful insights.
4. Identify Gaps. After completing steps 1-3, you will undoubtably found some gaps, whether large or small. You might identify gaps in technology, trackable data, in-depth technical knowledge, data analytic skills, or bandwidth to take on this change. But don’t be alarmed; you’ve taken the essential first step. You can’t fix what you don’t acknowledge.

Using data and AI will help you create more powerful learning programs, programs that explicitly show the value of L&D in your organization.

WIIFM? (What’s in it for me?)

A rite of passage for any southern cook is the successful execution of the most important baked good: The Biscuit. Filled with bacon, cheese, and egg, it becomes a substantial meal in itself. Buttered and drizzled with maple syrup, it becomes the end to what I call a “wood-splitting breakfast” — because you had better do something with all those calories!

So, it was with some enthusiasm (and ill-placed confidence) that I, then a teenager, attempted my first batch of biscuits. The moment came to take the tray from the oven. The tan hockey pucks on the tray in front of me bore some resemblance to biscuits. But they had a concerning, very dense sound as I slid them onto a plate. I soon discovered that what I had produced was not the biscuits of my childhood; these were closer to the hardtack that sustained nineteenth-century sailors as they endured months-long circumnavigations of the globe.

My critical error?  I left out the baking powder. In my rush, I had grabbed the all-purpose flour but left that little can of baking powder on the shelf.

One teaspoon. (!)

That’s what stood between me and my culinary triumph.

A few years later, I was in my first role as a learning and development professional. I did most of the right things: I met with the business stakeholders. I created an interactive training. Heck, I even met with some of the people who had been in previous trainings to get their feedback.

So, it was with some enthusiasm (see where I’m going here?) that I facilitated the training.

As a facilitator, you can tell when the room (whether physical or virtual) feels “flat.”

This was a flat room (not unlike the aforementioned biscuits). Not a lot of engagement. Very little discussion.

I dismissed the group for lunch. As I sat in the empty training room, I discovered my critical error: I had left out any discussion on why the content was important.

It’s not that I didn’t know why it was important: I had solid reporting data showing that the new skills would help participants be more successful in their roles. Unfortunately, the participants did not have the benefit of that information.

Faced with this realization, I outlined the rationale for the course. I grabbed someone who had previously taken the course and asked them for a quick testimonial to share with the class. Then, I pulled together a summary of the data that demonstrated the value of taking the course. In short, I articulated the WIIFM – the ‘What’s in it for Me?’ – something that I should have done at the outset!

The WIIFM concept is not new.

As the field of advertising came of age in the mid-twentieth century, more emphasis was placed on addressing the customer’s needs and wants. Over the following decades, the WIIFM concept was developed and refined. And whether you realize it or not, the learner is your customer! Adoption of any course begins with the learner “buying what you are selling.”

Your courses most likely already begin with strong learning objectives complete with Bloom’s verbs. That’s great! However, don’t make the mistake of assuming that good learning objectives answer the WIIFM question. To be sure, learning objectives align with the WIIFM, but articulating the WIIFM will help the learner understand how the learning will benefit them personally.

Here are some steps to answer the WIIFM right away:

1. Begin with the problem that the learning is designed to solve. You’ve created the learning for a specific purpose, so spell it out. For example, this might mean acknowledging the shortcomings of an aging ERP or the cost of poor customer service. Are your learners already aware of the problem? Probably, but there is something about naming the issue in plain words that is very effective.
2. Emphasize how the learning will address the problem. In the case of a systems or software training course, this is the ideal place to introduce the new tool and preview how it will address the problem. For instance, if the course teaches the durable skills as a part of customer service training, this section might include examples of how skills will lead to a better customer experience.
3. Stress the benefit of ‘buying’ the course. This is the heart of the WIIFM! To really drive this home, we have to put ourselves in the place of the learner. How will this training make their work easier? How can it optimize the experience of everyone involved? If there are implications to CSAT scores, compensation, or other key metrics, spell them out!

Back to my near miss with WIIFM.

Armed with this information, I welcomed the class as they returned to the training room. Before we jumped back into the content, I acknowledged that I had failed to truly address the reason for the training and how it could benefit them. I presented the WIIFM that I developed over lunch. In a moment of serendipity, the employee who provided the testimonial was actually walking by the training room; I called them in to talk with the class.

The difference in participant engagement after this was undeniable, and course feedback reflected the value of the discussion.

Occasionally I forget to take the trash can down to the street on Sunday night. Sometimes, when someone asks my age, I have to think for a moment. But there are two things I never forget: baking powder in the biscuits and the WIIFM in every training opportunity.

Case studies are a powerful tool in organizational training.

Case studies use realistic challenges to help employees develop critical thinking, problem-solving, and decision-making skills. They root learning in the context of the real world, making lessons more effective in several ways.

Why use case studies?

They bolster your project goals.

You think a change in technology or process will deliver benefits, but you don’t know until you try. Training case studies are the first test. They build a bridge between strategic concepts and practical application.

They give employees a taste of success.

Case studies are based on reality – real people doing real work. They show learners what’s possible. Learners approaching technical training often expect to feel overwhelmed. But if they complete case studies successfully, training reinforces both the new skills and confidence that they can do the job in the new way.

They help employees become better problem-solvers.

Case studies challenge learners to react to the complexities of your real-world business. They have to assess information, identify key issues, figure out what to do, then do it. This tests not only their work process or technology change, but their thinking and problem-solving skills as well, which they will absolutely need on the job.

They help learners retain and apply new skills.

Riding a bike is a whole lot easier to learn through practical experience rather than studying. Case studies put the learner in the context of their real jobs, making training feel real and relevant, and making new skills easier to remember and apply.

They strengthen teams.

Case studies often involve group work, encouraging collaboration and the synergy of diverse perspectives. This keeps learners engaged and – bonus — fosters teamwork, communication, and the exchange of ideas.

Use these tips.

Clearly define learning objectives.

Hopefully this is pretty obvious but make sure to establish clear learning objectives. Determine what skills or knowledge you want learners to develop, such as strategic thinking, analytical skills, or team collaboration. The learning objectives determine everything you get out of the training program. And they anchor the program back to the organizational needs, ensuring what we teach is aligned with strategic initiatives and drives ROI.

Choose relevant and realistic cases.

Select case studies that make sense for your learners’ roles. They must practice the work they’ll actually do on the job. That means a realistic scenario, data, and challenges. Cases that reflect their actual work environment will get you the skills bump you’re looking for and provide the team with practical insights.

Provide the right inputs and context.

Give learners all the information and context they would have on the job. That includes detailed descriptions of the scenario, the people they’re interacting with to complete the task, data they need, and feedback on results. Insufficient data and context make your case study frustrating and ineffective. This is where you need to rely heavily on your subject matter experts. Get their input and sign-off before you train.

Use varied case studies.

A diverse selection of case studies exposes learners to different scenarios and challenges. Include cases that vary in complexity, industry, and business functions to build a broad skill set. This prepares learners for the range of situations they might encounter in their roles. For example, if learners work with customers from different regions or industries, include as many as possible. Highlight unique challenges and solutions for each.

Encourage engagement.

Talking through a case study is incredibly powerful for learners. Even if the case study isn’t a collaborative task, build in learner conversation and debriefs. Encourage learners to discuss their challenges, solutions, and how they might apply their learning on the job. Use open-ended questions to prompt critical thinking and ensure that all participants have the opportunity to contribute. Discussions can also help connect learners to the wider organization and reinforce the strategic goals of the training. For example, ask questions like, “What are the potential risks of this strategy?” or “How could this decision impact other departments?”

Give real-time feedback.

Timely feedback reinforces learning and retention; it’s the “reward” part of habit formation. Feedback should go beyond “right” or “wrong.” Nuance is key – good/better/best provides more avenue for growth than simply bad/good. Also, tell them why, then highlight strengths, suggest alternative answers, and relate their decisions to real-world outcomes. This feedback helps learners visualize the practical implications of their decisions and performance.

Encourage reflection and debriefing.

After completing a case study, build in an activity where learners can reflect on their decisions and the work process. Discuss what worked well, what could be improved, and how the lessons learned can be applied in their daily work. This reflection reinforces learning and encourages continuous improvement. For example, ask questions like, “What was the most challenging aspect of this case study?” and “How can we apply these insights to our current projects?”

Integrate technology.

Use technology, where it makes sense, to enhance the case study experience. Incorporate any digital tools that make the case more realistic, such as online simulations, interactive platforms, and collaboration software. Technology can provide real-time data analysis and work team collaborations.

Use multiple modalities.

Provide materials in various formats, such as written documents, videos, and interactive modules. Variety and repetition boost engagement and retention. For example, if you have an overview, provide it both in written and video form. Or, if you are presenting a workflow, use a graphic with a voiceover to hit multiple senses and reinforce learning.

Beyond that, switch up your delivery style. Try providing the context of one case study through a video of a simulated client conversation, and then cue up the next case study through a simulated email chain. This captures multiple real-life avenues of interaction, while avoiding repetitive, stale delivery.

Measure effectiveness and iterate.

Case studies are a big investment of time and brain power; it’s a good idea to find out whether you got the bang for your buck. Use assessments, feedback, and performance metrics. For example, you might deploy surveys to see how the new skills are being used on the job. Then refine your approach, update case study materials, and improve the overall learning experience. Continuous iteration and improvement pay off.

In conclusion…

By now you’ve realized the significance of well-crafted of case studies for organizational training…if you design and build them right.

Click here to download our list of tips for case studies.

AI Tools and Tips for Beginners.

The beauty of AI is that it can be used by anyone, but its potential is realized only by those very skilled in it. In other words, most AI tools have a low barrier to entry and a steady learning curve. Invest a lot of time learning AI, and its benefits will feel limitless.

To illustrate this point, let’s look at the learning curve of another common tool; Excel. Let’s use Excel as an example. Excel has a low barrier to entry; entering data into a row and column, calculating sums is a skill that most folks can learn quickly. The ratio of time investment to effectiveness is low. Excel also has a gradual learning curve, and those who invest a lot of time are rewarded with a gorgeous, color-coded bundle of formulas that produce veritable wizardry.

(Shoutout to Mike Cassady and Micah Green, our resident Excel wizards.)

AI works like that. Low barrier to entry; steady learning curve; investment = greatness. So, how do you start? Specifically, how can learning and development practitioners unlock the power of AI when creating their next project or course? Let’s break it down into a few key tools and explore how we’ve used them on our projects.

The three tools we will explore are:

• ChatGPT
• Synthesia
• Midjourney

ChatGPT

Ya know it, ya love it. ChatGPT is an AI program, created by OpenAI, that can understand and write human-like text. It helps users by answering questions and having conversations on various topics.

I like to think of ChatGPT as my own personal (and very knowledgeable) assistant. As of August 2024, it is likely the best AI tool available today in terms of versatility, accuracy, capability, and usability.

Level-up your verbal content.

I see ChatGPT as an accelerator. Use ChatGPT to improve the syntax and verbiage of content you’ve already written. It will give you many options – alternate ways to say what you’re trying to say.

Have you ever looked at a sentence and felt there’s a better way to express it, but you’re drawing a blank? ChatGPT to the rescue!

My Prompt

Hey ChatGPT, here’s a sentence that I’m trying to improve the flow of. Can you give me 3 options for this?

“When implementing a software change that will influence every employee, these three most common causes for frustration must be considered.”

ChatGPT’s Answer

Sure! Here are three options to improve the flow of your sentence:

1. “When implementing a software change that affects every employee, it is essential to consider these three common causes of frustration.”
2. “As you implement a software change that impacts all employees, it’s important to take into account these three prevalent sources of frustration.”
3. “In the process of implementing a software change that will affect every employee, you should consider the following three common causes of frustration.”

My Prompt

I like option 3, but let’s shift a little bit and pose it in the form of a question. It will be a click-to-reveal slide and prompt the learner to discover these three causes on their own.

ChatGPT’s Answer

Great choice! Here’s a revised version of option 3 posed as a question for your click-to-reveal slide:

• “What are the three common causes of frustration to consider when implementing a software change that will affect every employee?”

At this point, I modify it to suit my preferences. In this case, I found it a bit too wordy, and the part about “every employee” felt redundant since it was mentioned earlier in the course. Therefore, I adjusted it to…

What Are the Three Leading Causes for Frustration When Initiating a Software Change?

Write learning objectives.

Sample Prompt

I am developing a course, and the learning objectives must align with these points. Provide me five options and please use terminology from Bloom’s Taxonomy: Level 2 when creating them.

Takeaway

The points you provide ChatGPT can be crude and segmented; you can “think out loud” as you provide it with enough content to generate an answer.

Write knowledge checks.

Sample Prompt

Help me create a knowledge check question with the following parameters:

• This must be a single-selection, multiple-choice question.
• Two of the distractors must align closely with the correct answer; one of them can be a bit further off.
• Answering the question correctly will demonstrate that the learner has achieved this learning objective.
• Provide customized feedback on why each choice is correct/incorrect.
• Here is the content: When initiating a change in software throughout the entire organization, things that must be considered are response effort, training needs, and providing ongoing support.”

Write a script.

Sample Prompt

Here is a paragraph of on-screen content I have written. Can you create a script for a narrator that will be in the second person? Use a tone that is informative and nurturing. Examples of this can be “It is normal to encounter resistance to technological changes in your workplace, so you’re not alone.”

Takeaway

When it comes to generative AI tools like ChatGPT, the limitations are often determined by the user. If you’re wondering whether ChatGPT can perform a specific task for you, it never hurts to ask!

Here’s what ChatGPT helped me do.

Synthesia

Access it here.

On one of our learning projects, we had some initial discussions with the client and discovered that they really wanted video narration from a facilitator or mentor throughout the series of courses.

They were considering hiring voice talent to do this, but there were logistical and cost concerns. First, the course content would be dynamic. Second, stakeholders would approve only deliverables that were close to the finished product, narration included. That would mean re-recording narration after every review cycle.

Because of these factors, we proposed using Synthesia. It provided video narration while also mitigating the logistical concerns.

After working with our SMEs, we created scripts for the first course with some input from ChatGPT. Then, we brought the scripts over to Synthesia.

Our initial thoughts about Synthesia were:

• The interface is straightforward and felt familiar, especially if you have experience working with video editors and other AI narration tools like WellSaidLabs.
• The inflection and presentation of the avatars, though clearly AI-generated, were in line with what we were looking for.

To reduce that “AI look,” we shrunk the MP4 output and placed it behind a frame that really tied everything together.

Here’s what Synthesia helped me do.

If my situation sounds familiar to you, consider looking into Synthesia. We found that it checked all the boxes.

Midjourney

Access it here.

Like ChatGPT, Midjourney is a generative AI tool that requires the user to provide a prompt. Midjourney uses your prompts to create imagery.

After a few working sessions with our client, we established a general theme for the courses. We were aiming for a sleek feel with a dark palette. Midjourney allowed us to generate imagery that fit within the theme and branding guidelines.

This tool has been a major timesaver when prototyping and creating visual mockups (Have you ever spent hours creating a concept only to have it declined within seconds?)

• In working sessions with our client, we established a general theme for the courses.
• We used Midjourney to create several options that fit the theme and their branding guidelines.
• After they selected their favorite option, we continued using Midjourney to develop more polished images until everyone was happy with the result.

Here’s what Midjourney helped me do.

Using AI on a learning and development project doesn’t have to be hard. The barrier is low, so get started! With creative prompting and a dedication to quality for learners, an instructional designer can produce great content efficiently.