“Complacency is like the water a fish swims in—it’s everywhere, but we don’t see it.” — John Kotter

Change management is having its moment again—but perhaps for the wrong reasons. In an era now defined by generative AI, hybrid work, and relentless transformation, learning and development (L&D) teams are being asked not only to help others adapt, but to reinvent themselves at the same time.

For more than 25 years, I’ve conducted in-depth interviews with leading thinkers on leadership and organizational change—Harvard Professor John Kotter among them. Over time, I’ve distilled the essence of their ideas into insights for learning professionals who are increasingly being called to serve as catalysts for enterprise change. Across all these conversations, one message is consistent:

Technology doesn’t drive transformation—people do. It’s fueled by their urgency to move, their readiness to challenge what’s outdated, and their courage to create what’s next.

In this, the first of a two-part series based on an interview with Kotter, I draw two enduring lessons that stand out for L&D leaders seeking to lead meaningful change in their companies: confront complacency and ignite urgency.

1. Confront complacency: Recognize the invisible enemy

Kotter once said that complacency is “like a fish not seeing the water it swims in.” In 2025, that metaphor feels painfully accurate for L&D. Many organizations appear in motion—launching learning campaigns, publishing micro-courses, tracking dashboards—but few are moving forward. Kotter called this ‘false urgency’: frantic activity driven by anxiety, not insight.

In learning organizations, false urgency often looks like:

• Chasing course completions instead of capability growth
• Mistaking content production for culture change
• Confusing ‘being busy’ with ‘being useful’

The deeper danger is that busyness masks complacency. As Kotter observed, “It’s almost impossible to find a person who sees themselves as complacent.” The same applies to departments. An L&D function can look productive—publishing hundreds of modules—while avoiding the tougher work of confronting outdated strategies, systems, or habits that no longer serve the organization’s goals.

What to do

Build reflective mechanisms into your practice. Instead of measuring learning activity, focus on how quickly people perform better—Kotter’s go-to benchmark for true learning. Use after-action reviews, performance analytics, or learner narratives to see whether knowledge is actually turning into change.

L&D insight

Build a culture that values reflection as an antidote to Kotter’s ‘false urgency.’

2. Ignite urgency: Keep the spark alive

Kotter argued that “a true sense of urgency is rare, much rarer than most people think.” It’s a focused energy built on opportunity, not fear. For L&D leaders, urgency is the spark that transforms learning from an HR service into a strategic driver of growth.

But maintaining that spark requires deliberate attention. In my interview, Kotter linked the problem to how people learn and evolve over time. “We level off in our forties,” he said, “and when that happens, we don’t see what’s newly important.” His point wasn’t about age—it was about habit. As careers advance, learning often narrows. We become experts in what worked yesterday, not explorers of what might work tomorrow.

This is especially true for senior managers who still equate training with compliance rather than curiosity. They see learning as something employees have to do, not something leaders get to do. The result is an undercurrent of complacency at the very level where urgency should live.

L&D professionals must therefore ignite urgency through connection, not crisis—by linking learning to real performance, customer impact, and organizational purpose. Kotter pointed to leaders like Andy Grove at Intel and Jack Welch at GE, who often created short-term tension (“If there isn’t a crisis, make one”) but then redirected it toward opportunity.

What to do

Frame learning as an enterprise-level advantage, not a departmental expense. Launch visible engaging ‘learning experiments’ tied to strategic outcomes. Communicate wins quickly and vividly—Kotter emphasized short, emotionally charged videos that show success stories rather than explain them.

L&D insight

Urgency is emotional before it is operational. Make people feel the need to grow.

Applying Kotter’s ideas in practice: The Amtrak experience

Years ago, while serving as part of a national Six Sigma initiative at Amtrak, I had the opportunity to put Kotter’s principles into action. I was dedicated to developing a 35-member cross-functional team led by a Six Sigma Black Belt. We used Our Iceberg Is Melting as the foundation for our change management training, translating its fable-based lessons into real-world practice.

The workshop was so engaging that the team adopted a stuffed penguin—just like the one in Kotter’s story—as its mascot. It appeared in team photos, newsletters, and project milestones for years after the seminar, becoming a playful yet powerful reminder of shared purpose.

Over a five-year period, I built a series of developmental challenges for the team that grew to include not only change management, but also communication, persuasion, and collaborative problem-solving. The penguin became a symbol of progress, showing that transformation wasn’t abstract—it was lived.

That experience confirmed what Kotter had long asserted: Lasting transformation depends not on process or technology, but on the human stories we use to make meaning of change.

In Part 2, we’ll turn to the tougher side of Kotter’s message—how to disarm resistance, sustain ‘urgent patience,’ and help teams move from false urgency to real momentum.

References

• Kotter, J. P. (1996). Leading Change. Boston, MA: Harvard Business School Press.
• Kotter, J. P. (2008). A Sense of Urgency. Boston, MA: Harvard Business Press.
• Kotter, J. P. (2014). Accelerate: Building Strategic Agility for a Faster-Moving World. Boston, MA: Harvard Business Review Press.
• Kotter, J. P., & Rathgeber, H. (2006). Our Iceberg Is Melting: Changing and Succeeding Under Any Conditions. New York, NY: St. Martin’s Press.
• Weick, K. E. (1984). Small wins: Redefining the scale of social problems. American Psychologist, 39(1), 40–49.

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In “D&D for Learning: Take Training from Forgettable to Formative,” we looked at why immersive training matters and why your team needs more than just information to make good calls under pressure. In this follow-up, we dive into the how: the tools, tactics, and trade-offs involved in designing immersive training that’s practical, affordable, and effective.

Whether you’re starting from scratch or looking to level up your current approach, this guide will help you evaluate your options and make smart, human-centered choices.

Dungeon master optional: Training in the age of AI

One of the most powerful—and newly feasible—approaches to immersive training is roleplay. When done well, it creates the conditions for people to practice difficult conversations, test judgment under pressure, and build confidence in gray areas where there’s no script to follow.

Until recently, this kind of training was expensive, inconsistent, and hard to scale. But that’s changing. Modern AI-driven roleplay platforms, such as Attensi, blend adaptive scenarios, emotional realism, and performance feedback to help people practice high-stakes conversations before they happen.

Whether delivered through mobile apps, avatars, or natural language AI, these tools simulate real-world dynamics—giving learners the chance to build confidence, empathy, and fluency through experience, not just instruction.

Reemerging every decade or so with better fidelity and new bells and whistles, virtual reality (VR) has increasingly practical applications for training and intervention. Modern VR training platforms create fully immersive environments where learners don’t just see the scenario, they inhabit it. By replicating physical presence and social cues, VR enables deeper emotional engagement, muscle memory, and context-sensitive learning. From managing a conflict to repairing equipment, trainees practice in high-fidelity simulations where failure is safe but the stakes feel real.

COVID provided an opportunity for many organizations to experiment with virtual workplaces, leveraging Metaverse and other platforms for formerly in-person functions including training. These experiments yielded promising results.  According to PwC’s 2022 U.S. Metaverse Survey, employees who trained in immersive simulations were:

• 275% more confident applying what they learned
• 4x faster completing training than in a classroom
• 3.75x more emotionally connected to the material

Simulations, the cornerstone of immersive training, are also becoming more economically and logistically feasible for learners across scale and role. Next generation platforms are expanding what simulation-based learning can do, and who can do it.

Forge, for example, leverages AI to streamline the design process, reducing the time, complexity, and resources typically required to build immersive learning experiences. That efficiency makes it possible to design high-quality simulations for a much wider range of roles, industries, and organizational sizes, without compromising on depth or realism.

Advances in intuitive UI make it easier for learners to engage and for people leaders to facilitate. No-code editing tools allow L&D teams to adjust and evolve their simulations over time.

These advances evolve the simulation value proposition in two important ways:

• Easier facilitating and editing mean L&D leaders get to run the show instead of outsourcing expertise
• Simulations become living tools instead of one-off experiences

The idea of meeting people where they are at is integral to immersive training. Simulation experiences or role-play platforms that tailor to the needs and strengths of teams, that understand, rather than ignore, their unique context and capabilities, and that adapt as circumstances change is the kind of dynamic learning and development critical in a world where business as usual is increasingly unusual.

Evaluating immersive learning

As cost and access barriers fall, the next challenge is making sure what we build actually works.

Immersion is the foundation. But intelligence is what makes the training believable and, ultimately, transformational.

In Dungeons & Dragons, the world isn’t rigidly programmed. It’s co-created in real time through player choices and the asymmetric intelligence of the Dungeon Master. The DM isn’t just enforcing rules. They’re responding, adapting, and reshaping the game based on the party’s decisions.

That’s what makes D&D so powerful as a learning model: Players can prepare, but they can’t prepare for everything. They have to stay sharp. Stay flexible. Think on their feet. They aren’t just playing through the story; they’re shaping it.

Most corporate training doesn’t come close to this level of realism. They’re linear. Predictable. Often reduced to branching paths and canned responses. Learners quickly see the seams. They game the system. The immersion breaks.

In this way, D&D also serves to underscore what we should look for in an effective immersive learning experience. Whether a simulation, a virtual platform, or even an AI roleplay partner, consider whether the solution mimic real-world complexity. In other words, does the experience behave like the real world?

If you’re unsure, here are some things to look for:

Does the experience include unpredictable variability?

Test whether the experience behaves like real life, i.e., with enough complexity and fluidity that a learner can’t just memorize an obvious “right path.” If your participant can memorize the script (or worse, if they’ve already heard it all before), they’re going to disengage.

Twists and turns make a good mystery (and a good campaign). Consider:

• Can someone game the experience just by choosing the most positive or corporate-friendly responses?
• Do different choices lead to different outcomes?
• Are there moments that surprise you?

If none of the above, your experience will struggle to be immersive.

Does the experience display asymmetric intelligence?

For learning experiences that involve interacting with a fictitious customer or colleague, consider whether this non-human collaborator is adaptive.

• Can the non-player characters (NPCs) deviate from the script?
• Do NPCs react in real time based on emotional tone, body language, and phrasing nuance?
• Are there scenarios in which the NPC can shut down, be uncooperative, or be antagonist (like a human)? 

If the experience doesn’t feel like a real conversation, why would a learner put their heart into it?

Does the experience incorporate responsive feedback?

Decisions should have consequences, and those consequences should be logical. Test:

• Do learner decisions have realistic outcomes in the scenario, and are these outcomes carried forward in a way that shapes the scenario?
• Do learner decisions lead to feedback that explores the impact of that decision, not just whether the decision was right or wrong?
• Can the learner fail?

This last question is critical. The potential for failure gives an experience emotional stake, depth, and resonance. And teaching your employees how to fail can as important, if not more, than teaching them how to succeed.

The best way to answer all these questions: Take the product for a real test drive, not a canned demo. Get hands-on. Try to break it. Any product worth the money should jump at the opportunity to show off its capabilities. Any product that doesn’t should be an immediate red flag.

Immersion matters because training matters

The fact is that most people don’t remember the policy manual. We remember moments that felt real, because we were in them, not just learning about them.

That’s what immersion does. It doesn’t just build knowledge. It builds stories. And when the stakes are real, or real enough, those stories shape how we think, how we feel, and how we act when the pressure is on.

If we want training to matter, it has to mean something in the moment. If we want people to grow, we have to give them the space, and the stakes, to practice.

That means investing in immersive learning not as a novelty, but as a necessity. Not because it’s flashy (even if it is!), but because it’s closer to the real work, and therefore closer to the heart.

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Imagine a spotlight on a stage, illuminating a lone figure. This is not just any performer entertaining a crowd. Rather it is an instructional designer in the digital learning arena. The instructional designer has many roles and tasks in a company, like a professional juggler who must keep balls in seamless motion in the air: content, assessments, technology, learner needs, tasks, and deadlines. They strive to not only design engaging learning experiences but also ensure the entire project does not come crashing down.
This article explores how this multifaceted skill set within companies uniquely qualifies instructional designers to manage eLearning projects, offering strategies to master the common challenges of evolving content, subject matter expert collaboration, project complexity, and shifting deadlines.

Project crossroads

Instructional designers stand at the crossroads of andragogy, technology, and communication within organizations. As is to be expected, this unique position makes them ideal candidates for project management, particularly where resources are limited or roles overlap. Instructional designers understand both learning goals and production realities, enabling them to create realistic project plans. It has also become increasingly common for instructional designers to work with multiple groups in companies such as technical teams, multimedia creators, subject matter experts (SMEs), and clients. Therefore, beneath the surface of a finished project lies a complex web of interconnected tasks and collaborative efforts that instructional designers manage.

The management of all the moving pieces in projects typically involves popular project management models, such as a sequential approach to completing tasks or the waterfall model, an agile approach that focuses on flexibility and adaptation, a hybrid approach that combines the waterfall and agile models, or systematic approaches that emphasize planning and organization to ensure project objectives are met.

Although each project management model has a few elements in common such as breaking down projects into manageable stages, continuous engagement with colleagues and clients, goal orientation, adaptability, or documentation and planning, the unique circumstances of each project dictate the choice of methodology to ensure that resources, timelines, and stakeholder expectations are effectively managed and achieve successful outcomes.

Evolving content

Instructional designers should view the evolving nature of eLearning development as an opportunity to enhance the quality of the learning experience. As content evolves and priorities shift, new insights and goals emerge. Importantly, successful teams embrace these changes, which occur throughout a project’s lifecycle—rather than resist them. External factors such as new textbook editions, updated policies, or emerging protocols and laws drive content evolution.

The inevitability of change, therefore, presents a unique opportunity for instructional designers to ensure educational experiences remain comprehensive and current. By adapting to these changes instead of minimizing their impact, instructional designers can create learning experiences that are not only relevant and grounded in real-world contexts but also require fewer revisions and less maintenance over time.

Managing the SME dilemma

Subject matter experts (SMEs) are vital to eLearning projects because they provide accurate, authoritative content and contextualize information with real-world scenarios. However, sometimes instructional design teams and SMEs engage in a power struggle over who is in charge of specific elements in the educational experience for the learners.

To effectively collaborate with SMEs, it is important to treat them as partners by respecting their expertise and acknowledging their time constraints. Strategies for better SME collaboration include:

• Setting clear expectations and roles from the start
• Using structured templates
• Reframing or adapting their input to suit the learner’s perspective
• Keeping meetings brief and action oriented.

These strategies optimize SME contributions, ensuring high-quality and improving relationships. Never should SMEs simply be ignored because they are not considered educational experts. Rather when respect is given to SMEs by instructional design teams, the result is an effective educational experience for learners.

Project complexity

Managing complexity in eLearning projects requires balancing instructional design practices and strategies with multimedia, interactive learning assets, accessibility, platform constraints, learning tools, and a diversity of content and assessments. To manage this complexity, instructional designers must continuously strive to keep organized.

Indeed, many instructional designers tend to create some type of project management system to track their progress and achieve goals. Recently, project management software such as Click Up or Trello have increased in popularity. However, the recognition that project management software may actually hinder progress rather than simply track it usually occurs when the software’s complexity outweighs its benefits. Complex project management tools can demand considerable time and resources for teams to master and frequently update, potentially slowing project momentum and even leading to frustration, especially if the team members have to spend more time managing the project than actually working on the project itself!

This is particularly relevant in eLearning projects that involve SMEs and various groups in an organization across different locations and time zones. To mitigate this challenge, instructional designers should select software that aligns with specific eLearning objectives and offers an intuitive and simple interface to minimize training time and make tracking updates less time-consuming. The best piece of advice is to keep task and project tracking simple. Maintaining simplicity often leads to a better finished product while complexity dilutes clarity and causes confusion among teams.

Shifting deadlines

Risk management is a vital component of project management, often requiring the adjustment of deadlines to address unforeseen challenges. While “risk management” might evoke thoughts of catastrophic failures, experienced instructional design teams recognize that adjusting timelines is crucial for setting realistic expectations, enhancing project outcomes, reducing stress, and allowing flexibility in response to unexpected changes. Fixed deadlines that ignore project dynamics can lead to failures or costly errors.

Instructional designers should align timelines with project complexity to improve productivity and quality, resulting in fewer revisions in the future. Additionally, AI tools can offer data-driven insights to support deadline adjustments, enabling more informed decision-making and improved project outcomes.

Conclusion

Instructional designers are pivotal in navigating the complexities of eLearning projects. Their ability to juggle content, technology, and learner needs uniquely positions them to manage eLearning projects in companies. By embracing change, collaborating effectively with SMEs, and keeping projects organized, instructional designers ensure educational experiences remain relevant and impactful. The pedagogical insight and technological experience that instructional designers bring to companies not only enhances learning experiences but also leads to innovation. As instructional designers continue to adapt and lead, their role will remain essential in shaping the future of eLearning.

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“You should really be using AI.”

If you’re an instructional designer, you’ve probably heard that from a boss, a vendor, or a gushing article on LinkedIn. The pressure is real. This article is my pushback.

I’m not against technology. I’ve been excited about its potential for learning since I wrote my first educational game in 1982 (you earned a point for every multiplication problem you got right; not much of a game, but I was nine and the computer had 16KB of memory).

I’m pushing back against AI for one reason: AI isn’t the future—it’s the present and the past. We’ve been using the parts that work for years—we just called it “predictive text” or “adaptive feedback” (or “Furby”). What’s being hyped as AI today is usually a loose collection of features looking for a purpose and investors.

Microsoft’s Immersive Reader is a perfect example. It was created at a 2015 hackathon by mashing up existing Microsoft tools. The tech never changed, but in 2019—right when early GPT chatbots were making headlines—it was suddenly rebranded as an “Azure Cognitive Service,” which was later renamed the “Azure AI Foundry.” Same code; new costume.

Educators aren’t here to impress investors. We’re here to build learning experiences that make a difference. To help us cut through the hype surrounding AI, I’d like to share four rules I derived from human-centered design (HCD) to guide my own decisions about using AI (or VR, AR, etc.). This isn’t a new framework or a provocation. The rules are a lens that cross-functional teams can use to focus design decisions on learners, rather than flashy features.

1. Solve the real problem

AI isn’t snake oil, but when something is being pitched as a solution for everything from low engagement to high development costs, it’s prudent to ask, “What really is our problem?” What I’ve noticed is that AI tools typically promise to solve business problems, not learning problems. While both matter, we contribute to the bottom line and the quarterly growth target by solving learning problems: helping people gain the knowledge or skills they need to do something they care about.

Some confusion about the real problem comes from the way we often measure outcomes. Because measuring learning directly is so tricky, we regularly measure proxies instead (such as engagement, satisfaction, and completion). These proxies yield critical insights into the health and efficacy of the learning environment, but are not evidence of learning itself.

What’s counterintuitive is that addressing a proxy directly will likely muck it up. For example, if you try to bump up your engagement numbers by adding an AI chatbot, you no longer know if the bump reflects genuine improvement in the module’s relevance, clarity, and challenge, or just the chatbot’s novelty.

Instead, solve the real problem by finding out what is getting in the way of your learners’ engagement. It’s the difference between solving a business problem with learning and merely improving a business metric.

2. Prefer needs over requirements

Remember the hype around the Segway, the scooter that would reshape cities the way the PC reshaped computing? It had cutting-edge technology, heavyweight backing, and lots of buzz.

The only thing it didn’t have was a reason to buy one. It was an innovative product that nobody needed because the Segway was designed to meet producers’ requirements, not the users’ needs.

AI is similarly an innovation looking for someone to need it. The hype is about how powerful AI is becoming and how you can’t afford not to use the latest AI tools. There is less talk about which needs are being addressed. The result is an ill-defined fear of missing out that is increasingly causing AI to be listed, usually in some nebulous form, among the requirements for new learning products (and job descriptions) without considering the needs of learners.

For educators, though, “considering the needs of learners” is central to our work. Learning occurs in one place and time only: inside the learner, when learning meets one of the learner’s needs.

No requirement can mandate learning. Hopefully, your team can work together to align requirements with needs. However, if you find ambiguity or conflict between the two, verify that the requirement is actually required and not merely a hedge against missing out.

3. Apply systems thinking

The world is more complex than we like to admit. We naturally limit our thinking to simple cause-and-effect relationships: you take an allergy pill and the sneezing stops. But you may also fall asleep at your desk.

One action will have multiple, often unintended, effects. Learning is a complex system. Adding something to a learning experience over here causes something that feels unrelated to pop up over there. Applying systems thinking means including as many of those effects as possible when making decisions.

AI only makes the system more complex, especially when vendors can’t tell you how their AI works. It may help you personalize content for more effective learning, but it may also inadvertently perpetuate the biases in the AI’s training or reduce accessibility.

Complexity is unavoidable, but if you aren’t thinking about the side effects of a feature, you end up playing whack-a-mole with learning problems.

4. Prioritize the audience over the show

This rule is a gut check. Who benefits from this feature: the learner or us? There’s no shame in wanting to create something impressive, but don’t confuse that with the mania surrounding anything “powered by AI.” Designing for affect over effect is just theatrics.

I call this the “Avatar Trap.” Yes, it was ground- and record-breaking, but has anyone ever quoted Avatar to you? Meanwhile, my kids yell, “I’m walking here!” without even knowing Midnight Cowboy exists, and finishing the quote, “Life is like a box of…” is practically a reflex.  Spectacle fades no matter how many awards it receives. To make a lasting impression, you need to resonate with the audience.

Learning works the same way. Adding AI-generated variations of ‘correct’ or ‘wrong’ might impress a committee, but not a learner. Microsoft’s Immersive Reader, on the other hand, quickly became the Princess Bride of edtech—no flashy features and no marketing at all, just creators laser-focused on an audience they understood and cared about.

How to use these rules

If your job is solving business problems with learning, the value of your work begins and ends with the change it facilitates in your audience. Human-centered design (HCD) is a mindset for making decisions, whenever possible, based on the needs and values of the human beings we are designing for.

These four rules are a handy HCD lens that cross-functional teams can use to cut through hype and reduce pressure from more peripheral factors. The next time you’re asked to use an AI tool or your team’s discussion turns to using the latest tech, pause and unpack your reasoning by asking yourself and your team:

• Are we addressing the real learning problem?
• Does adding this requirement interfere with any of the learner’s needs?
• Have we considered the effects throughout the system?
• Is this something our learners want, or is it something we want?

There are no simple answers to any of these questions, and that’s okay. The insights you or your team gains by wrestling with them will make you better at your job.

People love to accuse our field of chasing tech fads only to see them fizzle. In reality, we’ve been looting other fields for their tech since the “magic lantern” was used to project anatomy slides in 1685. We don’t need the hype around AI to be excited about its possibilities. When we find a tool that works, we make it work in ways its creators never imagined.

Disclaimer: This content is solely the responsibility of the author and does not necessarily represent the official views of the University of Pittsburgh or the National Institutes of Health.

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By the end of this session, you will be able to:

• Apply liberatory design thinking to create inclusive microlearning that centers psychological safety, belonging, and learner voice.
• Integrate storytelling and generative AI tools (e.g., ChatGPT, 7Taps, Canva) to build emotionally engaging, accessible microlearning modules.
• Create inclusive persona profiles that reflect the diverse identities, needs, and barriers of learners, serving as a foundation for equitable and human-centered learning design.
• Use a UDL-informed framework from design to assessment of the inclusivity, accessibility, and cultural responsiveness of microlearning experiences across formats and platforms.

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• How to catch even subtle accessibility barriers in learning design.
• How small design changes can create a more inclusive experience.
• Practical strategies to apply accessibility principles across all types of learning design.
• The impact of common accessibility barriers from a learner’s perspective.
• How to cultivate a collaborative mindset for design teams to solve accessibility challenges.

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By the end of this session, you’ll be able to:

• Structure your content using techniques that work for screen readers, including how to think critically about headings, groups of links or buttons, and other elements that affect navigation.
• Make strategic decisions about which elements need labels or alt text and which should be marked decorative.
• Write contextually appropriate alt text for different types of instructional images.
• Balance visual design needs with screen reader accessibility.

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In this session, you will learn to:

• Identify common accessibility pain points in eLearning development.
• Leverage AI tools to support accessibility tasks such as alt text generation, captioning, and contrast analysis.
• Integrate accessibility checks into your instructional design workflow with AI-assisted tools.
• Recognize ethical challenges when using AI for accessibility and apply human-centered review practices.

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Whether you’re building asynchronous modules, facilitating virtual sessions, or supporting SMEs, you’ll gain a practical approach for making your learning content more inclusive—and more effective—for everyone. By the end of this session, you will be able to:

• Identify assumptions in your current teaching approach that may create barriers for some learners.
• Apply the plus-one strategy to add one new content delivery option and one alternative assessment method to existing training.
• Create an implementation plan for incorporating plus-one improvements into your next course or module.

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You will leave this session with an understanding of:

• How to use the Checklist to ensure accessible, inclusive, and WCAG-compliant eCourse development.
• An enhanced understanding of Storyline- and multimedia-specific programming techniques.
• Greater confidence in your understanding of accessibility and ability to apply inclusive design principles.

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