Podcast Summary: Rewiring Workflows and the Real Work of AI Transformation with Markus Bernhardt of Endeavor Intelligence
When you listen to Markus Bernhardt talk about artificial intelligence, one of the first things you notice is how grounded his perspective is. He is not selling hype or chasing trends. He is focused on what is real. He is focused on what organizations are truly experiencing as they attempt to adopt AI. And he is focused on the fact that most companies are experimenting faster than ever yet struggling to see meaningful results.
In this episode of the Learning Leader Spotlight, Markus joins TrainingPros President Leigh Anne Lankford for a candid and eye-opening discussion on the state of AI in the workplace. With humility and humor, Markus shares how he became one of the earliest voices in the learning field to speak about AI, long before crowded conference sessions and viral headlines. Today, as the Principal of Endeavor Intelligence, he helps senior leaders navigate AI decisions with clarity and confidence. His approach is simple. Look at the evidence. Study what actually works. Build strategies around real-world behavior and real organizational systems.
Throughout their conversation, Markus explains why many companies feel stuck, what leaders tend to overlook, and how L&D can play one of the most important roles in the future of work. His core belief is refreshing. The real work of AI transformation does not start with technology. It starts with people, with workflows, and with the decisions that teams make every day.
From Early Curiosity to a Career Guiding Leaders Through AI Change
Markus describes himself as a strategic advisor who supports leaders making high stakes decisions about AI and workforce transformation. But his journey began long before AI became a mainstream topic. Years ago, he was one of the few people in learning and talent development who wanted to talk about AI at conferences. He remembers presenting to half empty rooms about a then unfamiliar model called GPT 2. At that time, it was difficult to imagine how quickly the landscape would change.
Even so, Markus saw the potential immediately. He believed these emerging tools would reshape how people access information, how they make decisions, and how organizations operate. That early interest prepared him well for the moment when AI shifted from niche curiosity to an everyday work tool. When GPT 3.5 gained popularity and leaders started asking urgent questions, Markus was ready. He had already spent years studying AI through the lens of performance, behavior, and organizational systems.
He founded Endeavor Intelligence with that purpose in mind. His work focuses on what he calls applied workforce solutions. These are solutions that support real-time performance, learning in the flow of work, and measurable outcomes. Rather than studying concepts, he studies what truly happens in workplaces. He examines tools, workflows, and case studies to understand how AI can actually improve performance. He combines that research with a practical model he calls the Two Wave Transformation, a framework that helps leaders separate activity from impact.
The Two Wave Transformation Model: A Clear View of Why Organizations Get Stuck
One of the most recognizable ideas Markus has developed is the Two Wave Transformation Model. The model came from what he observed inside real organizations. Leaders were launching pilots, hosting training sessions, buying tools, and rolling out dashboards. From the outside, it looked like momentum. But inside the organization, not much was changing.
“We saw a massive, costly disconnect,” Markus explains. “Organizations were showing plenty of AI activity but no real business change.”
To help leaders understand the difference between visible progress and true transformation, he created two concepts.
The Surface Wave
The surface wave includes everything people can easily see. New dashboards, pilot programs, training sessions, and quick wins fall into this category. These activities help build initial awareness and are useful for early literacy. They help people become comfortable with AI, and they introduce the organization to new possibilities.
However, the surface wave has limits. It is comfortable because leaders can measure it. They can count the number of pilots. They can count the number of people trained. But surface level activity does not fundamentally change how work gets done.
The Undercurrent
The undercurrent is where transformation becomes real. It involves the deeper structural work that organizations often avoid. This includes mapping workflows, redesigning decision rights, clarifying data needs, identifying bottlenecks, and redefining roles. These changes touch areas of power and authority. They require collaboration across business units. They involve political conversations about who owns decisions, who signs off, and who manages risk.
The undercurrent is demanding, and for that reason, many organizations hesitate to go there. But according to Markus, this is the only place where AI can create true impact.
“You cannot transform a workflow by only introducing new tools,” he says. “You transform when you redesign how work is done.”
Trends in Learning & Development:
Insights from Learning Leaders
Why Tools Alone Cannot Transform Work
As Markus explains, AI transformation is not a technology problem. It is a leadership and behavior problem. When people receive a new tool, the first thing they do is apply it to their old habits. They use AI to write emails, summarize documents, or speed up familiar tasks. They work more efficiently, but the work does not change.
After several weeks of experimenting, a shift begins. People start thinking differently. They begin seeing patterns and opportunities that were not visible before. They realize that they can redesign how they work, not just speed up how they work.
AI literacy helps people understand what the tools can do. AI fluency helps people imagine what new workflows might look like.
Markus gives a practical example. In many organizations, sales teams use AI to generate call summaries. That saves time. But the real transformation would be redesigning the approval process so managers can approve discounts on the spot, based on AI verified data. This change reduces friction, improves customer experience, and eliminates unnecessary delays. It is a workflow redesign, not just a tool adoption.
According to Markus, the biggest breakthroughs come when teams gain fluency and begin asking new questions. These questions include:
- What insights can AI surface that were never visible before?
- Where are we slowing ourselves down with outdated approvals?
- What decisions could move faster without compromising quality?
- How could our work look different if we trusted the system more?
These questions open the door to the undercurrent, where the real work begins.
How Data and Workflow Mapping Help Build Confidence
Another major topic Markus highlights is the importance of understanding data. Many organizations delay automation until they believe they have perfect data. Markus disagrees with this approach.
“There is no such thing as a perfect data lake,” he says with a smile. “It is always out of date.”
Instead of waiting for perfect conditions, he encourages leaders to examine the data within a single workflow. Identify where the information lives and who verifies it. Determine what level of data quality is needed for the workflow to function. These decisions form what he calls data contracts. They provide clarity about where data should come from and who is responsible for maintaining it.
This is particularly important in workflows like insurance claims. Automating small claims is often possible if the necessary data is clean and easy to access. These early wins help teams build confidence. They learn how automation behaves. They identify gaps. They find opportunities to improve. They grow more capable of redesigning more complex workflows in the future.
Markus emphasizes that automation does not remove the need for people. Instead, it shifts people into higher value work. Instead of spending time on repetitive steps, team members monitor processes, adjust for exceptions, and make judgment calls that technology cannot handle.
The Expanding Role of Learning and Development Professionals
As AI reshapes the workplace, Markus believes L&D professionals are stepping into an increasingly strategic role. Learning teams have long supported skill building. Now they must also guide cultural and structural change.
According to Markus, L&D has two essential responsibilities.
Building Workforce Fluency
L&D must help employees develop both literacy and fluency in AI. People need to understand what the tools can do and how to use them responsibly. They also need encouragement to imagine new ways of working.
Facilitating Governance and Cross Functional Collaboration
L&D is uniquely positioned to bring together leaders from across the organization. These conversations are often sensitive because they involve power, decision rights, and risk. But without them, organizations remain stuck in the surface wave. L&D can help teams talk openly, align on goals, and focus on the human side of AI adoption.
Markus acknowledges that L&D teams are often stretched thinly. Many are responsible for compliance training, leadership development, onboarding, and other critical functions. But he also believes that well-chosen AI tools can free up time and allow L&D to become a strategic partner in transformation.
A Practical Starting Point for Teams Ready to Begin
During the conversation, Markus offers a concrete suggestion for any L&D team looking to apply his model right away. He recommends starting with content localization. Localization is time consuming, expensive, and often a major bottleneck for global organizations.
In one case study from his Endeavor Report, a company used an AI enabled authoring tool to reduce localization costs by twelve times. This allowed the team to reallocate time and resources toward projects that required deep strategic thinking.
Markus believes the best starting pilots share several qualities. They are small, well-bounded, and measurable. They offer clear improvement potential. And they help teams learn how to evaluate workflows, data, and bottlenecks.
The Leader’s Mindset: Focusing on Change, Not Activity
One of the most encouraging parts of the conversation comes when Leigh Anne asks Markus what advice he would give to leaders who feel overwhelmed by AI. Markus responds with a principle that resonates across industries.
“Do not count activity. Start measuring your change.”
Activity is not the same as progress. Leaders should stop focusing on how many tools they purchased or how many training sessions they held. Instead, they should focus on where work is slowing down, where decisions get stuck, and where employees feel frustrated. Those points of friction are opportunities for redesign.
Markus often advises teams to choose one workflow and map it. Identify what decisions are made, who makes them, what data is required, and what steps could be simplified. Some workflows will not be good candidates for automation. That is not a setback. It is information that will help leaders make better choices next time.
He adds with warmth, “Your first workflow is unlikely to be a winner. If it is, call me. I want to celebrate that with you.”
Resources Markus Recommends
Markus has spent years researching what drives workforce transformation. When asked which resources he trusts most, he highlights several that guide his thinking.
The Endeavor Intelligence Reports
These semiannual Endeavor Intelligence Reports are filled with real world case studies, client led examples, and detailed analyses of workflow transformation. They help leaders understand the true impact of AI in modern organizations.
The Learning Guild
Markus has partnered with the Learning Guild for years. Their research papers, conference sessions, and industry studies remain valuable sources of insight for learning professionals.
Harvard Business Review
Harvard Business Review (HBR) offers deep research on leadership, organizational behavior, and decision making. Markus considers it a key resource for leaders who want to understand the human side of transformation.
Peer Communities and Executive Roundtables
Markus frequently participates in cross-industrial roundtables where leaders share what is working and what is not. These sessions offer candid insights that rarely appear in published research.
Academic Research in Psychology and Decision Science
Because trust and human judgment play such an important role in AI adoption, Markus draws heavily from academic studies in behavioral science and organizational psychology.
These resources reflect his belief that successful AI transformation blends technical capability with human understanding.
Looking Ahead: The Last Inch Challenge
Toward the end of the episode, Markus shares a preview of his latest research focus, which he calls the last inch. While the last mile refers to solving technical challenges like getting the right data into the system, the last inch focuses on the human side of AI. It is the moment when an employee receives an AI recommendation and must decide whether to trust it.
For Markus, the last inch may be the most important challenge of all. Even if the AI makes a strong recommendation, employees may hesitate to act on it if they do not trust the system or if they do not feel psychologically safe. If people retreat to old processes during high stakes moments, organizations lose the full benefit of their investments.
Closing this gap requires clear communication, responsible use of data, transparent workflows, and cultural support. When employees feel confident and safe using AI, organizations move closer to real transformation.
Final Thoughts
Throughout this conversation, Markus demonstrates a rare blend of vision and practicality. He understands the complexity of AI, yet he keeps the focus grounded in people. His insights challenge leaders to rethink activity-based measures of progress and commit to the deeper work of redesigning workflows and decision rights.
For L&D professionals, his message is uplifting. Learning teams play a central role in helping the workforce build fluency, shaping governance conversations, and supporting leaders through change. With the right mindset, L&D can help guide organizations through one of the most significant workplace shifts of our time.
TrainingPros extends its appreciation to Markus for sharing his expertise and for inspiring learning leaders across industries. In honor of his contribution, TrainingPros is pleased to plant five trees in his name. His work continues to influence how organizations approach AI, performance, and the future of the workforce.
Listen to the full interview with Markus here.
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