Balancing Learning Science and AI Innovation with Laura Dermody of Boston Consulting Group
This episode of Learning Leader Spotlight features a conversation with Dr. Laura Dermody, Director of Platform and Solutions at Boston Consulting Group. The dialogue explores how learning science, organizational upskilling, and rapidly evolving AI tools intersect in today’s learning and development landscape. Throughout the episode, Dermody offers a grounded, human-centered perspective on what is changing, what remains constant, and how L&D teams can navigate complexity while supporting meaningful performance growth.
Dr. Laura Dermody brings a multifaceted background spanning K–12 education, higher education, ed tech, and corporate upskilling programs. After beginning her career as a classroom teacher, she spent a decade in academic and student affairs roles at institutions including Ohio State University and Vanderbilt University. She later transitioned into online program development at Pearson, Anthology, and similar providers before joining Boston Consulting Group. In her current role, she leads technology, product, and platform solutions for BCGU, the firm’s global upskilling division serving corporate, public sector, and citizen reskilling initiatives worldwide. Her work centers on designing impactful, customized learning experiences that align with organizational strategy and measurable capability building.
The Pace of Change in L&D Is Outpacing Expectations
Dermody notes that although AI dominates current conversations, the more profound shift is the exponential speed at which tools, expectations, and workflows evolve. Even for professionals whose role is to stay informed about learning technologies, the landscape feels overwhelming. She emphasizes that while modalities and content creation capabilities have changed dramatically, foundational learning science principles continue to anchor effective design. Core models such as backward design, applied learning frameworks, and evaluation methodologies remain essential despite accelerating innovation.
Applied, Embedded Learning Remains Critical in Corporate Contexts
A recurring theme in Dermody’s work is the need to connect learning directly to the learner’s real work. She outlines a foundational, applied, embedded framework that parallels but adapts Bloom’s Taxonomy for corporate settings. Effective upskilling requires understanding the tools, workflows, and constraints of each organization so learners can apply new concepts immediately. Dermody’s teams tailor use cases, capstones, and learning-in-action activities to actual job tasks, ensuring the experience never feels abstract or disconnected from business outcomes.
Corporate Learners Navigate Different Realities Than Students
Dermody compares her time in higher education to current work with professional learners. In academic settings, learning is the student’s primary responsibility; in corporate environments, learning must compete with full workloads. A summer internal upskilling initiative at BCGU helped her team appreciate firsthand how even well-designed programs can overwhelm working professionals. This insight reinforced the need for succinct content, targeted application, flexible pacing, and intentional prioritization.
AI Creates New Opportunities but Also New Complexity
While AI tools can automate certain tasks and improve content creation efficiency, Dermody highlights that overall complexity has not decreased; it has shifted. Learning professionals must understand what AI tools can and cannot do, how to validate outputs, and where human oversight is indispensable. She also stresses that many organizations invest heavily in AI technologies but see limited return because workforce upskilling is insufficient. Technology alone is ineffective without training, adoption, and human-centered change management.
Personalization and Skill Data Are the Next Frontier
Dermody envisions a future where organizational learning pathways adjust dynamically to each learner’s prior knowledge, performance, and work context. Realizing this vision requires ethical and sophisticated data ecosystems, which remain challenging for many companies. She notes that personalized learning has been discussed for decades, but achieving true customization at scale requires better integration between learning systems and workplace systems. Emerging technologies in skills verification and ambient assessment show promise, but human-centered design and data privacy considerations remain critical.
Learning Trends Shaping the Future – What Learning Leaders See Coming Next
Practical Takeaways for L&D and Business Leaders
1. Anchor Innovation in Learning Science
As AI tools proliferate, Dermody emphasizes that core principles of learning design still guide successful outcomes. Leaders should ensure teams are grounded in backward design, application-based learning, and established impact evaluation models before layering technology enhancements. Innovation is most effective when paired with rigorous discipline around outcomes, learner context, and instructional quality.
2. Design for Working Professionals, Not Idealized Learners
Corporate learners absorb training amid competing priorities. Short modules, clearly framed relevance, real-world application tasks, and flexible delivery increase completion and usefulness. Leaders should question whether every component of a learning experience is essential, and consider pilot-testing with internal teams to reveal hidden burdens or bottlenecks.
3. Treat AI as a Skillset, Not Just a Toolset
Dermody underscores the importance of hands-on experimentation with AI tools. Strategic AI literacy is now relevant for nearly every role. Leaders may benefit from encouraging teams to explore tools in low-risk environments to understand limitations, hallucinations, or workflow opportunities. Pairing exploration with ethical and responsible use guidelines helps teams adopt AI in meaningful and sustainable ways.
4. Prioritize Human Skills as Technology Accelerates
Even as AI handles more routine processes, critical thinking, interpretation, and meaning-making become more important. Dermody frames these as core liberal arts abilities that help professionals adapt to rapid change. Leaders should protect time and space for strategy, reflection, and complex problem solving rather than assuming technology will simplify everything.
5. Invest in Data Infrastructure for Future Personalization
To realize personalized and embedded learning, organizations will need strong data architecture connecting skills, performance, and workflow insights. Leaders should begin exploring what data is collected, how it is shared, and how to manage privacy responsibly. Early moves in this direction will position organizations to take advantage of increasingly sophisticated learning technologies in the years ahead.
He also underscores the power of emotion in creating lasting impressions. Even in topics that may seem dry or technical, emotional engagement helps form the mental connections that allow ideas to stick. This emotion can be positive, but it can also surface through challenge or discomfort if designed thoughtfully.
The final component, targeted specificity, ensures that learners receive content that directly relates to their context, eliminating wasted time and cognitive overload. When these three elements converge, learning shifts from routine information delivery to an experience that remains in memory and influences behavior.
Finding Your Next L&D Leadership Role
Optional Resources or Tools Mentioned
Closing Reflection
Throughout the episode, Dermody offers a thoughtful balance between enthusiasm for AI-enabled innovation and conviction that human-centered learning science remains essential. Her experiences across education, ed tech, and corporate learning reveal a consistent message: the fundamentals of how people learn are stable, but the environment around them is changing rapidly. L&D leaders who blend grounded expertise with curiosity, experimentation, and strategic data thinking will be best positioned to support their organizations’ evolving skill needs.
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