Sean Bengry
Senior Learning and Development Leader
DaVita Kidney Care
Episode 149
Future of learning: AI demands a new 'idea economy' mindset
Current chapter: Built by People podcast features insights from world's top HR leaders
Built By PeopleJune 12, 2025 · 14:50
Thesis
“Artificial intelligence is a 'general platform technology' that will fundamentally transform how we learn, shifting the value from mere knowledge acquisition to understanding and application in an 'idea economy,' requiring proactive preparation through integrated knowledge graphs and an adaptable mindset in L&D.”
Show notes
AI is a "general platform technology" — the kind that reshapes entire economies rather than just automating specific tasks. Sean Bengry has been making this argument in the L&D space for years, long before it became a conference keynote. His case: when knowledge becomes a commodity, the economy's value shifts to understanding and application, and learning programs that still optimize for knowledge transfer are building on a foundation that's rapidly eroding beneath them.
Sean's career has moved through four phases — build, manage, consult, lead — each deepening his technical and human-centered toolkit. At PwC, he built a customized learning platform for the cybersecurity practice that aggregated external certifications, vendor content, and internal development into role-specific playlists at every level and career milestone. At Accenture, he applied human-centered design principles to a large-scale learning transformation: prototype carelessly, measure ruthlessly, share credit generously. The result was measurably improved engagement and performance in a population that had been chronically underserved by generic programs.
His vision for AI in L&D is concrete, not futuristic: a well-formed knowledge graph where instead of searching folders for a policy document, employees just ask a question and get the answer. The technology exists. What's missing, in most organizations, is the information architecture that makes it work. Building that architecture now — before the AI layer arrives — is the most consequential thing an L&D leader can do.
- AI as a general platform technology — what that means for how we design learning programs
- The shift from knowledge to understanding — why content-heavy L&D is becoming obsolete
- Human-centered design in practice — prototype carelessly, measure ruthlessly, share credit generously
- Building knowledge graphs for AI-ready learning — the infrastructure work that prepares organizations for intelligence management
- Being T-shaped in an L&D career — why breadth plus deep expertise is the most durable professional architecture
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What you'll take away
- 1AI is a 'general platform technology' that will profoundly reshape learning, moving the economy from knowledge as a commodity to understanding and application.
- 2Proactively build a well-formed information or knowledge graph to prepare for an 'intelligence management strategy' where AI layers can provide real-time learning assistance.
- 3Adopt a human-centered design approach in L&D by focusing on business metrics, prototyping carelessly, measuring ruthlessly, and sharing credit generously.
- 4Recognize the symbiotic relationship between design and technology, using learning as the linchpin to balance them and enhance human capabilities.
- 5Develop a 'T-shaped' skill profile – deep in one domain for effective leverage of technology, and wide in curiosity and continuous learning for future adaptability.
What most organizations get wrong
- •Knowledge is becoming a commodity; the future value will be in understanding and application, ushering in an 'idea economy'.
- •Elegant design dies without technology, and the coolest technology is pointless without design, emphasizing a necessary symbiotic relationship rather than prioritizing one over the other.
In Sean's words
“We put together a learning technology platform that aggregated both the external, internal certifications from various vendors, as well as added our own internal learning and development pieces to create customized playlists for each level and each milestone that a person in that practice would have to go through.”
This highlights a practical and impactful application of learning technology to solve specific business and career development challenges.
“Always keeping the, both the learner and the business at the center. So you should always be falling in love with the question, what business metric am I moving with this? This learning problem, learning challenge, and then prototype carelessly, measure ruthlessly, and then share the credit generously.”
This provides a clear, actionable framework for incorporating human-centered design principles into training programs.
“Instead of people looking for the right file that captures the information that they're looking for, they actually just ask the question, where, what is the answer to this? How do I do this thing? What is this policy all about?”
This illustrates the transformative shift from document retrieval to real-time, conversational learning enabled by AI-layered knowledge graphs.
“Artificial intelligence right now is a GPT, and most people understand that as ChatGPT, but it's not that GPT that I'm talking about. I'm talking about a general platform technology.”
This offers a compelling re-framing of AI's fundamental nature, emphasizing its pervasive impact on all aspects of life and work.
“Elegant design dies without technology, to be honest with you, in this day and age, you can have the beautiful thing, but if it doesn't do anything and it doesn't provide any affordances or provide a a better way or a capability for me as a person, it just dies. So elegant design dies without tech. I would also say that the coolest tech is completely pointless without design.”
This powerful statement underscores the critical, symbiotic relationship between design and technology in creating truly effective solutions.
The problems this episode addresses
- •**Inefficient Certification Tracking**: Organizations struggle to efficiently track and verify employee certifications (especially in fields like cybersecurity), hindering their ability to respond to RFPs and win new business.
- •**Information Silos & Discovery Challenges**: Knowledge workers waste time searching for critical information (files, templates, policies, procedures) across disparate systems, impacting productivity and real-time learning.
- •**Outdated Learning Measurement**: Traditional L&D metrics (SCORM, LMS, LXP) are becoming inadequate for measuring true learning, performance, and accomplishment in an evolving, AI-driven 'idea economy'.
In this episode
Built by People podcast features insights from world's top HR leaders
Built by People
I tend to break my career journey around 4 different phases
4 Phases of My Career
Sean, can you tell us about a time where you leveraged technology to solve a challenge
How Technology Solutions Solved the Talent Development Challenge
Sean, how do you incorporate human-centered design into training programs
How do we incorporate Human-centered Design into Training Programs?
Sean, can you tell us about a learning design strategy that improved engagement and performance
Employee Learning Design Strategy
Sean: We leveraged technology to enhance the learning experience for employees
How Microsoft Learning Experience Can Be Leveraged by AI
How do you see artificial intelligence shaping the world of learning and development
How AI is reshaping the world of learning and development
Sean Miller says elegant design dies without technology
Sean Conway on the Intersection of Design, Technology, and Learning
Topics covered
Organizations and entities mentioned
Full transcript
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