By George Hall
Recently, stories began circulating about AI-powered “monks” capable of answering spiritual questions with surprising depth and fluency. They could discuss philosophy, generate reflective responses, interpret teachings, and seem wise—convincingly enough that many people found the interaction unsettling.
Most people reacted to this as a technology story. Learning professionals should probably read it differently, because the deeper issue is not whether AI can simulate expertise.
What Is Expertise?
It clearly can. The deeper issue is what happens when expertise becomes separable from the developmental process through which it was traditionally earned.
For centuries, wisdom was assumed to emerge slowly through:
- Experience
- Reflection
- Context
- Relationships
- Failure
- Adaptation
- Lived “complexity”
Now, a machine can instantly produce many of the outward signals of wisdom. That fact, much like the existence of the AI monk, should force an uncomfortable question for organizations: What kinds of expertise still matter when information, summaries, frameworks, and even simulated insight become endlessly available?
I found myself thinking about that question while revisiting an interview I conducted with management thinker Karl Albrecht. Our discussion focused on organizational intelligence, leadership, systems, and a concept he called “collective stupidity.”
Rereading the interview now, in the context of AI, many of his observations feel strikingly relevant to the future of learning and development.
Early in the conversation, Albrecht challenged the assumption that organizations naturally become smarter over time. In fact, he argued the opposite: “Collective stupidity is not new: It has always existed, but it’s probably just now becoming more apparent.”
His explanation was not that organizations had suddenly become worse but that they had become more complex. And complexity exposes weaknesses that simpler systems could once conceal.
AI Reveals Systemic Weaknesses
Unfortunately, that observation feels especially important today. Because AI dramatically increases organizational complexity while simultaneously increasing the speed of decision-making, communication, and information generation. Learning organizations can now create:
- Personalized development pathways
- AI-generated coaching prompts
- Leadership simulations
- Adaptive learning content
- Remarkably fluent knowledge systems
All at extraordinary scale. But scale does not automatically create intelligence. In fact, Albrecht warned that organizations often become less intelligent precisely because, using traditional management approaches “They suddenly stop seeing people as people and start seeing them as objects.”
That observation lands differently in the AI era. Because organizations now face subtle temptations to:
- Confuse data about people with understanding people
- Mistake behavioral prediction for wisdom
- Assume that because systems can generate sophisticated recommendations, human judgment itself becomes less important
Albrecht always argued the opposite. Throughout the interview, he repeatedly returned to the idea that organizations become more intelligent when they recognize human beings as “centers of intelligence” rather than simply functions inside a machine. That distinction matters enormously for learning professionals.
For decades, many workplace learning systems were built around industrial assumptions:
- Standardize behavior
- Increase consistency
- Improve compliance
- Scale efficiency
- Reduce variation
Do these goals seem familiar—in an industrial-factory sort of way? These goals still matter. But AI increasingly handles exactly those kinds of structured, repeatable processes well.
The Value of Expertise
Which raises a more difficult question for L&D: What forms of expertise remain uniquely valuable when information itself becomes abundant?
Albrecht hinted at the answer while discussing leadership models. One of the major failures of traditional leadership theory, he argued, is that, “They tend to leave out the idea of context.”
That observation may be one of the most important lessons for modern learning organizations because expertise rarely operates in abstraction. Real judgment is contextual:
- The effective leader in one environment may fail completely in another.
- The successful strategy in one system may collapse in another.
- The same behavior can produce trust in one context and resistance in another.
This is precisely where many development programs unintentionally oversimplify expertise. They teach models that are detached from lived complexity. They teach competencies as isolated behaviors rather than as adaptive responses shaped by context, relationships, and systems.
But as Albrecht explained, “A leader is a Leader in a Context.”
That distinction becomes more important—not less—in an AI-enabled workplace. AI can increasingly provide information. What it cannot fully provide is our exquisite human discernment. We have a unique ability to:
- Interpret context
- Read tension
- Understand competing pressures or values
- Navigate ambiguity and
- Make responsible judgments under uncertain conditions or pressure
Ironically, the rise of intelligent systems (AI) may make these deeply human capabilities even more valuable. Not, however, because AI lacks sophistication. But because organizations still depend on people to:
- Interpret meaning
- Build trust
- Understand culture
- Navigate systems
- Adapt responsibly as conditions change
Albrecht also warned against simplistic “fix-the-organization” thinking. Reflecting on his consulting approach, as external consultant, he explained, “We don’t try to come in and ‘fix’ the organization; I don’t think we can.”
Instead, he described his work as forming “a lasting, learning relationship” with leaders and teams. That perspective feels deeply relevant to modern L&D.
Learning as ‘Guided Evolution’
Because learning itself may increasingly need to be understood less as content delivery and more as guided evolution, starting immediately, L&D needs to help organizations:
- Become more adaptive
- Become more reflective
- Become more context-aware
- Adapt to conditions of extreme complexity
Revisiting Albrecht’s interview now, what strikes me most is that he never described organizational intelligence primarily as information accumulation. He described it as something more difficult: “Organizational intelligence is the ongoing human capacity to interpret complexity wisely inside evolving systems.”
And in an era increasingly flooded with generated knowledge, that may become the expertise organizations value most.
Image credit: Brothers 91
