[DSC Europe 25] Dragan Vucic - Building the Learning Organization - How AI Transforms Knowledge Processes.pptx

[DSC Europe 25] Dragan Vucic - Building the Learning Organization - How AI Transforms Knowledge Processes.pptx

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  Building the Learning Organization:How AI Transforms Knowledge Processes Author: Dragan Vucic, Cyclos Systems
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  I. The FoundationalChallenge II. The AI Paradox: Risk & Provocation III. The Executive Playbook: Three Strategies IV. The Mandate Agenda
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  The Theoretical Ideal:Senge’s "Learning Organization" The goal: To build an organization "where people continually expand their capacity to create the results they truly desire." — Peter Senge, The Fifth Discipline. Systems Thinking Seeing the whole ecosystem, not just the silos. Personal Mastery Clarifying personal vision and objective reality. Mental Models Deeply ingrained assumptions that influence how we act. Shared Vision A common identity and destination for collective effort. Team Learning "Thinking together" to create collective intelligence. The AI Challenge: Can we maintain "Systems Thinking" when the system includes non-human agents?
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  The Currency ofthe Organization: Tacit vs. Explicit Knowledge Knowledge is not a monolith; it is an iceberg. Explicit Knowledge (The Tip): • What it is: Documents, code, databases, manuals. • Properties: Easy to codify, store, and transfer. • AI Role: AI is Superhuman here. It processes this instantly. Tacit Knowledge (The Mass Below): • What it is: Intuition, experience, "unwritten rules," context, judgm • Properties: Sticky, personal, hard to articulate. • AI Role: AI struggles here. This is the domain of the Human Expe
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  The Pathology: Hiding,Losing, and the "Corporate Brain Drain" Before we discuss AI, we must acknowledge why organizational learning fails human-to-human. Knowledge Losing ("Corporate Amnesia"): • The Issue: When experts leave, their tacit knowledge leaves with them. • The Cost: We repeat mistakes and lose • "decision-making context." Knowledge Hiding (The Intentional Barrier): • The Issue: Employees intentionally withhold knowledge to maintain power, status, or job security. • The AI Risk: As employees fear AI replacement, Knowledge Hiding may increase. Why train your replacement?
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  The Vision: FinallyRealizing "The Learning Organization" For 30 years, Peter Senge's "Learning Organization" was an ideal. AI makes it a reality. Peter Senge's 1990 Vision • Defined by 5 disciplines, notably Systems Thinking. • Limited by lack of data visibility. • "Team Learning" was often siloed. 2025 Reality: AI-Powered Evolution • AI provides infrastructure for Senge's vision. • Transforms "episodic learning" to "continuous reflection." • Enables "Superagency" – amplifying human intent.
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  The Provocation: "CognitivelyOffloading" Your Future The "Autopilot" effect is no longer theoretical. Cognitive Offloading “Significant negative correlation" between frequent AI tool usage/ increased reliance on AI tools and critical thinking skills. Mechanized Convergence Focus exclusively on performance warns of "Mechanised Convergence"—a lack of diversity in output and a shift from creation to verification. The Paradox: AI accelerates output but erodes the process of learning.
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  The Knowledge Dynamics:Tacit vs. Explicit AI excels at Explicit Knowledge (documents, code), but organizations thrive on Tacit Knowledge (intuition, experience, context). Combination — Explicit to Explicit (AI is superhuman) Internalization — Explicit to Tacit (AI is transformative) Externalization — Tacit to Explicit (AI is emerging) Socialization — Tacit to Tacit (AI is dangerous)
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  The Mechanism: AI’sDisruption of the SECI Model How AI impacts the 4 phases of Knowledge Conversion (Nonaka & Takeuchi): Socialization Tacit to Tacit DANGEROUS: This relies on human friction and mentorship. When juniors ask AI instead of seniors, this critical loop breaks, hindering new tacit knowledge generation. Externalization Tacit to Explicit EMERGING: GenAI can now automatically codify "unwritten rules" from video/audio, solving the "Knowledge Losing" problem. Combination Explicit to Explicit SUPERHUMAN: AI synthesizes vast datasets instantly, , transforming raw information into structured knowledge., so scaling "Systems Thinking.“ Internalization Explicit to Tacit TRANSFORMATIVE: It helps humans absorb and internalize codified knowledge, converting explicit information into practical and skills. If we use AI only for efficiency, we kill Socialization, creating a "sterile" organization where no new tacit knowledge is generated
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  Strategy 1: Mastering "Externalization"(Stopping the Brain Drain) Don't ask experts to write manuals. Use AI to watch and learn. 1. Assess Identify "Knowledge Losing" risks (e.g., retiring experts). 2. Capture Record video walkthroughs and structured interviews ("Think Aloud"). 3. Codify Use GenAI to autonomously analyze transcripts, extract logic, and structure it into KCS articles. 4. Scale Deploy an AI Coach that answers questions using only this verified, expert-derived content.
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  Strategy 2: Building"Super-learners" (The IBM Case Study) Fight Skill Atrophy with Competency-Based Strategy AI as Guide Recommends personalized learning from over 300,000 resources. Human as Agent Employees complete 40+ hours/year of learning. Business as Validator HR systems correlate learning outcomes ("Badges") with business performance.
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  Strategy 3: Governanceas an Enabler & Knowledge Protector The Imperative: Governance is not a cost center; it is the protection layer against Epistemic Decay. The Hidden Risk: Epistemic Decay AI's intelligence is parasitic. If governance fails, the knowledge base suffers from decay/ "generative fluff" and outdated data., training AI systems on dangerously outdated snapshots. Leadership Mandate: Protect the Foundation • Human-Centric Design: Involve non-technical staff (HR, Legal, Sales) within development pods. • Define Accountability: Designate individuals responsible for AI tool elements, as AI cannot be held accountable.
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  The New Frontier:Generative Knowledge Creation Moving beyond Retrieval (RAG). Today: Retrieval-Augmented Generation (RAG) • Function: AI retrieves answers from your existing, authoritative knowledge base. • Goal: Efficiency, fighting hallucinations. (Finds what we know.) Today /Tomorrow: Knowledge Creation (Deep Learning/GenAI) • Function: AI uses Deep Learning to analyze "large, unlabeled and unstructured data sets" to find complex patterns. • Goal: Innovation, discovery. (Discovers what we don't know.)
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  The Call toAction: The Leadership Barrier Path 1: Status Quo or the Atrophied Organization Path 2: The Learning Organization Automate tasks, ignore "Knowledge Hiding," and accept Cognitive Atrophy, Competency Debt, Socialization failure. You get efficiency, but you lose your mind. Don't just automate. Elevate. Use AI to Externalize tacit knowledge, Internalize new skills, and build Superagency.