Artificial Intelligence

Closing Polanyi’s Paradox: How Frontline AI Tools Capture Tacit Workplace Knowledge

· GlobeWire Daily Editorial Desk · Source: www.techradar.com

2 min read

Key takeawaysFrontline workers across retail and warehouse operations rely on undocumented, tacit knowledge to manage daily tasks, exceptions, and practical workarounds. According to commentary and general academic studies cited in industry discussions, a significant majority of company knowledge remains unwritten in official manuals. Traditional top-down standard…
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Frontline workers across retail and warehouse operations rely on undocumented, tacit knowledge to manage daily tasks, exceptions, and practical workarounds. According to commentary and general academic studies cited in industry discussions, a significant majority of company knowledge remains unwritten in official manuals. Traditional top-down standard operating procedures often fail to capture this expertise, which can lead to knowledge gaps when experienced staff leave an organization.

Reports indicate that the introduction of frontline artificial intelligence tools and AI knowledge agents is helping organizations surface these long-overlooked gaps. Rather than relying solely on centralized teams to draft manuals, companies are exploring bottom-up approaches to crowdsource institutional knowledge from the workforce.

Key Concepts in Frontline Knowledge Management

  • Tacit Knowledge: Practical know-how based on experience, muscle memory, and situational problem-solving.
  • Standard Operating Procedures (SOPs): Traditional top-down guidelines that often miss frontline realities.
  • Bottom-Up Crowdsourcing: Using AI assistants to let workers flag inconsistencies, suggest updates, and capture operational insights.

Practical Implications and Verification

  • Continuous Learning: Organizations are shifting from one-off onboarding sessions to ongoing training models, sometimes referred to as "everboarding."
  • Multimodal AI Agents: Modern tools may support voice, text, image, and video interactions, allowing workers to verbally highlight gaps or photograph operational setups for instant comparison against official plans.
  • On-Device Inference: Smaller models running locally can help keep data secure within company networks while reducing latency.

To verify original claims or announcements regarding enterprise AI deployment, stakeholders should consult primary vendor documentation, peer-reviewed organizational research, and official corporate governance reports rather than relying solely on promotional summaries.

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Read the original source: Crowdsourcing the corporate brain: Closing polanyi’s paradox on the frontline

AI-assisted reporting; source claims are attributed and have not been independently verified.

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GlobeWire Daily Editorial Desk — AI-assisted news based on attributed published sources.

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