Solving the Expertise Gap with AI in Manufacturing - with Antoine Bisson of Poka

2026-04-06 · Source: The AI in Business Podcast · Field: Manufacturing & Industrial — Smart Manufacturing & Industry 4.0, Manufacturing Operations & Management, Automation & Robotics · Depth: Intermediate, extended

Summary

Poka CEO Antoine Bisson discusses how manufacturers can address the widening execution gap on the factory floor, caused by retiring experienced workers and new operators expecting digital support. Poka, a connected-worker platform, digitizes work instructions and training, using AI to convert legacy knowledge into structured content and deliver real-time contextual guidance. The platform aims to modernize training and onboarding, moving beyond paper-based processes to provide consistent, real-time support. AI-generated instructions significantly compress ramp-up time for new employees, stabilize execution, and reduce reliance on long-tenured experts. This approach helps standardize knowledge capture and validation, strengthening continuity and enabling a shift from reactive to proactive operations.

Key takeaway

For Directors of AI/ML or Operations Professionals facing expertise loss and inconsistent training, prioritize implementing connected-worker platforms that leverage AI for knowledge capture. Focus on converting critical "tribal knowledge" into structured, AI-generated work instructions, starting with high-value use cases like onboarding or specific maintenance tasks. This strategy will accelerate new employee ramp-up, stabilize performance, and enable a more proactive operational posture, ensuring continuity as experienced workers retire.

Key insights

Digitizing tribal knowledge with AI transforms manufacturing training and operations, bridging expertise gaps.

Principles

• Knowledge capture prevents expertise loss.
• Digital tools must suit modern worker expectations.
• AI augments human capabilities, it doesn't replace them.

Method

Capture expert videos, use AI to generate structured work instructions with safety checkpoints, and validate with human oversight to ensure accuracy and safety in critical operations.

In practice

• Convert legacy paper instructions to digital formats.
• Implement video-based training for new hires.
• Focus on 1-2 high-ROI use cases for AI adoption.

Topics

• Connected Worker Platforms
• Expertise Capture
• Generative AI in Manufacturing
• Digital Work Instructions
• Frontline Productivity

Best for: Director of AI/ML, Operations Professional, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI in Business Podcast.