In manufacturing companies and technical service organizations, a significant share of performance depends on hard-to-replace field expertise: diagnostics, adjustments, work methods, edge cases, operational reflexes, client relationships, equipment knowledge, and problem-solving. When that expertise lives primarily in the heads of a few experienced employees, the organization becomes vulnerable. Departures, retirements, absences, or role changes can result in the loss of critical know-how, slow down onboarding, and undermine execution quality. AI can help transform this tacit knowledge into a structured asset: knowledge bases, internal assistants, dynamic guides, business search engines, enriched documentation, and decision-support tools. But the value depends first on the organization's ability to capture, validate, organize, and govern its internal knowledge.
47%
of Quebec SMBs have started at least one concrete AI use case
62%
of leaders believe their data is insufficiently structured for AI
31%
have formal governance around generative AI tools
AI maturity in the enterprise - 2025 → 2026 evolution
Identified and prioritized AI use cases







