ANALYSE SECTORIELLE

Automation, AI, and Performance Management in Franchise Networks

Franchise networks and multi-location businesses are increasingly turning to automation and AI to strengthen performance tracking, analyze sales data, optimize inventory, and support local managers. These technologies represent real opportunities for a sector where consistency across locations and speed of execution are critical

8 min readJune 1, 2026Commerce & Franchise

At a glance

Franchise networks and multi-location businesses are increasingly turning to automation and artificial intelligence to improve performance tracking, analyze sales, optimize inventory, and support local managers.
These technologies represent real opportunities for a sector where consistency across locations and speed of execution have a direct impact on results.
But these technologies do not create value on their own.
They depend on reliable data, clearly defined processes, and a level of consistency across locations that many networks have not yet fully established.
Many networks approach automation and AI by first evaluating what available technologies can do: which tool could forecast demand to adjust orders, which solution could automatically analyze customer feedback, or which system could generate alerts when a location deviates from its usual standards.

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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

58%

42%

AI-ready data

Key dimensions

The structural issues covered in this analysis, grouped by theme.

Franchise networks and multi-location businesses are increasingly turning to automation and artificial intelligence to improve performance tracking, analyze sales, optimize inventory, and support local managers. These technologies represent real opportunities for a sector where consistency across locations and speed of execution have a direct impact on results.

But these technologies do not create value on their own. They depend on reliable data, clearly defined processes, and a level of consistency across locations that many networks have not yet fully established.