AI in Action for Small and Medium-Sized Enterprises

The Issue

Canada’s AI paradox is well documented: world-leading research strength coexists with uneven adoption, particularly among small and medium-sized enterprises (SMEs). Yet even this gap is difficult to pin down precisely. Reported adoption rates vary widely, depending on definitions, from 12.2% in Statistics Canada surveys focused narrowly on use of AI in operations, to 71% in Microsoft’s broader measure that includes generative AI tools. A 2024 BDC survey found that 39% of SMEs self-reported using AI, but the figure rose to 66% when concrete examples were provided. These discrepancies highlight how definitional differences and underreporting shape our understanding of adoption.

This gap is not only a question of technology but a question of competitiveness. SMEs are the backbone of the Canadian economy, yet many lack the resources and capacity to adopt new tools at the pace of larger organizations. Artificial intelligence has the potential to address these challenges by streamlining operations, reducing costs, and strengthening customer relationships, but many firms are not yet realizing these benefits.

These variations underscore that adoption may be underreported, yet they also highlight that a significant gap remains. Even as some SMEs experiment with AI, many others lag behind. Closing this adoption gap is essential if Canadian SMEs are to compete effectively. More work is needed to help SMEs understand the “use case” –  where AI tools can be applied in their operations and to ensure they have the skills, support, and confidence to implement them.

The rationale for this bulletin is to showcase concrete use cases of SMEs across industries implementing AI tools at different stages of the value chain and achieving impactful results. By highlighting diverse applications, the bulletin provides practical evidence that adoption is both feasible and beneficial, offering SMEs clear models to follow.

What We Investigated

This project set out to document and analyze real-world applications of AI in SMEs, focusing on practical impacts across the business value chain. Key questions included:

• How are SMEs applying AI in everyday operations?
• What measurable benefits are being achieved in terms of efficiency, productivity, service quality, and cost savings?
• Which sectors and functions are leading adoption, and what lessons can be drawn?

The research compiled a diverse set of case studies spanning inbound logistics, operations, outbound logistics, marketing and sales, customer service, procurement, HR, technology development, and firm infrastructure. The selection includes Canadian and global (e.g., UK, Europe, USA, etc.)  SMEs across agriculture, manufacturing, services, retail, etc. The cases were collected and synthesized into a bulletin published in September 2025.

What We’re Learning

The findings show that adoption is not a distant goal but an active reality for many SMEs. Key lessons include:

Operations: AI strengthens core production processes by automating repetitive tasks, improving quality control, and reducing downtime. These tools allow SMEs to achieve consistency, cut costs, and reduce reliance on scarce skilled labour. For example, Pièces d’autos Fernand Bégin improved process efficiency by 20 percent and cut labour costs by 15 percent with AI-enabled data systems, while Patates Dolbec raised sorting accuracy from 70 percent to 95 percent with AI-powered quality control.

Workforce management: AI improves scheduling, staffing, and training, enabling SMEs to optimize limited human resources. This reduces administrative burdens and ensures more effective use of personnel. For instance, Bien Chez Soi cut scheduling time by 68 percent, reduced vacant visits by 42 percent, and increased caregiver hours per workday by 25 percent, which directly expanded client capacity. Promark Electronics also cut new-hire training time in half and achieved a first-pass yield above 95 percent after introducing AI-powered digital work instructions.

Marketing and sales: AI allows SMEs to personalize outreach, predict customer needs, and automate campaigns that would otherwise require significant staff time. These applications help smaller firms compete with larger players by increasing conversion and order value. JENNY BIRD, for example, grew upsell revenue by 8.5 percent and boosted average order value by 58 percent, while Brava Fabrics achieved 101 percent growth in online sales after automating email flows. Three Ships Beauty tripled purchase likelihood among quiz takers, with customers 3.5 times more likely to buy after using its AI-powered skin analysis tool.

Customer service: AI-supported tools enhance responsiveness and free staff from routine tasks, providing round-the-clock service while maintaining quality. This improves both customer satisfaction and revenue generation. At Simba Sleep, an AI agent handles the workload equivalent of eight full-time staff, generating £600,000 in monthly revenue while ensuring continuous support (over $1,100,000 in Canadian dollars). Suitor, a small suit rental business, reduced response times by 97 percent, from around 3 minutes to 6 seconds, with an AI agent that now handles up to 85 percent of customer queries automatically.

Infrastructure and compliance: AI is also transforming less visible but critical functions such as compliance, finance, and risk management. By automating complex reporting and analysis, SMEs can save time and redirect staff effort toward higher-value activities. For example, Nolinor Aviation reduced compliance investigation time from 40 hours to 5 by introducing an AI-enabled assistant investigator.

These lessons show that AI tools are adaptable across industries and functions. Adoption can be incremental, addressing specific challenges first, and scaled over time. Partnerships with technology providers often accelerate the process, making AI accessible even for traditional or resource-constrained SMEs.

Why It Matters

The evidence demonstrates that AI adoption is achievable, beneficial, and increasingly necessary for SMEs. The benefits are broad: streamlined operations, increased productivity, cost savings, and stronger customer relationships.

For policymakers and funders, these cases confirm that targeted interventions to reduce barriers, particularly skills development, awareness building, and trust frameworks, are critical to scaling adoption. For SME leaders, the cases provide concrete, replicable models that show how even small investments can yield significant returns.

At a system level, accelerating adoption among SMEs is central to Canada’s competitiveness and productivity agenda. Without broader uptake, the country risks falling behind peers who are already integrating AI into everyday business practice.

State of Skills:
Unleashing AI into the Skills Development Ecosystem

FSC-supported AI tools have bolstered outcomes in skills matching, career development guidance, and recruitment. The overall effectiveness of these tools was underpinned by recognizing and mitigating the inherent bias and discrimination embedded into these technologies.

Read Thematic Report

What’s Next

This bulletin is part of a broader effort to close Canada’s AI adoption gap. While it highlights successful use cases, the work is ongoing. A forthcoming report will provide a new AI Competency Framework. Together, these resources aim to equip policymakers, funders, and SME leaders with practical insights and actionable tools.

• Build on this bulletin by expanding the library of SME AI case studies, offering practical examples across more sectors.
• Connect findings directly with skills and training initiatives, ensuring SMEs have the literacy and capacity to adopt.
• Disseminate insights widely through SME networks, sector associations, and policy channels to demystify adoption and accelerate uptake.