FCC Thought Leadership exploring AI opportunities for Canadian agriculture and food

A soon-to-be-released report from Farm Credit Canada suggests that ecosystem factors, rather than access to technology, are delaying AI adoption in Canadian agriculture.

Artificial Intelligence (AI) is no longer a future concept for agriculture and food. Around the world, AI is already being used to optimize inputs, manage risk, improve yields, strengthen supply chains, and support more resilient food systems. Yet in Canada, progress remains uneven. Adoption is advancing in pockets, but system-wide impact has been lagging.

On July 14^th, FCC Thought Leadership will release a new report, AI In Canadian Agriculture: Present Challenges and Future Prospects, that will explore what AI could mean for Canadian agriculture and food. The report looks beyond individual technologies to examine how AI fits into the broader agriculture and food ecosystem that supports producers, processors, agribusinesses, and the institutions that connect them.

As the agriculture and food sector faces mounting pressure from climate volatility, labour constraints, geopolitical uncertainty, and rising costs, the question is no longer whether AI has potential. The more pressing question is whether Canada is positioned to capture that potential in a way that strengthens productivity, resilience, and competitiveness over the long term.

Canada has strong foundations, but progress is uneven

Canadian agriculture enters this new digital era with clear advantages. The sector is supported by a globally trusted food system, a strong research base, world-class AI expertise, and a growing agriculture and food innovation ecosystem. Canadian producers have also shown a willingness to adopt new tools when they are practical, well-tested, reliable, and economically viable.

At the same time, adoption of AI and other digital tools across the Canadian agriculture and food sector remains uneven across regions, commodities, and stages of the value chain, and lags other industries. While some businesses are integrating advanced analytics, automation, and decision-support tools, others face barriers related to infrastructure, skills, cost, and uncertainty.

Figure 1: Businesses reporting use of AI as of second quarter of 2025 – agriculture, forestry, fishing and hunting vs. all other industries

Source: Statistics Canada

These differences raise important questions. Why do promising technologies move quickly in some areas but struggle to scale across the system? What conditions help AI solutions move from pilots to everyday use? What risks emerge as agriculture becomes more data-driven and digitally connected?

AI is more than a technology question

AI adoption in Canadian agriculture is not simply a question of access to tools; it is closely tied to how well the broader ecosystem supports innovation, commercialization, and adoption.

AI depends on high-quality data, reliable connectivity, skilled labour, investment, and clear rules around governance and accountability. Weaknesses in any of these areas can limit uptake, even when the technology itself is ready. In practice, this means progress with AI often reflects the strength of the broader innovation ecosystem within a sector.

Figure 2: AI innovation ecosystem

Source: FCC Thought Leadership

This is especially important in agriculture and food, where operations are highly interconnected and exposed to risk from factors like weather, shifting market conditions, biosecurity concerns, and global trade uncertainty. As AI becomes embedded across the value chain benefits to businesses increase, but so do dependencies and vulnerabilities. Understanding how these pieces fit together is essential for determining how AI can deliver durable value rather than isolated success stories.

A moment of choice for Canadian agriculture and food

Internationally, peer countries are moving quickly. Many are pairing AI adoption with coordinated investment, shared infrastructure, and sector-specific policy frameworks. These efforts aim to reduce uncertainty for producers and businesses while accelerating the movement of solutions from research into real-world use.

Canada now faces a strategic moment. AI has the potential to strengthen decision-making on farms, improve coordination across value chains, enhance risk management, and support long-term competitiveness in export markets. The caveat is this: realizing those benefits at scale will depend on choices made today, not just by technology developers, but across industry, government, and finance. This includes decisions about how data is governed, how risks and responsibilities are shared, how innovation is supported, and how producers are equipped to engage with increasingly digital systems.

What the full report will explore

The upcoming report from FCC Thought Leadership examines the current state of AI in Canadian agriculture and food, the conditions shaping its adoption, and the opportunities that could emerge with greater coordination and clarity. Drawing on research, data, and perspectives from across the agriculture and food innovation ecosystem, the report looks at AI not as a standalone innovation but as part of a living system that must grow together in a balanced and resilient way.

The report does not offer simple answers. Instead, it raises essential questions about what kind of AI-enabled future Canada wants for its agriculture and food sector, and what it will take to get there.

The full report will be released on July 14^th. Stay tuned as FCC continues the conversation on how artificial intelligence could help shape the next chapter of Canadian agriculture and food.

Article by: Bethany Lipka, Senior Economist