Scaling AI in Canadian business: A confident and responsible path forward

 

Transformation

Canadian businesses are navigating a unique convergence of pressures: record wildfire seasons, an increasingly complex regulatory patchwork across provinces, accelerating cyber threats, and customers who expect more, faster. Artificial Intelligence (AI) offers a way to respond with greater speed and precision, yet many organizations rest between ambition and action, held back by privacy, reliability, and governance concerns. The challenge is clear: how do you scale AI in a way that delivers real value without outpacing trust?

The rise of AI

In just a few short years, Artificial Intelligence (AI) has evolved at a pace that few technologies have ever matched. Moving from experimental use to becoming a core part of how people work, communicate, and make decisions, AI today is automating repetitive tasks, supporting complex analysis, and reshaping industries and daily life.

Across the globe, adoption is accelerating. Businesses are investing in AI not only to improve efficiency, but to unlock new ways of working, from real-time decision-making to predictive insights that drive strategy. A 2024 article by Bloomberg noted that the world’s largest technology companies collectively spent more than $200 billion building AI infrastructure. This surge reflects a growing consensus: AI is not a passing trend, but a transformative force that is reshaping the global economy.

AI in Canadian business

Across Canada, organizations are under growing pressure to do more with less while responding to a rapidly changing risk environment. Extreme weather events are increasing in frequency, cyber risks continue to evolve, regulation is becoming more complex, global instability is disrupting supply chains, and customers expect faster, more consistent service across provinces.

AI is emerging as a key tool to meet these demands. In 2025, Statistics Canada reported that 12.2 percent of Canadian businesses reported using AI to produce goods or deliver services, doubling from just 6.1 percent the year before. Adoption is strongest in information and cultural industries, consulting and advisory firms, and finance and insurance, where roughly one in three businesses are already using AI in some capacity.

As AI becomes more accessible, businesses are integrating it into core operations. Common applications include text and data analytics, virtual agents, marketing automation, and voice recognition. These tools are helping organizations respond faster to customer needs, improve forecasting, and streamline decision-making. Importantly, counter to common misconceptions, AI adoption is not leading to widespread job losses. Statistics Canada notes that nearly 90 percent of businesses that implemented AI reported no change in employment levels, while 40 percent redesigned workflows and 39 percent trained staff to work with AI tools. This shows that AI is reshaping how work gets done, not replacing the people who do it.

From pilots to practice

Despite AI’s vast potential, few organizations have become truly AI-native. Many Canadian businesses remain in the pilot phase, experimenting with AI in pockets but not yet driving value at scale. This cautious approach stems from three main concerns: data privacy and security, the reliability and accuracy of AI outputs, and the challenge of adapting the workforce to new ways of working. Companies know they must unlock AI’s benefits safely and responsibly, ensuring that innovation does not outpace governance or erode stakeholder trust.

These challenges are real, but they are not insurmountable. With strong data stewardship, transparent governance, and targeted training, businesses can move from experimentation to execution with confidence. Canada is already laying the foundation for responsible AI use. The federal government’s Voluntary Code of Conduct for Advanced AI Systems highlights safety, transparency, and human oversight, principles that align closely with the expectations of regulated industries. Canada's evolving regulatory landscape, including the proposed Artificial Intelligence and Data Act (AIDA) and Quebec's Law 25, signals that governance expectations will continue to rise. Organizations that build strong frameworks now will be better prepared as these requirements take shape.

Building AI maturity is a gradual, structured process that requires clarity of purpose, disciplined experimentation, and a solid foundation of governance and skills. Successful organizations will take a deliberate approach, following the framework below:

1. Democratize AI: AI should not be confined to a small group of specialists. Employees across all functions should be equipped with user-friendly tools, training, and the confidence to use AI effectively. By democratizing access, companies embed innovative thinking into their culture and ensure AI-driven improvements can come from anywhere in the organization.
2. Identify high-value use cases: Rather than starting with the technology, start with the business challenges. Map value chains and pinpoint where AI can deliver the greatest impact, whether through automating a manual process, generating deeper insights, or reducing a key risk. By focusing on a few high-potential areas, organizations can achieve quick, measurable wins that build internal credibility.
3. Invest in robust data: The output of any AI system is only as good as its input data. Ensuring high-quality data is essential. That means data should be relevant, accurate, well-labelled, up-to-date, and free of bias.
4. Experiment and learn safely: Pilot projects should run in controlled environments with strong oversight. Test small, fail fast, and learn quickly. By experimenting in sandboxes or limited user groups, teams can observe outcomes and address issues before wider rollout. Maintaining human oversight ensures that AI outputs are reviewed, lessons are captured, and improvements are made. This builds confidence that successful pilots can scale.
5. Invest in skills and change management: Upskilling employees is critical to AI maturity. By equipping teams with both the technical and soft skills needed to navigate AI, organizations ensure they can interpret outputs, recognize bias, and adapt workflows. Equally important is change management. Leaders should position AI as a tool for empowerment by involving employees early, addressing concerns, and sharing success stories. Many organizations designate “AI champions” or cross-functional teams to support adoption and build confidence across the business.

Throughout these steps, data security and governance must remain top priorities. Safety means ensuring AI systems are robust and do no harm, transparency means explaining AI decisions to stakeholders, accountability means clear ownership and oversight of outcomes, and reliability means AI does what it is supposed to do, consistently and without bias. These principles mirror the expectations of Canadian regulators and customers.

What this means for your insurance program

As AI becomes more deeply embedded in business operations, it is also becoming part of the conversation with insurers. How an organization governs, deploys, and oversees AI is increasingly relevant to how risk is assessed, particularly in Canada, where regulators like the Office of the Superintendent of Financial Institutions (OSFI) are raising expectations around technology risk and operational resilience.

This is not about penalizing adoption. It is the opposite. Businesses that can demonstrate strong AI governance, clear accountability, sound data practices, ethical safeguards, and transparent decision making are signalling operational maturity and resilience. In an environment shaped by increasing pressures facing Canadian businesses, that signal matters. Organizations that invest in these foundations are not only managing risk more effectively, they are also positioning themselves favourably when it comes to securing coverage and demonstrating resilience to stakeholders.

The smart shift

AI is no longer a distant, futuristic concept. It is a reality that is reshaping industries, redefining how decisions are made, and opening new paths to growth. As its capabilities continue to evolve, the question for businesses is not whether to adopt AI, but how to do so with purpose and care.

In Canada, the case for action is clear. Businesses are facing a variety of mounting pressures. AI offers a way to respond with greater speed, sharper insight, and more efficient operations. For those willing to invest in the right foundations, the opportunity to scale their business is significant.

At Zurich Canada, we are putting these principles into practice across our business, from how we assess and price risk to how we support our brokers and customers. Our focus is on supporting innovation while providing clarity and confidence in an evolving environment.  If these themes resonate with your organization’s journey, contact Zurich Canada to continue the conversation.