Whether it’s entertainment or logistics or accident prevention, there isn’t a corner of our lives that AI hasn’t touched, and that includes the automotive sector. Our writer takes a helicopter view of how AI is changing things up across multiple platforms.
By Rohit Narayan Sholingur
Canada’s automotive industry, which has relied on traditional supply chains and manufacturing methods, is undergoing a substantial and groundbreaking transformation. Artificial intelligence (AI) is now a key factor in this shift. From real-time design modeling to predictive maintenance and autonomous driving cars, AI is changing how vehicles are designed, built, and used. This transformation is happening amid changes in global politics and new trade barriers. Recent data from the Canadian Vehicle Manufacturers’ Association (CVMA) shows that the automotive sector adds over $19 billion to the national gross domestic product (GDP) each year, making this technological shift important both economically and strategically.
AI’s integration into manufacturing is already significant. Public data from Canadian original equipment manufacturers (OEMs) like Magna International and Linamar shows that companies are using AI simulations in their design processes. These allow engineers to test new vehicle designs in virtual settings. The simulations use telemetry and crash data to evaluate safety, weight distribution, and energy efficiency well before creating a physical prototype. This is particularly crucial for optimizing electric vehicle (EV) platforms, where AI balances battery placement, structural integrity, and aerodynamics to comply with regulations and performance requirements.
In Canada’s manufacturing facilities, AI is changing quality control and operations. For example, news releases from Stellantis and Ford Canada note that machine vision systems now check components on the assembly line, detecting flaws more precisely than human inspectors. These systems work alongside predictive maintenance algorithms that assess sensor data from machines to predict breakdowns before they happen. This reduces expensive downtime and boosts productivity. These AI applications are becoming essential components of plant operations throughout Ontario and Quebec.
AI’s impact extends beyond manufacturing. In cities like Toronto and Vancouver, startups such as Waabi and SkyDrive AI are developing Level 4 autonomous technology for crowded urban areas. Their systems interpret traffic patterns and connect with smart infrastructure to tackle issues like congestion and reducing emissions. In a country where over 80% of the population lives in cities, this goes beyond innovation; it is becoming critical for public policy.
Here’s where the real-world perspective adds more depth:
In a dealership environment, AI applications are more complex. Niki Figliano, vice- president of Westowne Mazda, says that although there is efficiency to be achieved with AI, customer acceptance is inconsistent. He explains how the dealership previously contracted with a company that provided AI scheduling for its service department. The system took more calls than staff could answer, but customers didn’t care for the lack of human interaction.
“Quite often, people would ask for a human adviser. Otherwise, they’d hang up, ring back, or send an e-mail, since they weren’t satisfied with the AI response,” he said.
As such, Westowne Mazda reverted to an on-live call-center to better align with customer expectations.
Figliano also noted that AI still plays a part in customer contact: the company uses it to answer questions and pursue inactive leads.
“Sometimes they come in asking for that person, the AI, by name, her name is Amy. So, they’ll come in and say that they’d like to see Amy. So anyway, we know that it’s working more on the sales side than on the service side.”
But he reiterated that automated, yet human contact remains essential to generating customer trust and satisfaction.
Looking farther ahead, Figliano wondered how autonomous vehicles could change the whole motive industry. He speculated that the field would consolidate to the extent that brand distinctions wouldn’t matter as much, and automobiles would simply be a form of shared transportation.
“At that point, it really doesn’t matter, there’s no status symbol… In my opinion, what will happen with automotives is that it’s just transportation.”
But he wondered if today’s infrastructure is capable of that kind of change, arguing that Canada’s roads remain too crowded for complete autonomous use.
When asked about features in modern day Mazda vehicles that might be stepping-stones to full autonomy, he emphasized the importance of existing features such as front obstruction warning sensors, lane departure systems, blind spot monitoring, and radar cruise controls. To him, these features put the industry on the threshold of autonomy yet tell us how incremental progress is bridging the gap.
“This is already the basis for that. So maybe it will happen sooner than we think that the cars will be driving themselves because they already have all this technology available.”
Figliano predicts dealerships themselves might radically alter in a standalone future: fewer cars will be purchased outright, but servicing will still be done, but the traditional concept of a dealership may be altered or cease to exist.
From the perspective of the Electric Vehicle Association of Atlantic Canada (EVAAC), AI is already making a clear mark on the Canadian electric vehicle (EV) market. Kurt Sampson, executive director of EVAAC, explained how, while it can be difficult to isolate AI from base computing in practical applications, EVs are at the forefront of integrating AI onto the platforms. He cited Tesla as an example, noting how the firm has been investing in AI across its entire platform for years now.
“Tesla has been embedding AI across their system for decades, and it’s certainly helped them maintain a position at the exponentially growing forefront in areas such as range estimation, onboard navigation, battery charging, charging infrastructure, battery lifespan, and of course active vehicle safety systems.” Sampson explained.
Sampson points out that AI has a greater effect beyond efficiency. Although it can enhance battery performance, optimize charging, and make things better, he anticipates the most revolutionary change to come from autonomous driving. He noted that AI plays a role at every point in the EV chain, spanning R&D, production, daily use, and end-of-life recycling.
“But where I believe we are going to be witnessing most of the shake-up and impactful change driven by AI is in the form of autonomous driving. We stand on the cusp of a revolution that will transform the motor industry forever.”
In terms of consumer concerns, including charging availability and grid reliability, Sampson said AI would prove to be a powerful tool in achieving EV adoption balancing with infrastructure readiness. AI can maximise charging station deployment, coordinate EV-grid synchronization, and tap renewable energy sources to both reduce electricity costs while minimising emissions.
“AI definitely will be utilized to optimize the way EVs and EV chargers interact with the grid to help to smooth the demand off the grid and pull the maximum potential for clean generation sources like solar and wind. Ultimately, this puts downward pressure on electricity prices and helps reduce emissions and electricity costs.”
Sampson referred to the necessity of cooperation between AI developers and local Canadian EV companies. He stressed that the potential of AI is still nascent and that Canadian innovation should not be dominated by foreign platforms.
“Effective integration of AI will definitely be the deciding factor in making or breaking numerous companies in the future, and we shall see this happening a lot in the transport industry as we move towards a connected, autonomous, shared, and electric—CASE future,” he added.
In the long term, Sampson admits that AI is at the heart of electric autonomous fleets, though social acceptance, regulation, and infrastructure pose major challenges. He further notes that while autonomous vehicle technology is growing exponentially, regulatory and society maturity will always be behind.
“AI will definitely aid in the implementation of supporting infrastructure, but past experience tells us that social acceptance and regulation always come along well after new technology.”
In the end, Sampson concludes that AI is already a differentiating factor in the EV industry, guiding the way to a future transportation system that is connected, autonomous, shared, and electric.
“AI is already a significant part of the EV ecosystem for many of us,” he says. “Successful AI development and deployment will continue to be a key differentiator as we transition to this new paradigm of transportation options.”
These observations from both Westowne Mazda and EVAAC paint a vibrant picture of how AI is remodeling and revolutionising the Canadian auto industry simultaneously. To legacy dealerships, the message is clear: while AI can bring efficiency with scheduling, lead management, and customer interaction, human touch cannot be substituted. Shoppers and buyers alike continue to prefer dealing with individuals in person, and dealerships must be able to put AI into their process without losing trust or the human aspect that is at the core of customer satisfaction.
At the opposite end of the spectrum, the EV sector illustrates how AI is transforming vehicles today as much as it is working to ready tomorrow’s mobility infrastructure. From optimising battery life and charging facilities to synchronisation with green power grids, AI is making electric transport intelligent and sustainable. Its most revolutionary effect, however, is on autonomous driving—where the technology is already changing at a runaway pace even as regulation, infrastructure, and acceptance are trailing behind.
Bringing these threads together, the AI story in Canadian automotives is one of balance: technology with confidence, automation with human oversight, and cutting-edge technology aligned to social and regulatory needs. AI is not just a productivity tool; it is a change driver. Wherever – in the showroom or on the road – the destiny of transportation will depend on the extent to which the industry can reconcile technology with human needs as drivers, passengers, and community members.
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In June 2025, the federal government’s Strategic Innovation Fund announced new funding rounds to speed up AI development, especially in the automotive sector. As noted in a Government of Canada news release, officials highlighted Toronto’s growing AI and tech communities and reaffirmed investment in projects that connect research and commercialization. These efforts strengthen Southern Ontario’s reputation as a key center for smart transportation systems and next-generation vehicle testing.
As the industry modernizes, it must also address the need for a fair transition. CVMA reports stress that while AI boosts efficiency, it also alters workforce dynamics, requiring upskill programs and inclusive labour policies. By linking public funding with workforce development, Canada aims to ensure that automation enhances rather than replaces jobs, particularly in vital areas like Windsor, Oshawa, and London.
Higher education institutions are essential in this environment. Universities like Toronto, McGill, and Waterloo have nurtured top-notch AI research talent, much of which flows directly into industrial use. The Vector Institute has collaborated with automakers to turn academic discoveries into practical AI applications. These institutions not only provide a talent pipeline but also help Canada stay competitive globally, especially as other countries invest heavily in similar fields.
Importantly, Canada is pairing technological progress with careful planning. Research efforts at the Vector Institute and other think tanks are working to lessen algorithmic bias in autonomous decisions, improve the transparency of AI models, and incorporate privacy into connected vehicle systems. This commitment to responsible AI positions Canada as a leader in innovation and a model for governance in the era of machine intelligence.
AI adoption is not exclusive to large manufacturers. Through the Automotive Parts Manufacturers’ Association (APMA), small and medium-sized enterprises (SMEs) are also using AI in their operations. Project Arrow, APMA’s zero-emissions concept vehicle, highlights how AI can optimize supply chains, enhance virtual prototyping, and personalize user interfaces. Project Arrow is Canada’s very first zero-emission concept vehicle to be designed and built from end- to- end within Canada, and it is serving as a testbed for next-generation automotive technologies, including AI-based systems. Based on publicly released reports, the project has attracted participation from various Canadian automakers, research institutes, and technology partners to go after innovations in virtual prototyping, supply chain optimization, and user interface design. With the use of AI in the design and testing phase, Project Arrow allows engineers to simulate real-world environments, forecast component behavior, and optimize vehicle systems before actual production. Significantly, it also demonstrates how small- and- medium enterprises (SMEs) can employ AI tools to optimize production, individualize features, and respond more rapidly to market demands. With Project Arrow, Canada is not just showing technological leadership but is setting an actual world model for the adoption of AI within the broader automotive sector.
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Canada’s AI-driven automobile sector is now facing new challenges, particularly from shifting trade dynamics. According to the Government of Canada (April 8, 2025), the U.S. imposed a 25% tariff on Canadian automobiles effective April 3, 2025, followed in May by an equivalent tariff on motor vehicle parts unless they qualified as compliant under the Canada–UnitedStates–Mexico Agreement (CUSMA). In response, Canada introduced countermeasures from April 9, charging 25% on U.S.-built non-CUSMA vehicles and on the non-Mexican or non-Canadian component of CUSMA vehicles. While not aimed at EV parts or AI systems, they have disrupted decades-old supply chains and added complexity for Canadian Tier-1 suppliers.
Given Canada’s heavy reliance on U.S. exports, this trade tension carries significant risks. According to Reuters (April 15, 2025), while such deals as the Comprehensive Economic and Trade Agreement (CETA) with the European Union (EU) and the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) present alternative market access for Canada, none provide the magnitude or integrated scale of Canada-U.S. car trade. As a result, various manufacturers are revisiting compliance tactics to weather the new tariff environment, balancing CUSMA requirements with higher global market expectations. This added complexity highlights the changing geopolitical reality propelling the use of AI and next-generation technologies in Canada’s auto sector.
Although challenges persist, long-term growth opportunities are strong. This strength is underpinned mainly by deep-seated structural trends such as technological progress, demographic transition, and changing consumer values. In the meantime, expanding market opportunities in both established and newer industries continue to provide impetus. Together, these factors suggest that the outlook for growth is not only stable but also on track for sustained improvement over the next few years.
In a 2024a report titled “Real Talk: How Generative AI Could Close Canada’s Productivity Gap and Reshape the Workplace—Lessons from the Innovation Economy”, published by The Conference Board of Canada,, generative AI can potentially drive the national economy by as much as close to two percent of GDP. Headquartered in Ottawa, O.N.,, The Conference Board’s report identifies that technology hubs such as Toronto, Waterloo, and Vancouver will be the largest beneficiaries. Although the study is not particularly focused on the automobile industry, it indicates how sectors such as manufacturing, transportation, and mobility can also be prime gainers of AI-driven productivity gains. This underlines the reality that AI adoption within Canada’s automotive sector could progress at a very rapid pace, driven both by consumer demand and local economic objectives.
AI will also be crucial in helping Canada reach its environmental targets. With a national goal to end sales of internal combustion engine vehicles by 2035, managing EV charging infrastructure, energy storage, and vehicle-grid integration will rely heavily on intelligent systems. AI tools that can forecast charging patterns and optimize interactions with renewable energy sources will be vital for ensuring Canada’s clean energy transition is reliable and affordable.
Lastly, as automotive systems become more interconnected, the need for cybersecurity is becoming increasingly important. Canadian cybersecurity startups and university labs are developing AI-based systems to detect and prevent cyber threats to vehicle networks. This includes intrusion detection systems, behavior monitoring tools, and real-time response strategies. As AI improves convenience and performance, it must also provide security—and Canada’s strong cybersecurity research community is ready to ensure that promise is fulfilled.
Canada’s automotive industry stands at a precipice, and artificial intelligence is not only a tool for efficiency but the linchpin to future competitiveness and relevance. From advanced manufacturing and predictive maintenance and autonomous mobility to dealership operations and customer experience, AI is transforming every stage in the value chain, reframing the way vehicles are conceived, produced, and enjoyed. At the retail level, dealerships such as Westowne Mazda show how AI is not so much a theoretical concept but a practical force shaping inventory management, customer interaction, and service work, illustrating how technology and human touch must work in concert. Yet the future of the business will be shaped as much by consumer confidence, infrastructure readiness, and trade policies as by technological innovation. Today’s pressures under CUSMA have underscored Canada’s deep reliance on cross-border integration, pushing firms to pursue diversification through deals such as CETA and the CPTPP, while managing new compliance complexities. All the while, the balance between automation and human touch remains essential; even as AI powers innovate,, Canadians continue to demand empathy, transparency, and human engagement in purchasing and servicing vehicles. Canada’s response to these opportunities has been threefold: public investment through programs like the Strategic Innovation Fund, world-class academic research, the establishment of responsible AI governance frameworks, and the launching of startups and projects like APMA’s Project Arrow. These efforts not only build technological momentum but also ensure that adoption aligns with national values of safety, accessibility, and sustainability. While global competitors rush toward autonomous driving and AI-powered energy systems, Canada’s distinctive combination of engineering expertise, flexible manufacturing, and ethical direction is poised to shape—not simply respond to—the terms of intelligent mobility. Tomorrow belongs to those who will be capable of pairing innovation with public trust, and Canada is strongly positioned to take the world in mapping a secure, sustainable, and human-centered path for automotive transformation.