FUTURE OF AI
Chief Science Officer, RBC
Unlocking Data Transforms Insights Into Impact
Organizations are using generative AI to enhance client relationships, make smarter decisions, and lead with innovation. But the value is intrinsically tied to the depth and strength of the data used to train the model.
RBC knows that harnessing the power of AI depends on reliable access to its vast and unique data assets and secure platforms. To better understand clients, manage risk, and create insights, RBC relies on Lumina, its internal data and AI events engine. Lumina provides RBC with real-time data collection capabilities which helps keep staff and clients informed, triggers alerts and automated actions, and simplifies business processes. It also helps to achieve
platform standardization, adhere to the bank’s responsible AI principles, and enable safe GenAI access across the enterprise.
“Lumina enables us to bring all our data capabilities together in a way that we’ve never had before,” said Foteini Agrafioti, Chief Science Officer at RBC. “It’s the powerful foundation we’ve built around our data to empower business leaders to make better decisions and to deliver more effective and trusted AI models. As we look to a future where most client interactions will be informed by AI, Lumina is the foundation that enables us to build cutting-edge AI solutions in a safe and scalable way.”
For Canadian businesses, data is more than a resource, it’s a differentiator.
Canada’s Artificial Intelligence Revolution: Leading with Purpose
Minister François-Philippe Champagne highlights groundbreaking initiatives driving innovation and inclusivity in Canada's AI sector.
was recently in Silicon Valley, where I met with the CEO of one of the hottest AI chip technology companies. The first thing he did was to put up a slide with a picture of the chips his company uses to power their supercomputers.
You know what it said on that chip?
It said Canada! — In big red letters. That was further proof for me that when it comes to AI, Canada is a true leader. We’ve been at the forefront of the AI revolution. We have the world’s top AI researchers. We’ve got more than 140-thousand workers, our AI sector is a driver of job creation, economic growth, and innovation.
We were the first country in the world to launch a funded national AI strategy, turning heads and attracting global talent to our shores.
This wasn’t just a government initiative — it was a declaration that Canada would shape AI’s future.
I want to underscore that digital inclusion is at the heart of the government’s strategy. That’s why many of Canada’s initiatives specifically support Indigenous-owned businesses, rural enterprises, and businesses led by members of equity-deserving groups. This commitment ensures AI’s benefits extend to all corners of Canadian society and is in line with Canadian values.
This strategy is working; today, Canada is not just participating in the AI race — we’re leading it. Our researchers are publishing papers at a pace that far exceeds other G7 nations. And when it comes to cultivating talent in the field, especially among women, we’re setting the global pace.
Here’s the bottom line: while others talk about AI’s future, Canada is building it. We’re creating an AI ecosystem that’s not just powerful, but purposeful. Not just innovative, but inclusive. Not just Canadian, but global in impact.
The Honourable François-Philippe Champagne is Canada’s Minister of Innovation, Science and Industry
Foteini Agrafioti
A Robust AI Ecosystem is the Key to a Strong Canadian Economy
With Scale AI, Canada is going all in on artificial intelligence, so that it can fully benefit the Canadian economy.
Frank Campagna
Artificial intelligence is everywhere in the daily lives of Canadians, changing how we live, work, and interact. It may seem like the age of AI came out of nowhere, but the Canadian AI ecosystem has long been growing and innovating. For many Canadian businesses, the productivity and insight gains of AI initiatives have been a well-documented and steadily growing advantage for some time now.
Across a wide array of industries, from agriculture to air transport, food safety to supply chain management, AI has become an integral part of the way Canadian businesses do business. Most Canadian companies are now building robust AI roadmaps to ensure their continued growth. Canada's AI capabilities are advancing rapidly, with a huge concentration of world-leading researchers, innovators, and service providers collaborating on a dayto-day basis to build AI services and solutions that meet the needs and challenges of Canadian businesses.
“The Canadian AI ecosystem has reached an exciting stage of maturity,” says Julien Billot, CEO of Scale AI, Canada’s AI Global Innovation Cluster. “For years, we've been able to build on a robust research foundation, thanks to our national AI institutes and significant governmental investments in this field. Canadian companies need to seize this century's opportunity by adopting and integrating AI into their processes. The more we can increase the number of concrete applied AI use cases, the more our productivity will improve as a nation, and simultaneously, our local AI product and service providers will shine and grow.”
Leadership for a truly Canadian AI ecosystem
Scale AI was launched in 2018, the same year two Canadian researchers — Geoffrey Hinton and Yoshua Bengio — shared the Turing Award, computing’s highest honour, for their roles in birthing the modern field of machine learning and artificial intelligence. Canada is AI’s birthplace, and Scale AI was founded with the sole objective of developing productivity of Canadian companies and building a collaborative AI ecosystem. As a pillar of the Canadian AI industry, Scale AI has fueled this growth by providing Canadian businesses with strategic and financial support, enabling them to solidify their competitive edge while reinforcing Canada’s position as a global leader in AI.
In the short years since its inception, Scale AI has co-invested in over 120 Canadian AI projects across diverse industries for total investments representing $700 million. These investments played a role in helping Canadian companies grow their productivity by de-risking their adoption of AI but also contributed to
the growth of AI service providers from coast to coast and the commercialization of AI solutions like that of AlayaCare for the healthcare sector, that of Airudi for managing human resources, or previously unimaginable visualization tools like that of Mappedin.
Eyes on the horizon for Canada’s AI cluster
And all that is just the beginning. Canada has come out of the gates unbelievably strong in this ultra competitive sector, but it would be easy to squander our lead. “As a country, our success hinges on adopting AI, specifically Canadian AI built according to our own standards and best practices,” says Billot. “We must grow our internal demand for Canadian AI to support our incredible pool of local talent and emerging companies. Otherwise, we could find ourselves as a country that has produced two of the three founding fathers of AI, yet miss out on the opportunity to capitalize on these achievements. While foreign AI giants may capture our attention, we believe in supporting our homegrown talent to build a robust Canadian economy powered by AI.”
And it’s working. More than 4,000 participants from over 40 countries recently gathered in Montreal for the second edition of ALL IN, Canada’s largest AI event, to explore what our nation’s leading experts are doing in AI, from those who imagine and define it to those who build and adopt it.
While foreign AI giants may capture our attention, we believe in supporting our homegrown talent to build a robust Canadian economy powered by AI.
The momentum is there for Canadian AI. In recognition of Canada’s continued global leadership in AI innovation, we have been named Country of the Year at VivaTech 2025 in Paris. This is a big deal, considering that VivaTech is Europe’s largest technology event, with over 165,000 participants from all over the world. It is a unique opportunity to showcase the excellence of Canada’s AI on the international stage.
Artificial intelligence is a global phenomenon, and it is here to stay. Canadian AI innovators are especially well-positioned to meet the needs of our businesses and governments, ensuring they find local opportunities to remain competitive in an ever-evolving world. By ensuring that Canadian companies prosper in the emerging AI landscape, we can shape the future of our economy and influence AI worldwide. The future of the Canadian economy depends on AI and the coming year promises acceleration, growth, and international expansion for the builders of that future.
Julien Billot CEO, Scale AI
This article was sponsored by Scale AI
Panel discussion on the future of AI in Ottawa, June 2024, featuring Minister Champagne, Hongwei Liu from Mappedin, Isabelle Hudon from BDC, Pape Wade from Airudi, and Julien Billot from Scale AI.
How to turn GenAI Experimentation into Real Business Value
Artificial intelligence and machine learning are driving competition among Canadian businesses, but how businesses adopt emerging technology, like generative AI, is critical.
Ken Donohue
While uptake varies by industry, the motivation behind AI modernization comes from the need to be more efficient and produce results faster. In 2022, the world was introduced to ChatGPT and businesses quickly jumped into action, trying to leverage and adopt generative AI (GenAI). Today, business leaders and IT decision-makers face enormous pressure to harness the potential of GenAI to generate business value.
“This is 90 per cent of the conversations I’ve been having over the past year and a half,” says Marinela Profi, Global AI/GenAI Market Strategy Lead at SAS, a leader in helping its customers use data and AI effectively, with trust, and with confidence to grow their business. “We’ve already seen how rapid advances in large language models (LLMs) have accelerated AI into mainstream use, and it will only become faster.”
GenAI adoption — a closer look
GenAI (a subset of AI) can produce new content, including text, audio, video, and images, based on user input. Having natural language processing serve as the backbone of GenAI has also unlocked potential for non-technical people to harness automation and benefit from expert insights. While early implementations have had issues with accuracy, Profi is excited by the technology’s inherent capability to solve complex challenges and functions that could impact us in positive ways; for example by designing new drugs, developing products, redesigning processes, and creating efficiencies in supply chains.
But creating real business value out of GenAI is easier said than done. In a recent global study SAS commissioned with Coleman Parkes Research Ltd., 1,600 global decision-makers reported some obstacles in the implementation of GenAI, including insufficient internal expertise, challenges transitioning from the conceptual phase to practical use, and difficulty proving return on investment. The ROI challenge was cited by 45 per cent of Canadian respondents, compared to 36 per cent globally.
Transformative tech
Brian Jackson, Principal Research Director at Info-Tech Research Group, says AI was the most rapidly adopted emerging technology in 2023, and according to Info-Tech's Tech Trends 2025 report, AI received more net-new investment from organizations than any other technology heading into 2024. The expectation is that AI will break through the “emerging” threshold and become a transformative technology alongside cloud computing and cybersecurity in 2026. This will only intensify with the continued proliferation of GenAI use cases.
“GenAI’s broad applicability and promise to automate tasks that previously seemed to depend on humans hold powerful allure,” says Jackson.
According to Profi, some highly competitive sectors, such as banking and telecommunications, have seen positive results from their adoption of GenAI. But others, including energy and utilities, have been slower to adopt the technology, allocating a lot of the innovation to less consumer-facing use cases and operational sta-
bility. Banks and telecom companies are seeing more mature AI and GenAI use cases flourish in the form of enhanced complaints management systems and AI-powered customer support agents.
“Organizations that are succeeding with GenAI are the ones that recognize that LLMs alone won’t solve business problems,” says Profi. “When it comes to enterprise adoption of AI, you need a clear blueprint that involves people, process and technology. And in the GenAI driven innovation, people and process have never been more important.”
AI you can trust Globally there is a lot of experimentation with GenAI, but Canada lags some countries in the use of and full implementation of GenAI, including China, the UK, the U.S., and Australia. Dan Finerty, Senior Systems Engineer at SAS, says some of this can be attributed to Canada’s conservative approach to tech adoption.
“Canada is recognized as a global leader in data rights and privacy, which is good for Canadians,” he explains. “The emphasis on compliance is positive, but it contributes to a conservative approach to AI. Canada isn’t far behind the trailblazers, but there’s a focus on adopting AI responsibly, instead of rushing in and creating harm.”
However, many organizations still lack full oversight of the AI tools in their own environment and the majority are at risk of non-compliance when it comes to risk. SAS research shows that only 1 in 10 organizations in Canada have undergone the preparation needed to comply with GenAI regulations, only five per cent of Canadian businesses have a comprehensive governance framework for GenAI, and almost 80 per cent are concerned about data privacy and security.
Jackson says having a better understanding of which tasks need the help of AI and GenAI solutions will help overcome some of the challenges related to compliance and developing a framework.
“Not every task boils down to receiving exactly the right answer, and that's where these core foundation models can provide value with their incredible flexibility and broad knowledge base,” he says. “When we want more expert-oriented results in systems that require specific answers, then we should either use a rules-based deterministic system or more finely-tuned AI models that are purpose built.”
Artificial and human intelligence working together
For data-driven organizations, the productivity of their analytics teams is crucial to business success. Platforms such as SAS Viya can help empower users, regardless of their role, to manage their data and ensure decisions made on behalf of other people are explainable, transparent, and fair.
Despite trailing other sectors by 10% (44% vs. 54%) in the current use of generative
17%
into
Beyond that another 43% indicated that they’re experimenting with the technology at the enterprise level
6 in 10 respondents said they’ve deployed at least one GenAI use case to date — the
“Our team can answer, is this a scientific experiment or something that will support the business?” says Finerty. “This technology is so new that people need help understanding what it is, how it can help, and how to deploy it.”
Almost 8 out of 10 respondents are concerned about data privacy (78%) and data security (75%) when GenAI is used in their organization.
46%
Almost half of respondents foresee difficulty proving that GenAI offers a strong ROI, or have found this hard to prove.
4 in 10 respondents (38%) say they’ve found insufficient internal expertise to be an obstacle to implementing GenAI.
*Source: Generative AI Challenges and Potential Unveiled | Canada
INTELLIGENT BY DESIGN
How One Organization Is Accelerating AI Adoption
AI is transforming lives by boosting productivity, tackling climate change, and advancing healthcare, but scaling requires talent, funding, and connections.
Ken Donohue
Acting as a pivotal connector and leader in Canada’s AI ecosystem, Mitacs’s unique formula involves harnessing strategic connections, skilled talent, and financial support in order to scale faster and fully realize the benefits of AI. Over the past five years, Mitacs has supported more than 3,000 AI-related projects and 15,000 internships, while investing over $200 million in AI research and development.
“Canadian investment in AI innovation isn’t new, nor is our research and development ecosystem’s ability to leverage partnerships for outstanding results. But the true key to our success is our ability to collaborate — channelling government support and funding, connecting research talent with enterprise, and, critically, supporting the relationships between innovation organizations themselves,” says Dr. Stephen Lucas, CEO of Mitacs. “We couldn’t be successful today without strong connections to other organizations like the Canadian Institute for Advanced Research, for example. The innovation ecosystem in Canada is only as strong as its partnerships.”
Making AI adoption accessible
Mitacs has created targeted programs to address key barriers, including skills gaps, high costs, and ethical concerns.
“We thrive on partnerships and cross-sector collaboration,” says Shabnam Haghzare, AI Lead at Mitacs. “Businesses need knowledge-sharing initiatives to understand how AI can address specific challenges, a workforce equipped with the skills necessary for AI implementation, and tools and frameworks to adopt AI responsibly. Mitacs can assist with these needs.”
Innovation in AI and digital technology is vital for closing Canada’s productivity gap and securing its global competitiveness. Sectors like clean technology, healthcare, and advanced manufacturing are already seeing exponential growth in AI adoption, which directly contributes to job creation, economic resilience, and sustainable development.
By enhancing decision-making, automating routine tasks, and developing cutting-edge solutions, AI enables industries to operate more efficiently and effectively.
With its cross-sector reach, Mitacs ensures these benefits extend to all industries, including traditional ones, fostering equitable economic growth and national prosperity.
The best-kept secret
The multi-layered approach and ecosystem-centric model utilized by Mitacs is accelerating AI innovation while addressing adoption barriers. Mitacs collaborates with over 117 academic institutions and 1,500 enterprises, with its programs bridging research and industry needs.
The ecosystem it’s building connects innovators, talent, and resources while enabling small- and medium-sized businesses and multi-national enterprises to adopt cutting-edge AI. By engaging with international partners, Mitacs is also enhancing Canada’s AI leadership. And with a focus on small- and medium-sized businesses, Mitacs is democratizing access to innovation and talent. AltaML, an Edmonton-based applied AI company, is an example of the Mitacs approach in action. With 76 Mitacs-funded interns having developed business-ready skills at AltaML, the talent in the ecosystem is increasing. “The partnership with Mitacs has been incredibly important,” says Nicole Janssen, Co-Founder and Co-CEO
of AltaML. “Not only do our clients see value, it’s gratifying knowing we’re part of the talent development. The interns we’ve had are doing exceptional things.”
AltaML works with organizations to build custom solutions and has an in-house venture studio that brings together talent, AI and machine learning expertise, and capital to accelerate the growth of applied AI startups.
In addition, GovLab.ai, a collaboration between AltaML, the Government of Alberta, and Mitacs, was founded to accelerate digital transformation in the public sector.
Janssen adds that interns are often surprised at some of the exciting use cases for AI in the public sector, including wildfire prediction and reducing cancer treatment wait times. “Mitacs is the best-kept secret. They aren’t just looking to sell us on internships, but helping us succeed,” says Janssen. “I can't imagine anyone not wanting to partner with them.”
Mitacs: Your competitive advantage
Businesses need knowledge-sharing initiatives to understand how AI can address specific challenges, a workforce equipped with the skills necessary for AI implementation, and tools and frameworks to adopt AI responsibly. Mitacs can assist with these needs.
Organizations partnering with Mitacs report remarkable outcomes. According to Haghzare, small- and medium-sized businesses collaborating with the organization achieve an average 11 per cent improvement in labour productivity. Cutting-edge solutions, from AI-driven diagnostics in healthcare to resource optimization in construction, are being made possible. And traditional sectors, such as agriculture and manufacturing, are able to adopt AI technologies that were previously out of reach, enhancing their global competitiveness.
Another of those partnerships is with ServiceNow, which is helping organizations of every size, in every industry, to put AI to work by specializing in digital workflow automation to improve business operations. “We built a visiting researchers program to offer research internships in machine learning and AI to graduate students. The program welcomes over 30 candidates annually and most of them benefit from Mitacs funding,” says Valérie Bécaert, Senior Director of the AI Research Group at ServiceNow. “The impact Mitacs provides enables us to diversify our research portfolio by exploring more ambitious and forward-thinking projects, while also allowing us to delve deeper into broader, more comprehensive initiative.”
“For over 25 years, our partners have invested in and benefitted from Mitacs’s unique formula,” says Lucas. “By combining strategic connections, access to incredible talent, and much needed financial support, we’re creating the conditions to drive innovation — in the field of AI and beyond.”
Dr. Stephen Lucas CEO, Mitacs
Shabnam Haghzare AI Lead, Mitacs
Nicole Janssen Co-Founder & Co-CEO, AltaML
Valérie Bécaert Senior Director, AI Research Group, ServiceNow
Learn how Mitacs is making AI adoption accessible and impactful at mitacs.ca
This article was sponsored by Mitacs
How AI is Transforming Ocean Innovation
Artificial intelligence and machine learning are driving competition among Canadian businesses, but how businesses adopt emerging technology, like generative AI, is critical.
Katherine Cappellacci
AI has the potential to significantly impact Canada’s ocean industries. The ever-advancing technology could improve efficiency and enhance sustainable practices at all levels.
With coasts to the north, east, and west, the country’s already immense ocean economy continues to experience rapid growth. “Ocean-based businesses come in all shapes and sizes, encompassing everything from marine transportation to offshore renewable energy,” says Jennifer LaPlante, Chief Growth and Investment Officer at Canada’s Ocean Supercluster (OSC). “Being a hub for ocean and AI research alike gives Canada a competitive edge.”
Working with the ocean can be unpredictable – it’s difficult to anticipate weather and climate shifts, environmental hazards, and changes in animal patterns. Finite resources must be properly managed, and geopolitical shifts can suddenly impact work in unforeseen ways. AI could help ocean industry organizations deal with these unique challenges.
Enhancing sustainable efforts
A particularly pressing issue is climate change. “People in ocean and seafood indus-
tries see huge impacts of climate change in these ecosystems,” Eric Enno Tamm explains. “It’s causing widespread problems in fish patterns, lower productivity in certain seafoods, and die offs of food chains.”
Eric is the CEO and Co-Founder of ThisFish, a Vancouver-based tech company and member of the OSC. “AI’s ability to make predictions based on data could dramatically improve marine conservation, pollution detection, and climate change prediction.”
AI also has the ability to optimize all levels of ocean industry work by streamlining automation and productivity. It will boost ocean technology in areas including fleet navigation, supply chain optimization, resource monitoring, underwater exploration, marine safety, and ocean energy production. With this, it could also help companies develop more sustainable, ecofriendly practices.
Despite all the benefits, the ocean sector has been slow to adopt AI. As Eric muses, “The work is already unpredictable, so sometimes these industries are hesitant to take additional risks.”
The future is now That’s why the OSC is dedicated to helping
the ocean industry connect with and implement AI. As an industry-led national ocean cluster, the nonprofit works to drive ocean innovation and sustainable growth of the ocean economy.
After conducting research across the ocean sector to better understand the barriers to adopting AI, the OSC launched an insights report today in advance of its release of “The Future of Ocean AI: A Strategic Approach for Canada.” With input from industry, academia, and government, the approach provides recommendations to overcome identified barriers, including addressing knowledge and skills gaps, and increasing private and public funding.
The approach supports Ambition 2035 –the collective vision of the country’s ocean network to grow the ocean economy to $220 billion by 2035. “These initiatives help to establish Canada as a global leader in ocean AI,” Jennifer adds. “We aim to empower ocean businesses at every stage to understand and leverage AI to their advantage.”
How to Unlock the Potential of AI to Benefit Canadian Citizens
Governments are in the midst of a fundamental transformation in the way the public sector operates in today’s digital world. Leveraging advanced technologies, such as rapidly evolving artificial intelligence (AI) capabilities, have the potential to improve the speed and effectiveness of the delivery of public services to Canadians. But if we are to capitalize on this potential, we need to move from talking about it to developing tangible and high value use cases and accelerating responsible adoption.
Ken Donohue
Canadian-based CGI, one of the largest independent IT and business consulting services firms in the world, is helping government agencies streamline operations and improve public services by identifying suitable processes for automation and AI, while addressing concerns around security, compliance, and budget constraints. Early applications in government operations are already enhancing efficiency and accessibility, showing how responsible AI solutions can address pressing needs within public services.
Changing the conversation
“We’re hearing a lot of excitement from our clients, and the conversation is shifting from what are we able to do with this technology to how can we make it useful,” says Dr. Diane Gutiw, Vice-President and AI Research Centre Lead, CGI. “There’s a lot of hands-on experimentation currently underway with AI in the public sector; however, there's still a gap in moving that into production. But I believe we’re going to see a rapid move in the coming year to more implementation as the public sector finalizes its AI policies, AI governance models and terms of use.”
Dr. Gutiw adds that rather than throwing generative AI or even traditional AI at everything, we need to identify the problem we are trying to solve and then determine the best technology to address that problem or ques-
tion. “This is what will make the biggest difference, and it’s very much a custom fit”, she says.
Harnessing the responsible use of AI
As with any technology, responsible use is imperative. When it comes to AI, this is a concern that comes to the forefront. CGI is deeply committed to upholding the highest standards in AI development and deployment. It has signed the Canadian Voluntary Code of Conduct on the Responsible Development and Management of Advanced Generative AI Systems, and its framework for responsible use of AI ensures that risk analysis and mitigation are part of every step in AI design and implementation. Public trust happens by embedding ethical considerations into AI strategies. With a strategy and safeguards in place, public sector agencies can start small to move forward and learn as they go. By doing this, they can prove what it can do in the realm of possibility and build on the knowledge gained.
We’re hearing a lot of excitement from our clients, and the conversation is shifting from what are we able to do with this technology to how can we make it useful.
responsible AI adoption. As a trusted partner that provides tailored solutions, deep industry experience and a commitment to responsible technology use, CGI solves problems and accelerates outcomes with AI.
It’s through strong public-private partnerships that governments can accelerate
CGI reinforces its ethical AI leadership globally as well, by signing the EU AI Act Pact, emphasizing Responsible AI through risk management, AI literacy, and governance, while contributing to the development of the Code of Conduct for General Purpose AI. Workshops and consultations from November 2024 to April 2025 aim to shape the future of ethical AI practices.
New Report Shows AI Adoption Strategy for Canadian Business is Essential
Canada excels in AI research but trails in adoption. Learn how new strategies and a competency framework can drive AI adoption and innovation.
Wendy Cukier
Canada has a reputation as a global leader in artificial intelligence (AI) research and development. Look no further than the recent Nobel Prize awarded to the University of Toronto’s Geoffrey Hinton. Yet, Canada lags in the adoption of AI technologies in the workplace — with research indicating only 35 per cent of Canadian businesses use AI, compared to 72 per cent in the U.S. Canada’s small- and medium-sized businesses (SMEs), which account for the majority of private sector jobs, are falling far behind with just eight per cent of medium businesses and six per cent of small businesses using AI. Creating disruptive technologies does not produce innovation. Using them does.
New data from our latest report Artificial Intelligence at Work, with the Environics Institute, supported by the Future Skills Centre, surveyed over 5000 Canadians and shows that nearly 3 in 10 employees report using AI tools at work, yet 44 per cent of these users have not received any formal training. This suggests that their employers may not have policies or processes or even know how their employees are using AI, creating massive risks of intellectual property, privacy and cybersecurity. Findings also showed that, of those using AI, more than two thirds (68 per cent) are learning independently, either through self-guided training (24 per cent) or without any structured guidance (44 per cent).
The data also highlights the potential for AI to bridge the digital divide. The gender gap for AI use in the workplace is much smaller than with other advanced technologies.
The “English Major’s Revenge”:
An opportunity to bridge the digital divide
The data also highlights the potential for AI to bridge the digital divide. The gender gap for AI use in the workplace is much smaller than with other advanced technologies. Among workplace AI users, 52 per cent are men and 47 per cent are women. Younger workers, Indigenous people, racialized individuals, and immigrants are more likely to report familiarity with AI and access to workplace training. Access to networks, tools, and skills can be barriers but in some respects the power of AI-enabled “low code, no code” applications open up opportunities for diverse groups which are often under-represented in science, technology, engineering, and math (STEM) fields.
The emergence of generative AI — “the English major’s revenge” — further democratizes AI skills which require excellent language and reasoning skills, broadening pathways to good jobs. Using diverse teams in developing AI has proven effective given its potential for embedding bias when it reifies historical data and decisions. Another recent Diversity Institute report co-authored with the Ontario Society of Professional Engineers — More than Just Numbers Revisited — underscores the importance to increase the participation of women and other equity deserving groups in STEM to advance inclusive design. At the same time, shifting our focus from developing tools to ensuring responsible and ethical adoption of AI highlights the need for a wider range of skills and disciplines — policy, law, organizational change and strategy, consumer behaviour, and more.
As part of its work with the Future Skills Centre, the
Diversity Institute has developed a competency framework for AI. At the apex are the deep AI skills including machine learning, and data analytics required to develop the technology. In the middle are AI innovation skills which are essential to help organizations in different sectors match technology to their needs and drive adoption. But the foundation is AI literacy which all Canadians regardless of their professional sector need.
Barriers for SMEs and Canada’s AI paradox SMEs, which account for about 90 per cent of private-sector jobs in Canada, face significant challenges in adopting AI. Unlike large corporations who tend to dominate the discussion and shape our strategies, SMEs often lack the resources and expertise to implement AI solutions responsibly. Many lack the investments needed but even more simply do not know where to begin or have the talent needed to move forward. Given the structure of our economy, any solution needs to address this challenge for SMEs.
A Future Skills Centre-supported initiative, the Skills Bridge program, developed by the Ontario Chamber of Commerce and Magnet with the Diversity Institute, is attempting to address these issues with a shared platform to support SMEs and their staff in navigating digitization and other transformations. By developing and curating training, use cases and other tools, Skills Bridge helps SMEs who lack the resources and expertise individually to create a critical mass for change. Coupled with student work integrated learning programs, there is an opportunity to both support SMEs in implementing AI solutions while creating pathways to employment. To date, more than 500 companies have participated, but the program continues to attract more organizations. There are also opportunities for nonprofit organizations and government sectors which have many barriers to adoption.
The way forward
Our report findings underscore the need for a comprehensive AI adoption strategy that addresses skills development, particularly for SMEs and equity-deserving groups. Canada’s paradox — leading in AI research but lagging in its use — requires urgent action if we are to achieve the promise of AI while managing its risks.
The new Canadian Artificial Intelligence Safety Institute is a welcome initiative to ensure we have the ethical frameworks to manage the risks. The planned $2 billion commitment to AI compute infrastructure is a game changer, particularly for researchers and large corporations. But we cannot assume that “if we build it, they will come.” We also need a targeted strategy to address barriers to the adoption of AI, particularly in SMEs, if we want to harness the potential of AI and manage the risks. Working together, policymakers, employers, industry associations, and educational partners must act swiftly to equip workers with the skills needed for the AI-driven future.
