White Paper

Viewing political trends in the US and Western Europe simply as rising nationalism is misleading. We must distinguish between civic and ethnic nationalism.

Depuis plusieurs années, Montréal se positionne à l’avant-plan dans les secteurs des nouvelles technologies, de la créativité et de l'innovation2. Plus récemment, c'est en intelligence artificielle (IA) que le positionnement international de Montréal se révèle3. Le secteur montréalais de l’IA bénéficie effectivement d’un écosystème propice à son développement accéléré. On retrouve en effet de la recherche universitaire de premier plan, des entreprises technologiques, petites et grandes, des structures d'incubation adaptées, du capital de croissance de même que d’importants investissements publics4. Cette combinaison de facteurs laisserait présager dans les années à venir une multiplication des succès du secteur montréalais de l’IA. L’intérêt grandissant porté, ici comme ailleurs, à l’IA se conjugue en effet à plusieurs autres développements technologiques pour ouvrir de nouvelles voies. Ainsi, l'émergence successive du Big Data, de l'analyse de données, de l’IA, puis de l’apprentissage profond, alimente de nouvelles formes de produits, services et de communications. Le secteur des services financiers ne peut rester insensible à ces développements d’application en IA. Les institutions bancaires et les compagnies d’assurances ont en effet toujours été de grands utilisateurs de modèles prédictifs. L'explosion des sources de données, combinée à l’infonuagique, pousse plus loin le secteur dans la généralisation des méthodes et des outils dans tous les départements des entreprises financières. L’industrie des services financiers a amorcé, il y a déjà plusieurs années, un grand virage afin d’exploiter dans plusieurs de ses opérations les bénéfices du Big Data. L’IA s’inscrit en quelque sorte comme étant la suite de ces avancées. Cette transformation soulève donc, à juste titre, plusieurs questions importantes pour le secteur des services financiers à Montréal. Par exemple, est-ce que le secteur financier montréalais peut capitaliser sur la force de recherche en IA? Quels seront les impacts sur l'emploi, sur les processus d’affaires, sur les produits offerts? Comment tirer profit des opportunités que ce domaine émergent génère? Y a-t-il des sous-secteurs qui sont plus à risque? C’est dans ce contexte que Finance Montréal et KPMG se penchent sur ces questions dans le cadre d’une étude de l’impact de l’intelligence artificielle sur le secteur des services financiers montréalais.

A significant proportion of Canada’s youth have poor literacy and numeracy skills. This is bad news for them, for employers and for our economy. These skills still matter. Level 3 literacy, the level at which readers begin to analyze, evaluate and apply what they have read in new and different situations and to easily problem-solve, is needed to perform well in every new job that is being created. What’s more, literacy and numeracy are the core “learning to learn” skills, and more than ever, our young people will need to keep learning to keep pace with the changing world of work. Building basic skills is the mandate of the K-12 system, but despite rising high school graduation rates, average literacy and numeracy scores of Canada’s high school aged youth are actually declining. The solution must begin here. More immediate results would be realized if the literacy and numeracy skills of the more than 80 per cent of youth who attend post-secondary education were assessed and, where necessary, boosted, upon entry to their post-secondary institutions. This would guarantee that graduates have these essential skills and would have the added benefit of ensuring students get more out of their expensive education. Finally, there is a need to embed these fundamental skills into any workplace training, including orientation training offered as new graduates begin their careers.

Canada’s poor productivity performance is holding back improvements in its standard of living, including wages. In particular, labour productivity has been virtually stagnant since 2000.¹ For the last few years, Canada’s Gross Domestic Product (GDP) per capita has hovered about $14,000 below that of the U.S.² In advanced services, manufacturing and energy industries, the workforce in the U.S. is twice as productive as Canada’s. The usual solutions to improved productivity include investing in more capital items such as machinery and information and communication technology or asking people to work harder. These solutions are not working. As more routine tasks are being assigned to machines, people are being asked to do more thinking, problem-solving and relational tasks. Rather than becoming less important, cognitive skills are becoming more important. It is clear that the Canadian economy needs to increase investment in another kind of capital: human capital. Working smarter, not harder can improve both productivity and economic growth. Working smarter requires the skills to learn new ways of doing things. Advanced literacy skills increase a person’s ability to learn easily and efficiently. New evidence shows that improvements in literacy can also increase productivity and GDP per capita more than ever before. Research also indicates that improving the skills of the people with the lowest levels of literacy provides an even greater boost. Furthermore, Canadian experience has shown that literacy skills can be increased through inexpensive and efficient workplace learning programs.

Workplaces are changing quickly. Machines or algorithms are replacing some tasks, and new and changing jobs require additional technical skills. To keep pace with these changes in current and future jobs, the ability to keep learning is the most important basic skill for any job. Because literacy is the most important “learning to learn skill,” Canada’s workforce requires high levels of literacy. However, many Canadian workers have poor literacy skills.

Ontario faces a dual challenge: automation technologies have the potential to improve productivity and competitiveness, and to generate more jobs and prosperity over the long term, yet many Ontario firms have hesitated to invest. At the same time, when firms adopt automation technologies, the disruption to jobs and tasks—and thus to workers’ income and well-being—can be significant. For Ontario firms and workers to thrive in the age of automation, we need to find ways to increase firms’ lagging adoption of automation technologies, while also equipping workers with skills and opportunities to adapt and thrive in a changing labour market. This report provides a grounded and detailed picture of the extent and nature of automation trends in Ontario and identifies strategies to help public, private and non-profit sector actors navigate this dual challenge. Rapid technological advances, particularly in artificial intelligence (AI), have heightened concerns about automation and the potential for job loss. These concerns have prompted a number of studies—each pointing to a large proportion of jobs or tasks that are susceptible to automation. While useful in highlighting an issue that deserves attention, the studies tend to overemphasize the risks of automation. First, most focus on whole economies, overlooking how impacts will vary by region, sector, firm and worker. Second, they tend to focus narrowly on jobs and tasks that could be automated by existing and emerging technologies in theory, and do not analyze the many factors that affect firms’ decisions to automate and thus the actual rate of automation in the economy. Finally, these approaches tend to focus more on the potential for automation to eliminate jobs or tasks, and less on the potential to augment or create jobs and enhance firm productivity and competitiveness. To fill these gaps in understanding, this report offers a more granular and nuanced understanding of automation in the Ontario context, and of the dual challenge it presents. It closely examines two sectors that are broadly representative of Ontario-wide trends—manufacturing, and finance and insurance—and explores the experiences and perceptions of Ontarians from different communities. The analysis draws on relevant data, existing literature, interviews with over 50 stakeholders from the two sectors, and engagement of over 300 Ontarians through interviews, public consultations and an online survey. This report is also informed by the guidance offered by an Expert Advisory Panel of 14 individuals with academic, technological, and industry expertise.

This report explores the risks and rewards automation poses for industries and workers in Ontario by examining trends in the economy as a whole, gathering local insights from across the province, and conducting an in-depth analysis of two key sectors in Ontario that are broadly representative of these trends — manufacturing and finance and insurance. This report outlines the dual challenge technology advances present to Ontario’s economy — to simultaneously improve lagging technological adoption, while mitigating its negative impacts for some workers — and proposes a bold strategy to meet this challenge head on.

Technological trends come with benefits and risks. On the one hand, they should be viewed as a major driver of economic growth and prosperity. On the other, technology poses potential risks – notably for workers responsible for job tasks that can now be automated. As a large, economically diverse country, Canada will experience an uneven distribution of the risks of technological trends. This data insights report begins to identify how susceptible Canada’s different regional economies to automation. It aims to inform the design of policies and programs that seek to mitigate the potential negative impacts associated with rapidly advancing technology. This report is part of a series focused on the tension between innovation driven growth and inclusive economic growth, with a focus on the future of work and skills.

Emerging technologies, such as artificial intelligence and advanced robotics, have the potential to fundamentally change our work and daily lives. In recent years, the understanding of how these technological trends will impact employment has been at the forefront of many recent public debates. Each week there seem to be more and more articles being released about how “robots are taking our jobs.” For the most part, this rich discussion has been driven by the work of many prominent academics and researchers. Unsurprisingly, there are many competing viewpoints. Some argue that disruptive technology will be the driving force behind massive unemployment. Others posit that any potential job loss will likely be o‑set by productivity increases and employment growth. Despite the extensive literature, this discussion is largely taking place without the use of Canadian data. Although, we know that Canadians are not immune from the effects of automation, and that technological trends will likely have enormous implications for many Canadian industries. But the gap in Canadian-specifi­c knowledge often means that we lack the tools to understand the impact of automation within our own borders. This limits our ability to begin to plan for potential disruption. We therefore felt that it would be useful to apply the ­findings from the existing literature to the Canadian workforce. To do so, we used methodologies both from both Oxford professors Carl Benedikt Frey and Michael A. Osborne and from management consulting ­rm McKinsey & Company, which have been employed in other jurisdictions, and applied them both to Canadian data for the fi­rst time. It is our goal to help Canadians better understand the effects that automation can have on our labour force. Overall, we found that nearly 42 percent of the Canadian labour force is at a high risk of being affected by automation in the next decade or two. Individuals in these occupations earn less and are less educated than the rest of the Canadian labour force. While the literature suggests that these occupations may not necessarily be lost, we also discovered that major job restructuring will likely occur as a result of new technology. Using a different methodology, we found that nearly 42 percent of the tasks that Canadians are currently paid to do can be automated using existing technology. But the data does not paint an entirely negative picture. Using the Canadian Occupation Projection System (COPS), we found that the occupations with the lowest risk of being affected by automation are projected to produce nearly 712,000 net new jobs between 2014 and 2024. As with any type of forecasting exercise, there are always going to be uncertainties associated with the predictions. However, we do hope that this study provides a tool to help guide future decision-making.