Canada’s Economy, Explained
Episode 9
SUMMARY KEYWORDS
G7, B7, AI adoption, digital transformation, sustainable growth, generative AI, investment hesitancy, skills shortages, environmental impact, supply chain resilience, government role, renewable energy, digital infrastructure, workforce re-skilling, green economy.
SPEAKERS
Franco Amalfi, Tom Mosseau, Marwa Abdou
Marwa Abdou 00:02
Welcome to today's episode of the Business Data lab Podcast. Canada's Economy, Explained. I'm Marwa Abdou. Lately there's been a lot of buzz around the Group of Seven. No, not of painters Emily Carr and Lauren Harris fame, but the g7 Canada, France, Germany, Italy, Japan, the UK and the US, seven of the world's most advanced economies. These nations meet regularly to tackle global challenges like economic growth, climate change, international security and global health. Their decisions ripple across borders, directly shaping Canada's economic landscape and signaling how world powers are thinking about shared strategic risks and opportunities. Now, while the g7 focuses on political leadership, the b7 brings together business leaders, major industry players to align with and contribute to the g7 goals as of January 2025
Marwa Abdou 00:59
Canada doesn't just have a seat at the table. It's at the helm of it as the president of both g7 and b7 now, to mark this occasion, next week, Canada will be hosting the 51st g7 leaders summit in Alberta. This is the sixth time that Canada hosts, and it's an ever timely opportunity for it to lead with the hard work. It'll be a high profile event, not only because of the timing and global participation, but also because of what's at the top of the agenda. Want a preview? Well, look no further than the 2025 b7 communique released after last month's b7 summit in Ottawa, which was hosted by the Canadian Chamber of Commerce. One of the communiques biggest recommendations is accelerating the strategic and sustainable adoption of artificial intelligence. It's a key pillar Prime Minister Carney's platform, and it's been made official with the recent appointment of Canada's first ever Minister of artificial intelligence and digital innovation. But here's the issue, despite our potential, Canada still lags its g7 peers in AI adoption in many respects, this isn't just a tech problem, it's a broader challenge, spanning investment, skills, commercialization, infrastructure and smart regulation. So to unpack what all this means, I've invited two experts from Capgemini, Canada, a global leader in helping businesses harness tech for inclusive and sustainable growth. Joining me today are Tom Mosseau, President and Managing Director of Capgemini Canada, and Franco Almalfi, Director of Sustainability,Sstrategic Partnerships and Initiatives. Franco and Tom, welcome to the show.
Marwa Abdou 02:38
Tom, I wanted to dive right in and ask you, from your experience you have now over 20 years of experience working with Canadian companies, what are the top of mind challenges that you think face most Canadian companies when it comes to adoption and digitalization. How does this compare across business sizes, geographies, industries? Can you give us a lay of the land? I think legacy infrastructure is one of the biggest factors in slowing down modernization, and some of those key sectors that are hardest hit for for this are finance and manufacturing, given the age of these industries in Canada, the other big one is skills shortages, the key skills required AI cloud and cybersecurity, and those are in limited supply, and they're certainly going To limit execution and innovation across across the industries. Investment hesitancy due to the unclear return on investment, the cost, which is high cost to implement these complex system integrations, really drives a lot of hesitancy in business decision, in moving forward and in investment communities and investing in those transformations.
Tom Mosseau 04:03
Small and medium sized businesses have their own different set of hurdles, considering limited funding, available data, quality issues that they've not been able to correct over the years. You know, resource constraints, we talked about, the skill shortages. There's a real resource battle there, and these small and medium sized businesses find it hard to compete with the large enterprises out there that are a little bit more advanced in the adoption in general.
Tom Mosseau 04:32
You know, all of these barriers put together make it difficult to fully leverage AI to drive efficiency and innovation. And the problem is is, if you don't scale, you're going to fall further and further behind, and that gap between small and medium sized businesses is going to increase and have them not be as competitive against their larger, larger enterprises when they're competing for for skills, investment dollars and. And the barriers just compound on each other. You know, at CAP, our job is to help clients cut through that buzz, leverage and identify the most relevant use cases that can drive the biggest impact for them. We focus on helping our clients first define what is their generative AI strategy. You know, what are those priority use cases? And then develop and deploy a tailored solution at scale in a responsible and trusted manner. And I mean, that's an important word that I just raised there, trusted. What does it really mean? And for us, what that means is, it's reliable, it's safe, it's secured, it's controlled, and I think most important, it's ethical. So I know you touched on a number of different things and shed a little bit of light in terms of what Capgemini does when it partners and works with businesses. I wanted to ask from your experience, how does Canada compare to other countries in terms of its pace and the advancement of technological adoption and innovation. We know that the new prime minister is quite focused on that aspect, in terms of pursuing more sustainable tech adoption and looking into leveraging AI and making Canada an epicenter for that. So can you talk me through where we are right now?
Tom Mosseau 06:27
Yeah, compared to global leaders, US, China, UK, our Canadian AI investment, both public and private, is relatively low, yet at Capgemini, we do see a strong acceleration of client appetite for generative AI, we've delivered over 300 projects in this space, very large pipeline, about 800 client opportunities sitting out there across the different industries. And we're really seeing a represent a shift from a proof of concept. So consider that an early stage use case, compared to a scaling phase, which, when you think of scale, think about in production, ready for client consumption. I'm convinced that this new technology wave will accelerate the transition to new digital and sustainable economy, and we're really excited about the possibilities that the technological advancements open up for our clients. You know, just to put some stats behind that, 61% of Canadian businesses agree that generative AI has the potential to fundamentally shift their business strategy. 28% of Canadian organizations are now integrating generative AI into their locations, into their daily functions, which is up 4% since 2023 so we are seeing that positive movement when we pulled the Canadian organizations. 48% are allowing employees to leverage generative AI in their in their daily use.
Tom Mosseau 08:01
Yet 45% are only are developing guidelines for responsible use of generative AI. So artificial intelligence is expected to have an even more profound impact globally than the introduction of the internet. We know that in 2017 Canada was the first country in the world to launch a national AI strategy, establishing itself as a home for trailblazing academic researchers, but we know that that has since stalled. Canada has the talent, it has the algorithms to play a leading role in this area, but its progress has stalled, like I mentioned, compared to the US to China, to Germany. Why has Canada fallen behind in this global AI race? Let's look at some of the key drivers here. One, there's no unified national strategy. Canada lacks a clear long term AI vision to guide investment. Education, we talked earlier about the skills gap and just general innovation across across the sectors, and still a policy gap remains. I mean, while the federal government introduced a voluntary AI code of conduct, the lack of binding regulation has led to inconsistent adoption across businesses. We talked about the the investment hesitancy as an example a little earlier in our discussion, that's driving the insufficient investment compared to the big leaders like us, China and UK that we spoke about. And that's not just in the private that is both public and private sectors. We're seeing that investment below and I think it's a missed opportunity to scale small and medium sized businesses while they're eager to adopt again, that limit of funding, of investment, that limit of capability with resources the education is really driving a barrier to to further advance the.
Franco Amalfi 10:00
The adoption and just general risk aversion without strong policy guidance, risk management frameworks businesses are hesitant to adopt Ai at pace, and the pace is required to truly accelerate to where Canada needs to be to match that of of the big countries like us, China, UK, as examples.
Marwa Abdou 10:23
So one statistic that stands out from our prompting productivity report is that in Canada, early adopters of generative AI, the kind that create new content, like text, images or video, tend to actually be larger companies, exporters or firms with highly educated workforces, and when we talk about Gen AI, we're really talking about tools like chatgpt, meta AI that are powered by large language models. Those are evolving incredibly fast. Canada is investing heavily in AI infrastructure, but there's been far less focus on the environmental footprint of scaling up these systems. Now. Capgemini, new report developing sustainable Gen AI really digs into this issue. So my question to you, Franco, given your experience, what are the key environmental risks of Gen AI adoption, and what would a more sustainable path forward look like for Canada and for business?
Franco Almalfi 11;23
Absolutely, Marwa, that is a great question. We are really at a crossroad of Gen AI from a sustainability point of view. We either view it as a hero or a threat. We believe we can have both. I mean, we have to make sure that we actually use Gen AI for the purposes that Tom talked about, all the advances that it brings us, but we do it responsibly. There's no negating that the environmental footprint of Gen AI is substantial with high energy consumption, increased e waste and significant water usage, both from model training and inferences. There's a resource intensive nature of Gen AI that pose challenges in managing carbon emissions and ensuring sustainable practices across the AI lifecycle. So we believe we need to balance these with these impacts, so we can require using a responsible approach to design, monitoring and optimization, so we can mitigate its consequences while leveraging its potential sustainable growth. We have such an incredible opportunity in front of us by using these technologies to really enhance sustainability initiatives, we are always looking for new ways to working with our customers to help them through their journeys on sustainability. Some of the areas that we are seeing, especially around supply chain. How do we enhance efficiency and reduce waste and supply chain operations, be it through logistics, be it through the way goods are produced, the way they're transported and so on. Using these technologies gives us a vast amount of information and insights to better manage these processes. One other area that we're seeing a lot of excitement about using these technologies is around sustainable products and services. We have now the capability by of using these technologies to be able to iterate and develop new materials that are much more eco friendly, that will use much more recycled material as part of it, be it in the product itself, or even in the package or in the services. If we're in the service industry. The other area is around operations and manufacturing optimization. We work with a lot of customers that are that I do this for, for their companies, is, how do we actually improve operational processes? How we reduce the amount of
quantity of items that are needed that to match your manufacture product, or auto optimize the way the the actual manufacturing process itself is done and minimum with a view always to minimize the environmental impact. And last but not least, it's logistics and transportation. How do we optimize logistics to reduce carbon footprint? How do we reduce the amount of transfer the trends that needs to take place? How do we optimize those routes? How do we get things to people as quickly as possible, while always being conscious of the impact from from an environment perspective. And maybe Tommy can talk about some of the statistics we're seeing from an executive perspective.
Tom Mosseau 14:10
Yeah, please, yeah. Look. I mean, does generative AI provide great business value, whether it be through enhanced customer experience, streamlined operations, accelerated innovation? I think that answers very clearly. Yes, we're seeing it across all industries, across Canada, but at what environmental cost? I mean, if you think about the power consumption, the water required to cool the systems in the process of the large volumes of data that allow us to come out with these insights. Franco to your point, what are the executives thinking about this? How are they responding to this? And
Tom Mosseau 14:46
I'll reply, maybe with some stats, and then throw it back to you to go into a little bit more detail on how Capgemini proposes that we should be thinking about the environmental impact of generative AI. But just the stats. 48% of executives believe AI increases emissions, yet only 12% are measuring the impact. Only 31% incorporate sustainability into their AI life cycle. I mean, highlighting there's a significant opportunity here to improve as these models become even more complex. So maybe Frank, go back to you a little bit to talk about what has kept Gemini thought leadership around how should executives handle this? What is a framework that they can turn to here?
Franco Almalfi 15:33
Absolutely Tom, and this is a I mean, at the end of the day, like we are seeing the explosion of a technology that has tremendous potential, and our customers have made commitments to be net zero by 2030, 2040, and so on and so forth. So they're very, very concerned with adopting this at an enterprise level to ensure that it does not impact negatively their commitments. So what we've done, working with through our research institute, working with many, many customers, we've actually developed responsible practices in the use of Gen AI for sustainability. We developed a comprehensive approach, which we call responsible by design, which includes key initiatives. The first one is we need to assess, monitor and mitigate LLM consumption. We need to emphasize the importance of continuously assessing and optimizing the energy consumption of the AI models to reduce our environmental impacts. More and more new techniques are coming into more into play that allow us to reduce the amount of water and energy we use for these models could be small language model, not everything is to be a large language model. It could also be trained on a smaller data set, so on and so forth. So the number of techniques that we apply here as well optimizing energy consumption, we focus on improving the efficiency of AI operations to minimize energy usage and associated carbon emissions. We're looking at, can we actually train this model using renewable energy and so on and so forth? So there's different techniques that we can apply to ensure that that happens, also governance and transparency. At the end of the day, we need to actually have clear governance structure and transparency to ensure ethical and sustainable practices. This has to be part of the design. When the organization is adopting this, we need to be thinking this from the beginning, not an afterthought. And if we think about it from the beginning, and we design what we're going to use it for, that's when we start seeing things done correctly and done the right way. And this sort of after the fact, and you have to go and correct it. We want to avoid that at all costs. We've built this concept of sustainable AI factories, where it's the sustainable by design the it aims to integrate sustainability into all aspects of the AI development and deployment, be it from the DevOps, be it from the training and ensuring that all the technologies that we use as part of the AI factory contribute positively to the environmental goals. Also, we work very closely with our clients. We partner with them to ensure that they minimize their environmental impacts and leverage sustainability challenges, opportunities for innovation and value creation. We work with a lot of customers to define their strategy for net zero. We actually help them define what initiatives should put in place. So this is part of that work. We continue that work. Would now invent Gen AI as part of that collaboration, and it's really part of a broader commitment to achieve net zero carbon emissions and addressing water sustainability challenge like including water consumption, waste management, biodiversity conservation, which is really critical the way ourselves conduct ourselves and the way we're looking at helping our customers
Marwa Abdou 18:37
Now to bring things full circle the Current Canada-US trade tensions and the sweeping tariffs are a real concern. They disrupt global supply chains. They make clean technology adoption harder, they set back international cooperation on climate goals. But this isn't entirely new. We've seen major supply chain rethinks before, during the COVID 19 pandemic, and even earlier, as companies adapted to faster delivery demands and rising customer expectations all throughout the 2000s
Marwa Abdou 19:09
What lessons can we take from these past disruptions, including today's trade tensions, about how businesses can build smarter, more resilient and more sustainable supply chains. Tom?
Tom Mosseau 19:23
Yeah, thanks. I'll just hit one quick point here, and then I'll turn it over to Franco, as this is a specialized area for him, but if you think back to COVID 19 pandemic, it revealed that sustainable supply chain practices created resilience. However, supply chains contribute up to 80% of greenhouse gas emissions. So companies are going to have to transform their transform their operations, using digital technologies to withstand future disruptions, yet they need to maintain the customer demands. And how do they balance all that while thinking about sustainability, Franco, do you want to just take us through a little bit of your thoughts on that?
Franco Amalfi 20:00
Yeah, absolutely. Thomas. I mean, this is at the end of the day. I mean, COVID 19 really uncovered a lot of the issues and the opportunities that we have today. So we really understood the need of having resilient supply chain over lean ones. I mean, obviously we drove as much efficiency as we could through the supply chain. However, there's been a lot of disruptions. We need to be able to have the flexibility to handle them. Companies are now prioritizing visibility and transparency to manage risk effectively. So they want to ensure that they know their suppliers and the origins of their products. That's very critical to organizations. They also need agility and flexibility. These have become crucial. They need to respond swiftly to changing conditions, whether to geopolitical conflicts, you brought the changes in tariffs and so on and so forth, natural disasters, as well as shifts in consumer demand, you may have a situation where people, all of a sudden are buying more products in a different part of the world, so on and so forth. So we need to be able to adapt to all these different dimensions. Digital transformations play a key role in enhancing supply chain operations. They enable us to have better decision making and operational efficiency. Having access to data and having access to Insights is really critical to be able to adapt quickly. That's what we need to focus on. We also need to focus on sustainability. This has grown dramatically. Consumers are demanding environmentally friendly products. I mean, despite some of the changes in public opinion and what politicians may tell us, consumers want environmentally friendly products, they promptly companies to integrate sustainability into their strategies. You can see this, Amazon sustainable products, they've grown enormously but the amount of data that they actually the products that they saw. I mean, it's a question of if you're going to sell more products if you're sustainable versus if you're not. We also need to adapt it to climate risk. I mean, we have, we've more and more extreme weather events globally, and these climate related disruptions can significantly impact supply chain. If companies don't have that make consumer goods, don't have access to palm oil. They can no longer make products. So that becomes they become vulnerable, and they need to develop strategies to mitigate these risks. They get a better they better understand where else can they actually source those raw materials? And finally, from a customer centric approach, it's essential that it's meeting the demand for faster deliveries and product availability requires balancing efficiency resilience. We need to make sure that we do this in a way that we can deliver the products. We can deliver them where people want them, and deliver the products of the type of products that people want so they could buy them from us.
Marwa Abdou 22:37
Capgemini has such a breadth of coverage in terms of the kinds of institutions it works with, we know that the stakeholders who influence a country's technology transformation and shape its ecosystem are diverse and interconnected. We talk a lot about that here on the podcast. Key groups include the government, the private sector and civil society. The government plays a crucial role in technology transformation by providing leadership resources and a supportive environment for innovation.
Tom from your experience here in Canada, can you tell me a little bit more about why you think it's important for government to play a role in closing some of these gaps that Canada has in this eco digital space?
Tom Mosseau 23:17
I think it's key that we have a coordinated national approach to strengthen Canada's digital competitiveness, and that includes having a collaborative ecosystem between government and industry. Capgemini government technology work has shown that government partnerships do create enormous public value. Our research identified 9.8 trillion global opportunity in Canada government collaboration is vital for nationwide demand response programs that, frankly, I don't believe private organizations can achieve alone. Back to stats, and back to one of our earlier points, with only 12% of organization organizations measuring AI's environmental impact, governments have to establish a regulatory framework encouraging sustainable practices and lead technology deployment to meet Canada's sustainability targets.
Marwa Abdou 24:13
Now, Tom, you touched on this the chambers b7 communique points out that accelerating AI adoption could boost global GDP by up to 7 trillion by 2030, now it seems that you have higher estimates, but in that regard to realize that potential, it emphasizes the need to develop a more AI and digitally skilled workforce. We need to invest in enabling infrastructure, and we need to promote regulatory clarity, transparency and interoperability, given that the new prime minister has made this essential pillar of Canada's economic strategy, what do you see the greatest Where do you see the greatest opportunities are for government to make real progress. That's one. And what are the areas that remain untapped and underdeveloped?
Marwa Abdou 24:59
And looking internationally, what can Canada learn from countries that are already making strides? You have France's 200 billion euro invest AI initiative, Germany's standardization roadmap for artificial intelligence. All of them are including and balancing this idea of innovation with ethical standards.
Tom Mosseau 25:20
Yeah. I mean, we have sectors where Canada already has a competitive advantage, sustainable forestry, renewable energy, Smart Agriculture, so the government should prioritize strategic investments in AI applications across these areas to gain an economic boost, we need to bridge Canada's Digital Divide for equitable economic growth across all regions and demographics. This is going to provide digital access across rural communities. You know, here in Ontario, there's a broadband for All Initiative as an example, we talked about the pandemic a little early on. This is a response to rural communities not having access to the internet, not having access to digital advancements. The government can unlock productivity and innovation through some of these means, and the government has to invest for digital infrastructure and workforce re skilling. We talked earlier on in our discussion that that the capabilities, the qualifications in this space are essential, and we're just going to have to reskill our workforces. And I do believe Canada can lock growth and prepare for the AI driven economy.
Amazing. Franco…?
Franco Amalfi 26:36
Yeah, in addition to what Tom just talked about, I believe that Canada, we have the opportunity to further strengthen our position as a global leader in green economy, as a country when many others are retreating and pulling back, I think we need to continue and really focus on a holistic approach, which reinforces a reputation as a steward of natural resources. We have set ambitious targets, let's continue reducing greenhouse gas emissions by 40 to 45% below 2000 2005, by 2030 let's continue on that journey. Let's make sure we do that. Let's invest in renewable energies. We have heavy investments in wind and solar power in all kinds of parts of Canada. Let's continue doing that. I mean, really, we have the opportunity to use those investments to drive a lot of economic value. Zero emission vehicles, we know we have seen tremendous adoption in Quebec, Ontario, BC, and many other provinces and in government itself. Let's continue those programs. Let's ensure that people drive electric vehicles, phasing out coal, eliminate coal fire power plants as much as we can through our country, we have that opportunity a green infrastructure. Investment in green infrastructure, let's make sure that we continuously invest in newer technologies, be it director capture or others, so we can actually set ourselves for being the leaders in the world, economic, strategic and integration. Let's align the financial markets with climate goals to drive economic growth and job creation. I mean climate change and green. Being green as a country, a green economy will give us economic opportunities that I think will drive growth and job creation and will actually help Canada be the leader in the world. I'm strong believer in it. I'm a proud Canadian, and I think and I love sustainability, I think we really can do something special here in Canada.
Outro 28:29
Thanks for listening to Canada's Economy, Explained. Follow us for updates and visit businessdatalab.ca for free tools and insights, and be sure to join us next time.