April 15, 2025
The Empire Club of Canada Presents
The AI Revolution: What’s Next for Law, Finance, and Accounting?
Chairperson: Jenna Donelson, President, Board of Directors, Empire Club of Canada
Moderator
Cameron Schuler, Chief Commercialization Officer & Vice President of Industry Innovation, the Vector Institute
Panellists
Dr. Foteini Agrafioti, Chief Science Officer, RBC; SVP, RBC Borealis
Colin Lachance, Innovator-in-Residence, Ontario Bar Association
Iliana Oris Valiente, CPA, CA, Managing Director & NA Innovation Hubs Lead, Accenture
Head Table Guests
Farah Qasemi, Global Client Services Partner, Ernst & Young
Welcome Address by Jenna Donelson, President, Board of Directors, Empire Club of Canada
Good afternoon, everyone. I hope you all enjoyed your lunch. Nice to see you all again. I’m Jenna Donelson, Chair of the Board of Directors of the Empire Club, and your host for today’s events.
To formally begin, I want to acknowledge that we are gathering on the Traditional and Treaty Lands of the Mississaugas of the Credit, and the homelands of the Anishinaabe, the Haudenosaunee, and the Wendat Peoples. I encourage you all to learn more about the Traditional Territory on which you work and live.
Today’s event would not be possible without the generous support of our sponsors. The Empire Club is a non-profit organization. Our sponsors support the club, they make events like this possible, and they make viewing complimentary, for those of you that are online. So, please join me, in thanking our Lead Sponsor, Ernst & Young. Thank you. And thank you, as well, to our VIP Reception Sponsors, CPA Ontario, and Dentons Canada. We appreciate you. We also couldn’t do these events without the ongoing support of our Lead Season Sponsors, Bruce Power, and Hydro One, and our VIP Reception Season Sponsors, Waste Connections of Canada, and Ellis Don. Thank you, for your support. And finally, thank you to our Media Partner, The Toronto Star, and our AV Partner, Bespoke Audio Visual. Couldn’t do it without you. Thank you.
I know we are going to have a very interesting discussion today, so if you have a question for our speakers, please scan the QR code that is found on your program. If you’re online, use the Q&A function. And for those of you online, if you require technical assistance, use the chat feature, and our staff will be there to help you.
I am so delighted that you are all here for today’s important conversation, “The AI Revolution: What’s Next for Law, Finance, and Accounting?” For more than 120 years, the Empire Club has been the place where important conversations happen. And it’s even been the place where important predictions are made. In 1996, Bill Gates was at this very podium, making some very interesting predictions about the future. Here’s a bit of what he said. He said, “You’ll have a computer in your car, and you’ll have something that you carry around in your pocket, that hooks up to the wireless network. It will always show you a map of where you are, give you your schedule, and your latest messages; it will even have digital cash, or digital tickets. We think of it as the wallet PC, because it’s a replacement for everything that you carry around today. You can even have hundreds of thousands of pictures of your kids, to show other people.” Wow, I think we can all agree that that was a pretty accurate prediction about smartphones that came from the Empire Club stage—especially, the one about the pictures of your kids. And I have every confidence that we will look back on today’s discussion about AI, in a few years, with the same appreciation, because today’s discussion is about where we are, and where we’re headed with AI.
We all know that artificial intelligence is reshaping how we work, how we serve clients, and how we define value in professional services. But for fields like law, finance, and accounting, sectors that are built on trust, ethics, and precision, getting this right could not be more important. In a short span, AI has moved from being a novelty to becoming a necessity, and that’s why we’ve brought together this panel of leaders, who are navigating this transformation from within, who understand both the opportunities, and the risks, and who are helping to shape an AI-enabled future. It’s a very timely conversation, and maybe we’ll even get a few predictions out of it.
As a start to this discussion, I’d like to once again thank our Lead Sponsor, Ernst & Young, for supporting today’s event. EY works at the intersection of AI and professional services. They’ve been helping clients navigate this complexity with clarity and innovation, making them a tremendous partner for today’s dialogue. So, I’m also delighted to invite to the stage Farah Qasemi, Global Client Services Partner at EY, and my former colleague on the Empire Club Board of Directors. I’m delighted she’s here to give intro remarks. Please join me, in welcoming Farah to the stage. So nice to have you back. Over to you.
Opening Remarks by Farah Qasemi, Global Client Services Partner, Ernst & Young
Thank you. Hello, everyone. I’m a little short—there. I’m Farah Qasemi, EY’s Global Client Services Partner for one of the largest banks in the world. I’m also, as Jenna said, a proud past board member of the Empire Club of Canada, and an enthusiast of all things disruption and change. Today’s event not only concerns our firm’s bread-and-butter, it’s just very timely, and hence, even more exciting. Who wants to start a betting pool around the number of times the word “Agentic” will be said in Fairmont Royal York today? Times are changing fast. We’ve all heard the stat that it took electricity 100 years to reach 100 million users, iPhone 10 years, and ChatGPT only two months—and that was three years ago.
If you look at the media and news articles, just in the last four months, you will see that in January, NVIDIA released a $3,000 personal AI supercomputer, that is more powerful than the usual data centre. Then DeepSeek and OpenAI started one-upping each other, in open source LLM powers. Our friend Elon Musk entered the chat, defended peak data, which means there’s no more human data left to train AI. And let’s not forget the T word: tariffs. Dynamic geopolitical environments accelerated the need for AI agents to boost productivity. Our firm started making big, bold declarations around the number of enterprise AI agents they will have by the end of the year. Folks, mark my words: agentic AI workforces will define 2025.
What does all of this result in? A word cloud that has anxiety, confusion, and opportunity, as the top three words. On one hand, there is the futuristic vision, and on the other hand, the reality gap of execution at scale. How do you turn statements made by your CEOs on global stages to reality through adoption, reskilling, and change management, ROI management, regulatory compliance, and governance? Topics I’m sure our speakers will cover at length.
But before we start, just a little bit about EY. At EY, we were the first firm to launch a private and secure LLM called EY.AI. Before we launched the clients, we wanted to build and test our own internal platform, EYQ, you know, on our hundreds of thousands of people selves, as client zero. Fast forward to today, we are all in, as evidenced by our recent partnership announcement with NVIDIA, which you may have recently seen in the news. We’re a multi-billion-dollar firm, located in 150 countries. AI will be a key pillar of our growth strategy, with a clear ambition to become the world’s leading AI powered professional services organization. This massive investment has not been in vain. We’re already projecting $680 million plus in tech productivity gains internally alone, not to mention higher engagement scores amongst our 115,000-plus regular EY.AI users, globally.
Now, with that extended intro, it is my absolute pleasure to introduce your speakers. Please hold your applause until the end. First, our esteemed moderator. Cameron Shuler is the Chief Commercialization Officer and Vice President Industry Innovation at the Vector Institute. He leads a team that works with a community of 32 enterprise sponsors in sectors like banking, telecom, and pharma, to accelerate AI adoption in their workflows, and supports SMEs new to AI.
Our first panellist, Dr. Foteini Agrafioti, is the Chief Science Officer at RBC, and Senior Vice President of RBC Borealis. She’s responsible for the data and AI ecosystem at RBC, and oversees a team of architects, engineers, scientists, and product experts, dedicated to transforming finance through world-class AI research solutions, and a resilient data platform. If any of you tuned into RBC’s Investor Day a couple of weeks ago, you would know how important AI, and Foteini’s job, is to RBC’s strategy.
Second, Colin Lachance is Principal with PGYA Consulting, and current Ontario Bar Association Innovator-in-Residence—I didn’t know a title like that was possible. Former CEO of the Canadian Legal Information Institute, past member of the Global Executive Committee of VLX, three-time founder of legal data and AI organizations, frequent speaker and writer on legal AI, and innovation topics, and routinely consulted by legal organizations, judges, bar associations, media, and legal tech startups.
Last, but not at all least, is Iliana Ores-Valiente. She’s currently the MD and Innovation Lead at Accenture Canada, working with senior executives and boards, to support their strategic transformation journeys. She leads multidisciplinary teams across design, data, and technology, focusing on emerging areas such as metaverse, blockchain, web3, sustainability, AI, and cross-industry initiatives.
Distinguished guests, please welcome Cameron, Foteini, Colin, and Iliana to the stage.
Cameron Schuler, Chief Commercialization Officer & Vice President of Industry Innovation, the Vector Institute
Well, thank you very much. Grateful to be here. So, in terms of presenting some context, in today’s hyper-connected economy, AI isn’t just transforming business. It’s redefining competitive advantage. And while global giants race to secure AI talent, Canada stands at the forefront of this revolution. Our advantage is a thriving AI ecosystem that’s already delivering results. Take Canada’s big five banks. They all rank in the top of the Global AI Index for Innovation and Adoption. And that doesn’t come without an awful lot of hard work, and great partnerships—so, we’re grateful for Foteini, RBC, to be here today. I also want to say thank you to Accenture and EY, who are also founding sponsors of Vector.
So, while there are Canadian companies that are absolutely global leaders, there is a need for more rapid and widespread AI adoption by Canadian industry. Someone who I know will be a driving force, and champion for Canadian industry, is Glenda Crisp, Vector’s new President and CEO—thank you, Glenda. So, Glenda is a seasoned data and technology leader in enterprise AI deployment, data strategy, advanced analytics, and technology leadership. Most recently, she was a head of data and analytics at Thomson Reuters, also a Vector founding sponsor, where she led the enterprise data and analytics strategy, focused on delivering high impact commercial outcomes. And we’re thrilled to welcome you to Vector.
So, before I speak with our panellists, I’ll give you a very quick overview, because not everyone may know about Vector. So, in 2017, Canada was the first country in the world to have an AI strategy—I was one of the authors of that—and Vector was founded at that same time. Now, why was Vector founded? To ensure that Canadian businesses would have the talent they need to compete globally, and in addition to that, that all Canadians would benefit from AI. So, our goal really is to accelerate AI adoption, through giving access to leading edge AI for our partners. In addition to that, the other elements required for success in AI.
So, now, onto the questions. So, Iliana, looking across—so, your role at Accenture, you look across many companies and industries. So, from your perspective, what are you seeing, when it comes to adoption? Which industries are leading, and what are they actually doing differently?
Iliana Oris Valiente, CPA, CA, Managing Director & NA Innovation Hubs Lead, Accenture
So, it’s a great question. And now, I have the pleasure of overseeing our Accenture innovation centres across all of the Americas. So, I can definitely comment on both the Canadian lens, and internationally. In Canada, to your point, we’re doing great from a technology-building standpoint. We’ve seen a bit of a lag on the commercialization side of things, and that’s a role that the Vector Institute is very importantly filling. So, definitely would encourage other organizations to join that initiative.
From the enterprise standpoint, we are seeing use cases across industries. But more interesting than the industry lens, I’m actually finding, is the functional adoption. When I look at certain areas of a business, for instance, marketing, that is the number one area where I am seeing uptake from leaders, because they’re shifting very quickly from early-stage experiments and proof-of-concepts, and finding, oh, wait a second, there is real value here, there is ROI, we can now start to scale this effectively. We at Accenture have been using ourselves as our very own best case study, and using AI and AI agents—so, to the earlier point of how many times we’re going to talk about agentic AI today, I imagine it’s going to be quite a number—but we’ve seen its ability to augment the capabilities of our own in-house marketing teams. And the same is playing out to be true, in a number of industries.
When it comes to the overall industry adoption curve, I’m seeing quite a bit in the consumer packaged goods and retail space, whether it be in personalization and understanding the user requirements, or even in areas like research and development. And using AI, for instance, to make more sustainable packaged goods, as we all push for more sustainable products inside of our supply chains and ecosystems. So, the use cases are numerous. It’s across industries. But there is one piece that I don’t think we talk about enough, which is actually the mindset of the leaders and executives in the organizations that are going to be the most successful in adopting AI. And I can tell you that, at the board level, you need to have buy-in. Because to adopt AI effectively, it is going to be a cross-functional, cross-department type of initiative. And it really needs to be part of a broader enterprise reinvention strategy, so that businesses can be relevant. But if you don’t have leaders at that board of directors that are willing to look holistically at the business, and not assume that there are, you know, certain parts that they can’t touch, then a lot of these initiatives fall flat.
And so, it’s important, for instance, at RBC, you have the leadership support. And I think that’s a really important step in that direction. So, leadership buy-in across all levels of the organization is a precursor to success.
Cameron Schuler
Yeah. We definitely see that across our partners, too, right? That it has to start at the top. And that support really enables people to grow. So, I have a second question for you. So, you’re also wearing your CPA hat today. And so, how are CPAs seeing the opportunities for AI, and how is that changing their business?
Iliana Oris Valiente
I have the honour of sitting on the CPA Ontario Council, where we represent over 100,000 CPAs in the province. And we recently concluded a membership survey. And, in that survey, a whopping 45% of the respondents said that they view AI as a tremendous opportunity for their businesses to, to leapfrog. I think that that’s a really telling statistic, and it’s much higher than where I would expect the general public would be. And CPAs sit in a really strategic, advantageous position within their organizations, because they understand the data, they understand the numbers, and they understand the business objectives. And the ability to criss-cross from those domains is very powerful. And so, the CPAs who are leaning in, and partnering closely with the rest of the C-suite, to choose what are the parts of the business that make the most sense to prioritize launching these various programs, those are the ones that are going to have a disproportionate impact on our adoption curve.
Cameron Schuler
Thank you for that. So, Colin, law is a field steeped in tradition—and if I may be cheeky, let’s say it’s built on a foundation of precedent. So, as you take a look at innovation and adoption based on your role, what does that look like in the legal field?
Colin Lachance, Innovator-in-Residence, Ontario Bar Association
It’s really interesting. Because you find out very quickly, as you look into this, that law is not one thing—which any lawyer would tell you, or any two lawyers will give you four opinions on what law is. And that’s really playing out in AI discussions, and AI adoption. So, whether you’re talking to a two-lawyer firm from Simcoe, Ontario, or a 700-lawyer firm from Bay Street, the international office, and so on, it’s both different and the same, in terms of awareness, understanding, adoption, and readiness. You can find the same enthusiasm at all ends of the spectrum, and the same trepidation at all ends of the spectrum.
So, what we are not seeing is an industry moving forward. What we are seeing are individuals moving forward. So, sometimes you see individuals within a firm, who are outpacing their own firm, in terms of their use and consideration of AI. And at the same time, you can see the office, let’s say the Calgary office might be going ahead in something, and the Toronto office in the same firm considers it a horrible risk that they couldn’t possibly consider. There’s a number of factors that play into that. Precedent is one of them. We didn’t get in trouble for doing it this way yesterday, we’re not going to get in trouble for doing it this way today. So, presumably, we won’t get in trouble for doing it the same way tomorrow.
Cameron Schuler
Seems logical.
Colin Lachance
Seems logical. Where the distinguishing factors come in are the individuals, or sometimes organizations, who will say, “Okay, but things are changing. Even if we’re not changing, the circumstances are changing, our clients’ needs are changing.” We’re certainly seeing it, and it’s unavoidable. So, what changes do we need to make, to be ready to adopt? So, that could be education, it could be experimentation, it could be any one of a number of things—and to use the trite phrase, to skate where the puck is going. So, we are seeing some of that now, but only if you look for it. If you’re not looking for it, you could be in law, and believe nothing has changed. Again, the idea of the teenage sex, everybody talks about it, but nobody’s doing it—that attitude is still pervasive. But things are changing. And I think what we will see, though, before the year is out, you’ll see some of the leaders reveal the value of the leadership positions that they’ve done, and you’ll see the panic set in, in some other areas. It’s all over the map, and it’s really exciting.
Cameron Schuler
But there really is a risk of not adopting fast enough.
Colin Lachance
There absolutely is, but it’s not in the water yet. The feeling of that risk is not in the water. The idea that my phone still rings, the emails still come in, I have more work than I know what to do with, where is the risk? And one interesting thing about law—and I’m not sure if it’s exactly the same with CPAs—is that, so in Ontario, we have, I think, something like 60,000 lawyers; half of them work in in-house environments. And of the remaining half, three quarters work in firms of 10 lawyers or fewer. So, unless they’re actively going out looking for this, they’re not seeing it, they’re not feeling it. And I think that’s gonna begin to change.
Cameron Schuler
So, I’d say the Gretzky quote used was not trite. It seemed to work for him, and I think he’s had some pretty good success in his career.
Colin Lachance
Yeah.
Cameron Schuler
So, should be a good precedent to follow. So, Foteini, RBC is ranked number three in the world for AI innovation adoption. So, congratulations. We’ve known each other for probably 10 years, and have seen you build that up, so, I think that’s pretty awesome, by the way. So, as somebody leading implementation in Canada’s largest financial institution, and one of the largest globally, what are the key lessons that you’ve learned, in terms of successfully integrating AI into established business processes?
Dr. Foteini Agrafioti, Chief Science Officer, RBC; SVP, RBC Borealis
Thanks for the question, Cameron. As you were talking, I was reflecting back to the early days of 2017, as the pan-Canadian AI strategy were coming together. What we know now as the AI ecosystem in Canada was unimaginable. We’ve come so far. At that time, we were going around the country—that’s how we met—we were maintaining these spreadsheets of AI researchers, and they’re graduating, and they’re not taking jobs in Canada, where are they going? Can we build an ecosystem here? And look how far we came. And thanks to Vector—and you talked about the leadership of Canadian banks globally, on AI maturity, and it really has to do with the fact that we’ve benefited from a thriving academic and scientific ecosystem in our backyard, in this country. And had it not been for that concentrated effort, we wouldn’t be to where we are today.
And so, at the Royal Bank, when we didn’t approach AI, because we, out of fear of missing out—I think that would have been quite late. We recognized early, around that time, 2016, I think was when we first realized that we could bring modern machine learning techniques to our business practices across our enterprise, because we use data for one type of decision-making or another, and we could really bring higher accuracies, manage risk better, if we could analyze that data better. And that’s how we started investing. And like any investment, you start in a lab, and you test a few things, and you have early adopters in the enterprise, and along the way, things mature. And we hit a certain point of maturity today, where I would say we’re past the scaling phase, we’re really looking into Horizon 3.
And lessons learned along the way. So, number one, if you’re in an industry outside tech, you still got a lot of work to do, to take these innovations that are coming from that industry, and these domains, into your own domains. And so, while something may look like, out-of-the-box, it will solve a problem for you, or meet your business needs, it usually doesn’t. You can buy it, but you still have to do a ton of work on top of that, to customize it to your data, to your platforms, to your infrastructure. So, there’s nothing really plug-and-play, in AI. And not having domain expertise, I think, is what can set you back. And if we treat these things as we talk a lot about low code, no code, just take it, download it, run it—well, it doesn’t look as simple as that. You can do prototypes like this, but when you try to do serious things with it, you better have a few people in your ranks that understand how these things work, that they’re not black box systems.
So, that’s number one. And then, we want it to be the first in line to, on the forefront of bringing these innovations from the space of computer vision and language into banking domains. Because to us, transaction data matter more, fraud, market data; not video, not so much language—we have some of that, but the vast majority of our data in our servers is core banking data. And so, we want it to innovate in our domains.
Number two is, going into production really quickly with AI, managing risks along the way is very important, that you learn a lot, than holding back, and trying to understand what kind of transformation you will need to go through, or overthinking it. Because a lot of the time, we felt like we had fleshed out an entire business plan, and we would launch an AI, only to find things that could go wrong—not in terms of failures, modes of failures, but in humans overriding an AI decision, for instance. And there’s so many ways that a business like ours, that’s really managed by humans, where humans play a critical role, this can happen.
And the last thing that I would say is, it’s underappreciated how much effort it takes to upfront organize your data, organize your platforms, in order to get in shape, to even use an AI technology. And that would be usually like the last mile. And that is the bulk of the work. And we’ve done that systematically over the years, bringing the data in the right shape, and investing in these things upfront. I actually feel like across the country, whenever I talk to our businesses, we find that a lot of that hurdle to begin is we just don’t have our data in a shape ready to go, ready to be analyzed. And that’s something that you gotta go through, otherwise you—you really can’t skip that step.
Cameron Schuler
Yeah, that’s excellent. So, if you think about advice you might give, or insights you have to other sectors on this, it really sounds like the data piece is the foundation of all of this—I mean, we know that it is—but is that the piece you’d wanna leave people with, on that?
Dr. Foteini Agrafioti
Absolutely, think about where you house your data, how you organize it, how you prepare it, how you clean it—hygiene of the data is very important—that’s one piece of advice. And the other is, call up Cameron at Vector, and talk to them about the type of talent they have there. And I’m being quite honest—like, it’s a joke, but I’m being quite honest about this—you gotta have a handful of people in your companies that will understand what to do with that data. It’s all made to look so easy; in reality, it’s not. And in our backyard, in this city, in Montreal, in Vancouver, in Edmonton, we got some of the best academic institutions in the world. Best destination, I think, globally, today, for science is Canada. And so, take advantage of that.
Cameron Schuler
So, thank you for that. So, a couple of things I wanna touch on, from these questions. So, one that I heard: you have to have support from the top, your leadership has to say this matters. Second part was really around take the bull by the horns, and start learning, start experimenting, start doing, and be a change agent yourself. You brought up the people not accepting jobs in Canada—and when I got in the field, that was absolutely true. But through all the partners that we have—because we certainly couldn’t do it on our own—when it comes to masters students alone, in Ontario, over 90% of them stay in Canada, and that’s because our partners have created opportunities for them. So, I think that’s incredibly important. And then finally, what we started to hear two years ago—because it was always talent, talent, talent, and it still matters—was change management. Because what’s on people’s mind is, what’s gonna happen to me? And so, you can’t lose that piece, either.
So, onto our next question. So, one thing that pops up all the time is return on investment. The infrastructure for this is expensive, getting your data organized is expensive. But the analogy I would draw is the rise of the internet. I would challenge anyone 25 years ago—and we can’t go back in time, unfortunately, not yet—but if we go back in time and say, “What do you think your ROI is gonna be, in terms of going online?” you wouldn’t know what that was; you just knew you needed to do it.
And so, as I think about what we need to do today, Canadian industry needs to move quicker. In Canadian industry, you compete globally, and your competitors are doing it. So, what are you doing to stay on top of that, and stay ahead? So, at RBC’s most recent Investor Day, there was certainly a very large number put out there. RBC is targeting a billion in enterprise value generated by AI, by 2027. So, we love hearing that. I think that’s an incredibly fantastic goal. But from a practical sense, what does that look like?
Dr. Foteini Agrafioti
I’m very busy. I get a lot of calls. But it shows maturity. And I really hope that we get to see that from more Canadian enterprises moving forward, where we get past that early phase of, we’ve experimented use cases, tried it, did it, to how do you generate real value? How do you get that true return? And for us, we felt like we are in a place now, where we can have clear financial targets on our artificial intelligence investments, and we’re very confident that we can deliver. Of course, we put a lot of scrutiny behind numbers like this, when we put them in front of our investors, and we’ve done our homework quite well.
The reason why we feel so confident we can achieve that, and increase the run rate of the bank, thanks to AI, is for three reasons. First, we have a competitive advantage, when it comes to our data, in that we do think it has a ton of insightful potential for the types of applications in the banking industry. And so, we’ve been taking good advantage of that. We’ve been training our own foundation models, created our own intellectual property in this space. And that’s really, really differentiating. We know that we can train models that cannot be replicated by companies that don’t have the amount of clients we have, the years off in the market that RBC has. So, that’s number one.
Number two is, we’ve invested in the talent early on. We’re not new to machine learning. We’ve built our own R&D practice, back in 2016, when we created Borealis AI. And this was an unusual thing for a bank to do. Today, it’s still, I get this question of, like, “Why would a bank do R&D in machine learning?” Well, this is why. Because you accelerate the path to having clear value generated out of these things. But we hired in our ranks PhDs, and postdocs, and professors, that joined us, and found themselves solving, and really getting grounded in banking applications, and how do you build constructively in these domains, and manage risk, and bring explainability into these systems, and solve the myriad of challenges that one has to face in our domains. And we’ve done that. So, we’re past that point.
And then, we’ve systematically invested in our infrastructure. And this has been a journey of, I think about a decade now, where we’re now housing all of RBC’s data in one platform, we call it Lumina. And really, that allows us to unify, and cross-analyze it efficiently. You cannot do modern AI, if you’re still operating in a world of there’s one data store here, one database over there, one there. Making that investment kind of bring them on, invest in the core infrastructure, the compute capacity that is needed, both on-prem and in cloud. We now have, we operate one of Canada’s largest privately-owned GPU clusters, that has allowed us to train large models at scale. And so, all of these investments, we’ve gone to production enough times, we’ve seen value created from our clients, our businesses are leading these efforts. We feel like we got the recipe for success. And that’s, that’s how we ended up announcing this to our investors.
Cameron Schuler
Well, thank you. And I do trust you on that number, by the way.
Dr. Foteini Agrafioti
Okay.
Cameron Schuler
I know you well enough that I’m not worried about that one. So, Iliana, so is it just return driving people’s motivation to adopt AI, or are there other factors inside of businesses that are motivating them?
Iliana Oris Valiente
I could summarize what’s driving a lot of the AI push right now with one word, and that word is: relevance. How does an organization stay relevant, in the future? So, let’s put it this way. In our Accenture Tech Vision Report, that we just published in January, one of the big trends we highlighted was what we call the “Binary Big Bang.” And it’s this idea that the way we build software, the way we build products, has fundamentally changed. I can now speak an app idea into existence. As a non-technical person, you can build a prototype. As a non-creative person, you can build ad copy, that you can test out at scale. Suddenly, it means that the barriers to competition just dropped. And so, for every company, this poses a really cool opportunity to say, how do we take a couple of steps back, and ask these really basic questions of, remind me again why we exist as a business? Who do we serve? Who are our end customers? What is the value that we generate, and we provide to them? And how do we make sure that we modernize our business, to be able to do what our business originally set out to do, using all the latest and greatest technologies of today?
I’ll give you an example. I am working right now with a hospitality company outside of Canada. And they realized that they had so much legacy tech debt, because hospitality as an industry isn’t one that’s particularly modern, if you will. But yet, this leadership team—coming back to this idea of leadership is really important—said, you know, this is also an opportunity for us to start with a blank sheet of paper. And so, that’s what we’re doing. We’re sitting down with the whiteboards, and mapping out why does somebody travel—business travel, personal travel–what is the value chain? Remind me where your business exists there.
We have spent the last 15 years trying to digitize processes. Great. That’s really important. But, in that process, many of us have lost sight of why that business existed, in the first place. And now, organizations are saying, “Well, let’s start with a blank sheet of paper. How do we rebuild these processes from the ground up, to be AI native, to be agentic AI native? To drive the efficiencies, but also, to keep our customers at the centre of why we’re doing this reimagination, to begin with?” Because if you don’t, there is a risk that someone out there in a small garage is going to be able to recreate a lot of the core functionality of what your business products were, at a fraction of the cost, without any of the legacy hurdles.
And so, I think at the core of what’s driving this push is the recognition, like with the internet era. You didn’t know exactly where the ROI was going to be calculated. And even in 2014, not that long ago, when Accenture had one of our Tech Vision Reports, we had said, “Every business is going to be a digital business. And in 2014, people derided that report, and laughed, and said, “We’re not digital. We’re not—why on earth would we need to be a digital business?” 2025, is that a controversial statement? No. Every business is a digital business. And so, every business is going to need to be AI-powered, if they’re going to want to remain competitive.
Cameron Schuler
So, I love that. So, you know, we do hear some companies—to be clear, not our partners—we do hear some companies saying we don’t want to lead; we want to play catch up.
Iliana Oris Valiente
M’hm (affirmative).
Cameron Schuler
So, we know how well that turned out for Blockbuster. So, we hope we learned from that experience.
Iliana Oris Valiente
Yeah.
Cameron Schuler
And that’s really, I think, what I’m hearing from you is, you really have to be stretching, and making sure that you’re leading. So, Colin, we start taking a look at how lawyers are adopting it. Is ROI a driver for them? Is there some other motivation there?
Colin Lachance
I think ROI is definitely among the drivers. It’s, it’s one of the trickier ones, because it’s not the easiest to realize. I mean, in part, because as Foteini was saying, to actually have an appreciation for what your ROI could be, you’d have to know how much work and effort is going into cleaning up your data, you’d have to know how much effort it takes to get through the experimentation phase, into the production phase, and into the adoption phase. And that’s not, typically, been sort of the approach a law firm would take. They would say, “Well, if the ROI has to be—I have a process, it has steps one, two, three, four, five; this replaces steps three and four, and I save X dollars.” It’s a product view of considering adoption of technology, and it has served law firms well, over many years, but it’s not applicable to AI. And many haven’t had that mind shift adoption yet, that they have to think about re-engineering their processes accordingly.
One of the other motivating factors outside of ROI is, is fear—I mean, fear of making an error. So, the volume of information that a law firm deals with has increased by orders of magnitude, over the years. It’s a lot easier to create digital content, and so, there’s a lot more of it. And so, you have to have digital tools, to go through that digital content. And so, the adoption of AI, it’s not foreign to the practice of law. It’s been used in a variety of ways, but in closed off, simple ways. And now, we have to ask, well, how do we decide when to take the bigger leap? How do we decide when to invest more time and effort in exploring the potential of something, when we don’t know the payoff, but we know that it’s necessary?
And similar to what Iliana is saying, it’s, in law, a lot of those questions are being asked and answered by new entrants to the market, by the person who had spent 10 years in a large firm, and now they want to set up their own shop, to take their knowledge, and accelerate the delivery of it. Or maybe, it’s a startup that says, “Well, jeez. There’s a trillion dollars in earnings, in North America, of legal services. Why don’t I take a chunk of that? Instead of serving the law firms with technology, why don’t I just try and find my way to serving the end clients?” So, ROI is not a driving discussion in law across the board, but it is relevant, and it is part of the conversation. Ultimately, it’s, I think, mostly, lawyers are making the decision to adopt based on perceived necessity, first and foremost.
Now, there clearly are exceptions, but they remain exceptions. I just spent the past few days in San Francisco, at an event at Stanford, where you have leading people from major firms, major tech organizations, talking about what they do. And it’s amazing. But then, you find out that, even within their own firms, they’re often the exception, not the rule. So, we’re not at the point. We don’t—the law doesn’t have the same sophistication, again, across the board. I don’t want to ignore the exceptions. There are some amazing firms—including, again, right here in this city—who are doing incredible things with AI. But we don’t have the organizational structure to prioritize ROI, particularly, as a partnership-based business—you know, you’re the owner, and every dollar you put into investment in R&D is a dollar, or less, you take home that year. So, it can be a challenging decision, at this stage, but I think that’s changing.
Cameron Schuler
It makes sense to me. So, we are coming near the end of our time, so I have one more question for our panellists—I don’t know if we’ll get to the Q&A. So, it’s no secret that Canada is lagging in productivity—if you haven’t heard that, then you’re hiding under a rock somewhere. And Bill Gates was quoted earlier, so I’m going to quote him again. “We always overestimate the change that will occur in the next two years, and underestimate the change that will occur in the next 10.” So, when it comes to Canada’s productivity challenges—I’ll go from Iliana through to Foteini—in roughly a minute, how do you think Canada’s productivity challenge can be solved, kind of in near and long term?
Iliana Oris Valiente
Sobering statistic, from that member research I mentioned from CPA Ontario, 50% of the members said that their organizations that they’re employed at are not actively pursuing an AI agenda at the scale at which they should be. So, yes, Canada absolutely has a productivity problem. And with the use of AI, it does give us a chance to focus on the more creative, strategic value-add tasks, that drive the economy forward. But there’s also an opportunity for us to use advanced technologies to fill gaps in our workforce right now. We have over 300,000 vacant jobs in the province of Ontario alone that we cannot fill, because humans do not want to do those jobs. Where is the opportunity for things like advances in robotics? It’s massive. Advances in domains like humanoid robotics, that have skin, and hair, and eyelashes that bat at you, that could potentially be companions to folks in elderly care facilities repeating the same information 12 times over—because we have a shortage of doctors and nurses, and last I checked, we are not about to have more of them falling from the sky. So, there is a tremendous opportunity for us to use all of these technologies at our disposal, to actually drive productivity forward.
Cameron Schuler
Thank you. Colin?
Colin Lachance
I would say in law, one way we should be thinking about it is, we all have the ability to now hire a team of agents to work for us, we all have the ability to serve many more clients individually than we were previously able to do. And considering a significant portion of our clients are business clients, we all have the ability to move at the speed of business, instead of at the speed of law, in supporting those. On the access to justice front, same thing. About 80% of legal needs go unmet, unserved by the legal profession. We have the ability to support that. I think law, through adoption of AI, could offer huge multipliers to both the public welfare, as well as to Canada’s productivity.
Cameron Schuler
Thank you.
Dr. Foteini Agrafioti
And I’ll echo, like, the time liberated with AI is one aspect here, and it’s an important one. But we never went with AI into any of our businesses and said, “Let’s unroot everything we do, replace that with end-to-end AI.” It makes no sense for us to do that. But we always were surprised by bringing AI to life, and seeing how we can grow that business, change it. And a couple of things that we’ve found, number one, when it comes to who banks with RBC, using our data, and our own analysis, and state-of-the-art AI, we’re able to better understand our clients, we’re able to extend more credit to families that we would have otherwise denied, we’ve been able to open up the aperture for who we lend to quite substantially, thanks to AI. We wouldn’t have seen that before. So, that’s one way that you’re growing the business.
Another one, I would say, we got very interesting results by putting this technology in the hands of our employees, especially those that talk to clients, that wanted to upskill towards managing more complex conversations, answering questions about some of our more detailed products, where people would normally shy away. We find that with the support of AI, you can have many of our frontline employees very quickly get confident in answering questions from our clients on a mortgage, or a complex credit product, or a loan, whereas they would otherwise not do that. It changes a little bit the relationship we have with our clients, and it quickly upskills our core employee base.
Cameron Schuler
Well, thank you. So, what I’d like to actually leave everyone with, on this topic, is, obviously, you heard the support from the top matters. That change management piece, and that self-determination for individuals to set their own pathway, that really matters. And so, when you think about adopting AI in your business, and you think about reinventing what you do, bring your people with you. Ultimately, they’re the ones that are going to help change your business. And if we’re not doing this for people, I’m not sure why we’re doing it. So, I do want to thank our panellists, Iliana, Colin, and Foteini. And I’m now going to invite up Jenna Donelson, the chair of the board, for the closing remarks.
Note of Appreciation and Concluding Remarks by Jenna Donelson
Thank you, once again, to our panel. What an illuminating conversation. Wow. There was a lot to take away from that. Let’s give our panel one more round of applause, please.
I’d like to recognize a very important group that we have in the room. We have our students, and young leaders here in the room. We have students from Queen’s University, and from TMU; we’re so glad you’re here, and a part of this conversation. Welcome.
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I also hope you will join us for two exciting upcoming events. On April 23rd, we’ll be exploring the science, skepticism, and financial realities behind the booming longevity industry. We’ll be enjoying insights from leading medical experts, and wealth advisors. So, that will be a very interesting one.
And on May 6th, we are hosting a conversation on corruption in the business world, its rise in global costs, shifting regulatory landscapes, and what you need to know to stay compliant, and protect your reputation. Tickets for both events are on sale now.
As a club of record, all Empire Club events are available to watch and listen to on our website. The recording of today’s event will be available shortly. Thank you all, for being a part of this discussion. I wish you a wonderful afternoon ahead. This meeting is now adjourned. Thank you.
