How Scotia Wealth Management has rolled out its AI platform

Each month at WP, we offer a slate of articles and content pieces that go deep on a particular topic. This month, we're focusing on AI in wealth management.

The banks are adding AI into their processes, and they’ve identified wealth management as a key area where AI can add efficiency and productivity into their advisor’s practices. This narrative reads as clearly on earnings calls and analyst updates from the banks as it does from their advisory teams. At Scotia Wealth Management, the AI opportunity has been identified and now tools are being rolled out across the dealer’s thousands of employees.  

Justin Hughes-Jones, VP and Head, Digital, Data, & AI for Global Wealth Management at Scotiabank outlined how his firm identified the opportunity in AI and worked to drive adoption. Jonathan Rigby, Senior Wealth Advisor, Portfolio Manager at ScotiaMcLeod and chair of the ScotiaMcLeod Advisory Board explained the experience of that rollout in advisory practices and how advisor feedback has been integrated into the whole firm’s approach to AI. In both of their experiences, a balance is being struck between the drive to adopt technology quickly and the need to ensure wide uptake and regulatory compliance.

“We'd been watching the AI journey for a while externally to look at the capabilities and been assessing models since they've become relevant. We were looking for them to reach a maturity level where they could actually drive incremental value,” says Hughes-Jones. "I would say that it was probably fall of last year when they were in that mature state. Then we started to look at how we harden that and secure it in a meaningful way so that we can use it to drive real benefit to our advisors.”

Where Scotia has added AI, so far

Hughes-Jones stressed that the AI rollout at Scotia Wealth Management will involve multiple phases and upgrades. The starting point has been in generative AI tools. These models that function largely as chatbots are similar to what many people now use in their day to day lives with open-access generative AI tools. Broad public familiarity with these tools makes their rollout and uptake far easier, which is key for the early success of a larger tech overhaul. What will follow, Hughes-Jones says, should be more AI tools including agentic AI. The current focus, however, is on generative tools.

That approach has resulted in a roughly 70 per cent of Scotia Wealth employees actively using AI tools in their day to day basis. That uptake, by 6,500 employees and advisors, over only three months shows both a familiarity with the technology at its current state and a view that this can help employees and advisors do their jobs.

The generative tools Scotia AI uses now are largely in meeting prep, information summaries, and compliance reviews. Hughes-Jones says that the upside has largely been found in work that requires the synthesis of information from multiple sources.

“You're spending less time on prep work and allows you to spend a lot more time like actually talking to clients and where you can really be adding the value rather than just trying to put all this stuff together,” says Jonathan Rigby

The advisor experience of Scotia’s AI rollout

While Rigby hasn’t started actively measuring time saved through the use of AI meeting summaries and prep tools, he says that certain tasks which might have taken him 40 minutes now take five or ten. The end result tends to be more consistent, too, and often the AI will find key pieces of information or key requests that might have been more incidental to the conversation. As more advisors are expected to bring in experts on issues like tax and estate planning, those small callouts can be very helpful in making sure a client feels cared for. Most crucially, Rigby says, the reliability of the AI notetaker allows him to listen more closely to his clients, rather than stress about the accuracy of his notes.

This rollout has not been without challenges. The scale of the organization is significant, and the regulatory expectation of data security is very high. While that required an immense amount of work leading up to the rollout of these AI tools, Hughes-Jones says he was surprised by how quickly advisors and employees started using them. He says that a ‘champion network’ of established advisors helped to get teams on board, while Rigby spoke to his experience as a veteran advisor leaning on younger members of his team for tech advice.

Rigby also stressed that there has been an open line of communication between advisors and Hughes-Jones’ team. His own role on the ScotiaMcLeod Advisory Board allows him to provide that feedback directly and explain to corporate leaders how AI tools are being used “on the street.”

What’s next for Scotia Wealth’s AI?

Beginning with generative tools has a number of advantages for a firm like Scotia Wealth Management. For one, these tools are typically less compute-intensive than agentic AI tools or models built for complex software coding. As of now, Hughes-Jones says that the firm has been cognizant of AI costs from the start. They are aware of token costs and he notes that the current use cases are still very comfortable from that perspective. As the firm moves towards the addition of agentic tools and other more compute-intensive forms of AI, Hughes-Jones says the firm will ensure that the full cost of any AI application is taken into account.

While the big Canadian banks may not have a reputation for rapid technology adoption, Hughes-Jones argues that the simple incentive of productivity gains is enough to motivate these large-scale moves.

“AI is a huge productivity lever,” Hughes-Jones says. “You can think about general capabilities that you can build out in isolation that drive an increment of productivity. But AI actually can do this at scale for us. And so a concerted effort to actually understand it can do it safely and do it in a financial sound way can drive compelling value for the customer and for our employees. So it is a key focus for us.”