Realizing AI’s Promise: Our Five Core Principles

Published April 23, 2019 | 4 min read

Key lessons to build top-to-bottom business buy-in for AI technology

Introducing transformational technology creates unique challenges for a business—and there are countless ways it can go wrong. Throw AI into the mix, with the myths and misconceptions that surround it, and the challenges multiply.

When RBC set out to bring the full power of AI to trading for the benefit of its customers, leaders were acutely aware that, to succeed, they needed to generate broad support across the organization – from the C-suite to front-line employees and beyond. Underlying RBC’s approach was a philosophy about the responsible use of AI that starts at the top: “The foundation to AI is people and data, and therefore, what we're dealing with as a society, broadly, and financial institutions are in the middle of it, is how do we secure the trust of keeping that data, storing that data, and being transparent in how we're using that data,” says RBC CEO Dave McKay. “As a society, we're on that journey, but certainly, it's incumbent upon institutions who want to use that data to honor three pillars: transparency, control and value exchange with customers.”

Following, here are key lessons from RBC’s approach to making everyone involved comfortable and confident that a new technology is best for customers, employees, and the future of the business.

 

1.Lead with steadfast direction. AI is one of the most transformational—and potentially disruptive— technologies impacting business today and it is shaping the future of financial services. But groundbreaking AI research doesn’t happen on a set schedule—no one knows if the breakthroughs will come today or in two years. At RBC, the teams working on AI trading needed to know they had the institutional support to do the job right, whatever it took. They found champions in McKay, who comes from a software background himself, and the RBC board of directors, all of whom fundamentally agree that innovation is critical to their future. “I'm very confident in my belief and understanding that RBC is a relationship-driven business, and it will remain a relationship business,” says Lea Hutton, co-head of North America cash equity trading at RBC and a 23-year veteran of the company. “But I also recognize that AI technology can help me do my job and help our clients at a higher level.”

2.Share your vision to attract the best talent. Competition is fierce for top AI talent, and top researchers often end up at firms like Google and Facebook. Convincing leading AI scientists to join a bank—the kind of company many of them would not traditionally consider—took a lot of work. Fortunately, McKay could make a persuasive case for the opportunities at RBC while speaking in top researchers’ language. “Dave would ask very specific, very smart questions about the technology—things most people wouldn’t understand,” says Dr. Foteini Agrafioti, RBC’s chief science officer and the head of Borealis AI, a research institute run by RBC. “On several occasions, he sat down with professors we were recruiting into Borealis AI and talked to them about his vision. It’s the kind of thing you’d expect from the founder of a startup, not the CEO of a major bank.”

3.Listen to each other’s perspectives. When introducing complex technology like AI, perhaps the most critical tool is also the most basic. “Communication is the key to doing just about anything right,” says Hutton. Leaders at the RBC took pains to connect the traders with its AI scientists, who initially didn’t understand each other’s roles or speak the same language. “Once you get people talking, communication becomes an organic exercise,” Hutton says. “You’re learning something, you’re giving information back, and the conversation just builds from there.” It was realized early on how important it was for all parties to feel heard and understood and set teams up well to do great work and develop cutting-edge AI technology.

4.Be transparent to ease fears. AI’s very nature elicits questions related to integrity and trust. “We all recognize that employees have concerns,” says Hutton, “and we’ve worked hard to encourage them to talk about their worries so we can address them. We know that’s a part of the process that we have to get right.” RBC anticipated difficult questions and the anxiety they can produce and aimed to respond with openness and honestly. AI requires change, and of course, education and reskilling, but that doesn’t have to be a source of fear. “Yes, we are looking to build out an entire ecosystem [with AI],” Hutton says, “but that ecosystem isn't going to just happen overnight. Everybody will have an opportunity for input.” To help ease skepticism, the culture RBC has created around transformation starts at the very top, with its CEO. “The conversation we have with employees, in an honest way, is about the journey we’re on,” says McKay. “Transparency and trust are really important in how you build something.”

5.Build on past successes. Artificial intelligence is just the latest in a long line of industry-leading breakthroughs at RBC. In the 2000s, the firm developed THOR, groundbreaking technology that leveled the playing field in electronic trading by allowing RBC clients to compete with high-frequency traders. “Increasingly, employees recognized that advances like THOR are what allow us to maintain a significant lead over our competitors,” Hutton says. “Today, we’re all realizing that these latest changes aren’t going to drive success just for the AI scientists or the tech group. They’re going to help RBC succeed.”

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