Turning Disruption into Momentum: Manulife’s AI Flywheel

It was mid 2020. Jodie Wallis, then Manulife’s Global Chief Analytics Officer, had summoned the company’s top executives into a Toronto boardroom. She knew the meeting would mark a turning point: OpenAI’s breakthrough latest large language model (LLM), GPT¹– 2 had just been released, and, at nearly 100 times stronger than its previous models, GPT-2’s implications stretched far beyond the technology itself. For Manulife, a 137-year-old insurer built on actuarial precision and risk discipline, the question was whether this new capability would be treated as a passing novelty, or as the spark for deeper change.

For years, AI at Manulife meant prediction and automation—underwriting models, fraud detection, lead scoring. Even as the frontier advanced with machine-learning models that could conjure hyper-realistic images, these applications still felt contained within the realm of “computer things.” They were useful and very impressive but safely bounded by expectation.

To Wallis, large language models like GPT shattered those boundaries. Designed for an iterative exchange, they created value not through a single output but through an unfolding dialogue—shifting the dynamic from command-and-response to something closer to collaboration. LLMs could now reason with a human-like cadence, inviting conversation rather than instruction. The breakthrough was not a more polished “answer,” but the model’s ability to so fluidly augment inquiry itself—generating new directions of thought and discovery.

That shift—from bounded tasks to open-ended discovery—was as unsettling as it was exhilarating. Wallis framed the moment with unusual candor: “Our industry has been too comfortable. This technology isn’t just another tool—it’s a fork in the road. We either harness it, or risk being reshaped by it.”

Around the table, reactions varied: curiosity, excitement, apprehension. The challenge was immediate. Should Manulife treat generative AI as an experiment at the margins, or as the new trajectory of the business itself? Wallis herself was convinced of the answer, but she also knew the technology was still raw—too raw, perhaps, for the boardroom to fully accept. The choice would force hard calls about strategy, governance, culture, and investment, all at the breakneck pace at which the frontier was advancing.

In such moments of technological upheaval, corporate boards look to figures like Wallis to distinguish passing trends from transformative forces. Unlike the technologist-soothsayers popular at the time, her task was consequential: to foresee how generative AI might reshape an institution built on actuarial discipline, and to ensure Manulife seized the opportunity rather than being undone by it. Frame the moment correctly, and new value could be unlocked; misjudge it, and the consequences could be existential.

But foresight alone would not suffice. Wallis knew no memo or slide deck could capture the implications of generative AI; words on a page risked being dismissed as abstractions. The only way forward was direct confrontation. To overcome that gap, one had to experience it themselves. Fortunately, the technology itself offered an answer—the opportunity to turn the crystal ball around and let skeptical peers glimpse inside for themselves.

So, she placed a tablet in front of each leader, preloaded with the latest OpenAI model, and invited them to test it—to ask it the questions they might otherwise have asked her. The room fell silent as screens lit up with blinking prompts. One by one, Manulife’s senior leaders began conversing with GPT-2, watching as it generated fluent answers in real time. The exercise was disarmingly simple, yet it shifted the atmosphere. Within minutes, the conversation had moved from “is this real?” to “what does this mean for us?”—the kind of pivot that months of memos and meetings could never have achieved.

It was Wallis’s decision—to make her colleagues experience the frontier for themselves—that created conviction at the top. But she knew conviction alone would not be enough. To matter, it had to be built into infrastructure, and then into the agility to adapt. With that boardroom experiment, Wallis set the flywheel in motion—conviction, infrastructure, adaptation—that would carry Manulife through one of the most profound technological shifts in its history. In doing so, Manulife joined a small group of financial giants positioning Canada at the forefront of AI transformation.

To understand how this journey unfolded, RBC Thought Leadership sat down with Jason MacDonald, Chief of Staff in the Office of the CEO, and Jodie Wallis—now the company’s Global Chief AI Officer—to explore how they and their colleagues steered a $72-billion insurer through one of the most profound technological shifts in its history.