RBC Estimates $1B in Revenue Lift by Embedding AI in Core Banking

Royal Bank of Canada is deploying artificial intelligence at the operational core of its business, across developer workflows, capital markets infrastructure and enterprise decision-making as the bank pursues a stated target of up to $1 billion in AI-generated enterprise value by 2027.

The shift positions RBC as a leader in what scaled AI adoption looks like at a major financial institution and raises the bar for how banks are expected to compete on AI capability going forward.

Developer Productivity and Internal Workflows

RBC has deployed generative and agentic AI tools across its developer population to compress iteration cycles, reduce time spent on repetitive tasks and accelerate product delivery. AI coding assistants help engineers move from idea to shipped feature faster, while workflow automation handles work that previously consumed analyst and developer hours.

The logic is structural: If AI multiplies throughput at the engineering layer, every downstream product and client-facing system benefits from shorter development timelines.

That productivity push extends well beyond engineering. Nearly 27,000 RBC employees now use RBC Assist, the bank’s internal AI assistant, as part of daily workflows. The internal AI infrastructure supporting these deployments is RBC Lumina, the bank’s enterprise data and AI platform, which runs on one of the largest private-sector graphics processing unit clusters in Canada, second only to the federal government’s.

Capital Markets and the Aiden Platform

RBC Capital Markets has produced the bank’s most operationally measurable AI outcomes through its Aiden platform, developed in partnership with Borealis AI and built on Nvidia AI Enterprise.

The AidenResearch platform deploys specialized AI agents across the Global Research division, automating earnings content generation, call summarization, data catalog analysis and real-time filing access. The effect on analyst capacity is direct: AidenResearch is designed to allow a single analyst to cover up to 50 companies rather than the traditional 15.

The performance metrics are concrete. Document processing capacity has increased tenfold. Research report generation is up to 60% faster. Complex client queries that previously required hours or days are now answered in near real time. The timeline for discovering alpha patterns is projected to shrink from 12 months to two.

RBC is extending the platform further with AidenBanker, a unified system for investment bankers that connects automated pitchbook creation, premeeting preparation and note-taking into a single workflow. More than 8,000 capital markets employees are already using the Aiden platform.

Bobby Grubert, head of AI and digital innovation at RBC Capital Markets, described the partnership with Nvidia as generating “customized generative AI solutions to unlock talent productivity and deepen engagement through more data-driven client experiences.”

Enterprise AI Strategy and Organizational Scale

To coordinate AI deployment across all its business segments, RBC announced the creation of a dedicated AI Group reporting directly to CEO Dave McKay. The move formalized what had previously been distributed AI activity into a centralized function with a mandate to identify, develop and scale the bank’s highest-potential AI use cases.

Bruce Ross, a 12-year veteran as group head of RBC Technology and Operations, was named to lead the new group. In an interview with Investment Executive, Ross framed the bank’s commitment in precise terms. “We committed to delivering $700 million to $1 billion of net benefit to RBC, our shareholders and investors through AI execution on a run rate basis by the end of 2027,” he said. RBC spends more than $5 billion annually on technology, and AI investment is explicitly embedded in that figure.

According to Newswire, RBC ranks first in Canada and third globally for AI maturity among financial institutions in the 2025 Evident AI Index, which assessed 50 banks worldwide. Underlying that ranking is a proprietary foundation model, ATOM, built by RBC Borealis with more than 100 researchers and trained on the bank’s financial datasets.

ATOM was used across 15 RBC products and processes in 2025. The bank has filed more than 1,200 patents since 2019, with 635 directly related to AI.

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