RBC Insurance

I’m hiring an SEO Content Manager to join my team at RBC Insurance . We’re scaling our GEO and SEO efforts and looking for someone who can help shape how Canadians discover, understand, and engage with insurance content across search and emerging AI-driven discovery experiences. This role sits at the intersection of content, organic growth, client experience, and digital strategy. You’ll help us identify opportunities, build stronger content systems, improve visibility, and make complex insurance topics easier for clients to understand. The ideal person is: ✅ Strong in SEO strategy and content optimization ✅ Curious about AI, GEO, and the future of search ✅ Comfortable using data to find opportunities and measure impact ✅ A strong writer and editor with great content judgment ✅ Able to work cross-functionally with marketing, product, analytics, design, and technology teams This is a great opportunity for someone who wants to help build a modern organic growth engine inside a large organization with meaningful scale.

A personal update, and a piece of writing. Last month I was promoted to Senior Director, AI & Data Product at RBC Insurance , with an expanded mandate covering both the AI & Data product management function I built over the past year and the BI and Analytics function. The work ahead is to bind the two: to connect product thinking with analytical depth, and to build the shared foundation both depend on. Thank you to Sabrina Dicintio, MSc. , my VP, for the confidence and the mentorship that made this possible. And to Vikram Luthra, our Chief Digital, Data & Strategy Officer, for the vision setting the pace for the whole function. Looking forward to delivering more against it in this expanded role. None of this happens without the broader AI & Data team. The colleagues who push, challenge, and ask for changes every day. Now, the article. The second piece in what's become a once-a-year reflection. Across eighteen years working in data and analytics in very different organizations, one pattern has stayed constant: the gap between AI ambition and AI readiness in large enterprises isn't a technology problem. It's a semantic one. The article makes the case for ontology (formal, shared definitions of what things mean) as the foundation the AI conversation rarely puts its energy into.