Canadian insurers have poured money into digital projects in recent years – but too many are still using new tools to prop up old operating models rather than truly reimagining how insurance works, according to Melissa Carruthers (pictured), partner and insurance consulting leader at Deloitte Canada. In a recent Deloitte analysis, she and her team outlined five “megashifts” they believe will define the next decade of insurance – from always‑on advice to outcome‑based products, proactive customer engagement, AI‑powered operations, and ecosystem partnerships.
Asked which of those five shifts Canadian carriers are least prepared for, Carruthers didn’t hesitate: reimagining insurance operations.
“In the last two or three years, there has been notable investment made by select carriers that have demonstrated clear pivots in their strategy,” she told Insurance Business. “Some are well-positioned for the future if they continue on their current trajectory.” But across the market, she believes the biggest readiness gap is in operations – and, specifically, in how insurers are (and aren’t) using AI and emerging technology.
“It is very difficult to keep pace with how quickly these technologies are evolving,” Carruthers said. “I still think many insurers are taking a similar approach to how they leveraged other automation technologies in the past – applying them to isolated use cases, which limits scalability and the benefits they realize.”
For her, that’s the core of the problem: too many transformation efforts are still treated as technology projects, not business rewrites. “This cannot be a technology‑led initiative, it’s a business transformation,” she said. To truly reimagine insurance operations, mindsets need to shift and business, technology and people leaders need to find common ground to enact change.
Carruthers sees AI sitting at the centre of that shift.
Over the next three to five years, she expects the biggest visible change to be a move “from manual, case‑by‑case work to automated, insight‑driven workflows” across underwriting, claims, distribution, and customer service. In practical terms, she said, routine tasks such as data entry, document reading, triage, initial underwriting assessments, fraud screening and even parts of claims adjudication are likely to become AI-led processes, freeing teams to focus on complex judgment, empathy and exception handling.
“That has the potential to materially reduce cycle times, improve accuracy, and allow insurers to run more efficient and adaptive operations,” she said.
Beyond automation, she expects AI to enable “real‑time, dynamic decisioning” using a much broader data set – from telematics and IoT sensors to financial patterns, health insights and climate data. In that environment, underwriters and claims adjusters are more likely to work alongside AI copilots that synthesize risk factors in real time, propose pricing or reserve adjustments, and flag anomalies before they escalate.
On the front line, customer‑facing teams and advisors could see similar support. Carruthers pointed to AI‑powered assistants that surface relevant information, compliant disclosures and tailored recommendations based on a customer’s profile, “dramatically improving consistency and quality in the experience delivered.”
AI, she added, will also reshape how insurers manage strategy, innovation and workforce models. Product development cycles could shorten as AI identifies unmet needs and simulates customer responses, while employees “increasingly work with AI copilots, orienting skills toward oversight, interpretation, and relationship management.”
For all that promise, she warned that the biggest danger is still cultural, not technical.
“The biggest risk is treating AI like another technology rollout,” Carruthers said. “Insurers still stumble when they bolt AI onto old processes or ignore workforce implications. This needs to be treated like a transformation, where the processes, operating model and roles are also being redesigned.”
Carruthers’ advice for mid-sized carriers is to start with the basics: test whether today’s strategy can survive tomorrow’s market.
“A mid-sized Canadian insurer should start by stress-testing its current strategy against emerging industry shifts,” she said. That means asking whether current investments, initiatives, value propositions and capabilities will really allow them to compete as AI, new ecosystems, sector convergence and shifting customer expectations reshape the sector – and being honest about the gaps.
Leaders, she argued, need to “identify strategic gaps and risks – then make deliberate choices about where to double down, where to reposition, and where new capabilities or partnerships are required.”
From there, she wants to see a much more ambitious approach to AI.
Insurers, she said, now need a clear plan for scaling AI “across the enterprise,” not just sprinkling pilots around the edges. “This is no longer about isolated automation use cases tacked onto existing processes,” Carruthers said. “It’s about reimagining how and what work gets done.”
Over the next 12–18 months, she believes carriers should be defining an AI operating model, prioritizing end-to-end workflows for reinvention, modernizing data foundations, and planning in detail for how AI will reshape roles, governance and workforce skills. “Treating AI as incremental change will leave carriers behind,” she said. “Future‑proofing requires a programmatic approach to embedding AI throughout the blueprint of an insurance organization.”
The final piece, in her view, is people.
“Insurers need to evaluate whether they have the leadership, talent and culture to compete in the insurance landscape that’s emerging,” she said. The traits that will matter most are the ability to adopt new tools, redesign processes and learn continuously. “Future‑proofing the business ultimately requires future‑ready people and change‑ready leaders.”
