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Insurance and AI in Canada: Reimagining the SDLC

Author

Tarun Dehariya
Vice-President, Consulting Services , Insurance Sector Lead, CGI

March 2026

Canada’s insurance industry is at a defining moment in its digital evolution. Insurers are navigating unprecedented volatility driven by climate-related catastrophes, evolving customer expectations, regulatory change, and rising fraud sophistication. At the same time, geopolitical uncertainty and economic pressures are increasing operational complexity.

Modernization is no longer optional. Across personal, commercial and life insurance, traditional operating models are under strain as legacy systems struggle to keep pace with demand for faster, safer and more adaptive technology delivery. Common challenges include:

  • Claims backlogs and extended cycle times that erode customer satisfaction, especially during catastrophic events
  • Ongoing regulatory changes — from the International Financial Reporting Standard (IFRS) 17 to evolving privacy and artificial intelligence (AI) governance — requiring frequent system updates
  • Increasing fraud complexity as digital channels expand the attack surface
  • Growing demand for product agility, including usage-based insurance, real-time underwriting and personalized coverage

Real-world examples illustrate the urgency. Life insurers operating decades-old policy administration systems face major barriers when introducing new products or updating rating tables. Health and group insurers responding to shifting policy mandates must revise claims rules and provider networks in weeks, not months. Lengthy software development cycles are no longer sustainable.

In this context, (AI) — particularly generative, predictive and agentic AI — is emerging as a critical enabler for modernizing the software development life cycle (SDLC).

Recent research shows that insurers increasingly view generative AI (GenAI) as critical to future competitiveness. Notably, 46% of insurance executives report achieving expected outcomes from their digital strategies, up from 38% in 2024.

As a result, AI has moved beyond experimentation and is becoming a practical business capability across the SDLC. From requirements and analysis to deployment and maintenance, AI accelerates delivery, enforces compliance, and frees teams to focus on innovation.

Accelerating Processes

AI’s true value comes when it is embedded across the full life cycle — from ideation and requirements to deployment and operations. Development cycles that once took months are being reduced to weeks.

By embedding AI into compliance checks and document reviews early, insurers can reduce downstream risk while freeing legal and regulatory teams to focus on higher-value work. Automation in test generation, defect detection, and code validation boosts productivity and consistency. Early adopters are reporting double-digit reductions in cycle time and operational effort, alongside improved quality.

In an industry where advisors remain a primary distribution channel, digitization combined with AI-enabled SDLC acceleration has a direct impact on advisor productivity and satisfaction. Faster delivery cycles help insurers provide the seamless, real-time experiences advisors increasingly expect. Importantly, speed must be paired with maintainable code, strong governance, and human oversight to avoid new risks and technical debt.

Meeting Expectations

Customer expectations for personalization, transparency and responsiveness continue to rise. Meeting these expectations requires greater agility across the SDLC, ensuring system updates are reliable, secure and aligned with regulatory and trust requirements.

AI enables this agility by improving responsiveness while supporting transparency in decision making. When paired with appropriate governance, AI-powered SDLC practices reduce friction, improve compliance outcomes, and strengthen confidence among customers, advisors and regulators.

AI Is Transforming Roles

AI is not replacing people — it is modernizing how work gets done across actuarial, underwriting, claims, policy administration, group benefits operations, IT, and digital teams:

  • Analysts validate AI-generated requirements rather than starting from scratch.
  • Testers shift from manual execution to automation oversight.
  • Developers move from repetitive coding to creative design and integration.
  • Product managers use AI-driven insights to align delivery with consumer and business goals.

Figure 1. The Enabler Across Every Role and Stage


Despite progress, gaps remain. Additional research shows only 43% of organizations have a holistic AI strategy, underscoring the opportunity for insurers to align AI adoption more broadly across functions and partners.

AI in Action

Early adoption of AI-enabled SDLC practices is already delivering measurable benefits. In one example, a large life insurer operating across North America and Europe modernized its testing and quality assurance (QA) processes using AI. The initiative delivered measurable improvements across speed, coverage and team effectiveness:

  • 45% reduction in test preparation time
  • 58 days saved across 11 concurrent projects
  • Test coverage improved to 70 to 85%
  • QA teams shifted from repetitive tasks to automation oversight and innovation

In another case, AI-assisted development approaches enabled the delivery of a digital claims portal in weeks rather than months, demonstrating how modern SDLC practices can accelerate time-to-market for customer-facing capabilities.

Beyond development and testing, insurers are applying AI to operational processes through approaches such as AIOps — also known as AI for IT operations. These capabilities help teams monitor environments, anticipate failures, and improve system resilience, supporting stronger business continuity in complex, regulated environments.

Looking ahead, orchestration platforms and low-code approaches are emerging as important enablers of SDLC transformation. By connecting requirements, testing, release, and operations within governed workflows, these platforms point toward faster releases with consistent compliance and control.

Overcoming Fear

The first step toward an AI-enabled SDLC is not technology — it’s mindset. An organizationwide shift from “AI as threat” to “AI as enabler” is crucial — reducing manual work, improving accuracy and elevating professional judgment.

Successful organizations adopt AI in a structured, trust-first way: starting with internal processes, embedding human oversight and governance from the outset, and measuring return on investment (ROI) at each stage. This approach builds confidence and creates a foundation for responsible scaling.

Bottom Line

AI is here to stay. For insurers, the opportunity is to transform the SDLC into a faster, safer, more compliant engine of innovation — supporting more accurate risk assessment, rightsized premiums and faster claims resolution. 

Orchestration and agentic AI point to the future. The path forward is clear: start small, build trust and scale strategically. Insurers that embrace this journey will accelerate delivery, strengthen compliance and improve consumer outcomes. Those that delay risk being left behind.

 

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