Insurance companies are fundamentally shifting how they approach artificial intelligence, moving away from disconnected pilot projects toward comprehensive transformation strategies that deliver measurable business outcomes. A new report from Information Services Group (ISG), a global technology research firm, reveals that insurers increasingly seek advisory relationships combining strategic planning with execution oversight, signaling a maturity shift in how the industry views AI adoption.

What's Driving This Change in Insurance AI Strategy?

The insurance industry faces mounting pressures that are reshaping AI priorities. Margin compression, regulatory complexity, shifting customer expectations, and climate-related loss volatility are forcing organizations to demand more from their technology investments. Rather than funding disconnected experiments, insurers now want clear connections between AI initiatives and business impact. This represents a fundamental pivot: the question is no longer whether to use AI, but whether AI investments are improving decisions, managing risk, and creating measurable value.

A parallel challenge is emerging across Canada, where nearly half of business leaders (46%) are experimenting with AI without achieving meaningful return on investment (ROI). Only 18% have successfully embedded AI into workflows and operations, according to BDO Canada's AI Vision Report. This gap between experimentation and execution is becoming the defining challenge for enterprise AI adoption.

How Are Leading Insurers Redesigning Their AI Operating Models?

Forward-thinking insurers are designing AI-first operating models to address specific business problems. These organizations are targeting improvements across multiple functions:

• Underwriting Optimization: Using AI to enhance risk assessment and pricing accuracy in policy underwriting
• Claims Processing: Automating and accelerating claims evaluation and settlement workflows
• Fraud Detection: Deploying machine learning to identify suspicious patterns and reduce claims fraud
• Customer Engagement: Personalizing customer interactions and improving service delivery through AI-powered systems

However, scaling AI responsibly requires more than technology deployment. Organizations must address governance, workforce capability, and operating discipline simultaneously. Advisory engagements increasingly include organizational readiness planning and workforce enablement to help insurers integrate AI into everyday operations.

BDO Canada emphasizes that this shift requires treating AI as an operating model change, not simply a technology purchase. The firm notes that by 2028, one-third of enterprise software applications are expected to include agentic AI capabilities (AI systems that can perform multi-step tasks autonomously), up from less than 1% in 2024. This acceleration means organizations must build foundations for responsible scale now.

What Are the Key Foundations for Scaling AI Responsibly?

Experts identify several critical elements that separate successful AI transformations from stalled pilots. According to BDO Canada's research, organizations moving beyond experimentation need to establish:

• Clear Governance Structures: Defined decision-making authority, accountability frameworks, and policies for AI deployment across the organization
• Workforce Readiness and Enablement: Training programs and capability building to help employees understand and work effectively with AI systems
• Workflow Integration: Embedding AI into actual business processes rather than running isolated pilots disconnected from daily operations
• Measurement Tied to Business Outcomes: Establishing metrics that connect AI initiatives to revenue, cost reduction, risk management, or customer satisfaction
• Data Strategy and Quality Assurance: Ensuring data reliability and governance to support AI decision-making across the enterprise

"The next gap will not be between organizations using AI and not using AI. It will be between those redesigning work around AI and those funding disconnected pilots. As AI moves beyond the chat phase and into workflows, leaders will need to be clear on what problems they are solving, who is accountable for the outcome, what data can be used, whether that data is reliable enough to support the work, and how value will be measured," said Bill Syrros, National AI Leader at BDO Canada.

Bill Syrros, National AI Leader, BDO Canada

Insurance enterprises are also reassessing broader business models to address profitability challenges. Many organizations are reviewing distribution economics, capital allocation, portfolio composition, and cost structures as part of comprehensive transformation programs. This holistic approach recognizes that AI success depends on alignment between technology, operations, and business strategy.

How Are Global Insurers Managing Complexity Across Regions?

Large multinational insurers face an additional layer of complexity. These organizations must pursue greater alignment across regions while managing diverse regulatory environments. They are developing cross-border data strategies and evaluating regional growth opportunities as part of broader transformation programs. This increases demand for consulting providers with established global insurance practices, deep regulatory knowledge, and experience supporting complex multinational initiatives.

The ISG report evaluated 45 advisory providers and identified 18 leaders in strategic advisory and enablement services, including Accenture, BCG, Capgemini, Cognizant, Deloitte, EXL, EY, Genpact, IBM, Infosys, KPMG, McKinsey & Company, NTT DATA, Oliver Wyman, PwC, Sutherland, TCS, and Xceedance. Additionally, Kyndryl and Wipro were named as Rising Stars, companies with promising portfolios and high future potential.

"Insurance companies are seeking greater accountability from AI and transformation initiatives and clearer paths to business impact. Organizations increasingly value advisory relationships that connect strategic priorities with practical execution and provide insights on buying AI transformation outcomes with true ROI," explained Dennis Winkler, Director of Insurance Industry at ISG.

Dennis Winkler, Director, Insurance Industry, ISG

The shift toward measurable outcomes reflects a broader maturation in enterprise AI adoption. Rather than pursuing AI for its own sake, organizations are demanding that advisory partners demonstrate sustained business impact over time and support transformation programs from strategy through operationalization. This accountability focus is reshaping the consulting landscape and forcing providers to move beyond pitch decks to proven delivery models.

For Canadian organizations specifically, the challenge is even more acute. With 27% of business leaders believing AI will have minimal impact on their organization over the next four years, there is a significant visibility gap as AI becomes increasingly embedded into enterprise software and workflows. This suggests many executives lack clarity on how AI is already reshaping their competitive landscape.

The insurance industry's evolution from pilot-focused to outcome-focused AI adoption signals a broader shift across enterprise sectors. Organizations that build governance, workforce capability, and measurement frameworks now will be positioned to capitalize on agentic AI capabilities as they become standard in enterprise software. Those that continue funding disconnected experiments risk falling further behind competitors who have already connected AI to measurable business value.