AI is changing the role of the finance function. How will you lead in the next age of insurance?

Artificial intelligence (AI) is accelerating a fundamental shift in the insurance CFO mandate. What began as selective automation is now changing how quickly financial insight is produced, how cost structures evolve, and how capital deployment decisions are made. For finance leaders, the challenge is how to harness AI to improve performance without eroding confidence, controls, or accountability.

Canadian insurers are already experiencing faster close expectations, more frequent forecasting demands, heightened regulatory scrutiny, and growing pressure to fund growth while managing expense ratios. As AI reduces latency from data to decision, finance leaders are increasingly moving into orchestration, shaping strategy, performance, and resilience alongside the CEO, CIO, Chief Actuary, and business leaders.  

In this article, we share three practical reflections on what is changing now, what is at risk if finance does not actively lead the transition, and where insurance CFOs and finance functions should concentrate their attention to position themselves for sustained success.

Reflection 1: CFOs and finance functions must actively shape enterprise strategy and transformation

AI is pulling finance leaders deeper into enterprise strategy as co-owners of organizational decisions. As decision cycles compress and data volumes increase, CFOs are expected to ensure that insight is fast, trusted, explainable, and aligned to strategy.

This is particularly critical for Canadian insurance finance leaders as they balance speed and insight with IFRS-compliant reporting, capital adequacy, and model governance expectations. A modern insurance finance function is built to adapt as the business changes. In practical terms, it must enable:

• Adaptable reporting that evolves with new products, channels, and regulatory demands.
• Scalable planning and forecasting to support rapid reforecasting, scenario analysis, and capital decision-making.
• Faster close and near-real-time insight that reduces latency from data to executive action.

Achieving this requires tighter alignment across the CFO, CIO, CTO, and Chief Actuary, particularly in three areas:

• Governance and decision rights: ownership of data definitions, assumptions, models, controls, and exception handling.
• Investment prioritization: clarity on what is funded now versus later, and how benefits and risks are measured.
• Data flows to the business: ensuring the right data reaches the right leaders, in the right form, at the right time.

Reflection 2: AI usage and digitization become a top priority

Leading CFOs are already elevating AI to the top of the finance agenda, moving from experimentation to execution. Half of CFOs cite digital transformation as their top priority for 2026, and 87% expect AI to be extremely or very important to finance operations in the year ahead.¹

As AI capabilities advance, their impact depends on finance integrating change directly into its processes. Functions cannot “receive” the future of finance from CIOs or CTOs. In an AI-enabled world, the strongest organizations will be co‑led, with clear decision rights and a shared roadmap that ties measurable outcomes to platforms, data, controls, and the operating model.

More than half (54%) of finance leaders say integrating AI agents into finance will be a top transformation priority. They rank it ahead of improving data quality, access, and usability (52%).² Reflecting this momentum, 63% of organizations report that they have already fully deployed and are actively using AI solutions in finance.³

These deployments tend to be tactical in nature. However, AI’s impact on finance is not limited to efficiency gains. While many early deployments focus on automation, the larger opportunity lies in redesigning finance processes so that technology, data, and governance work together. In this context, finance functions must actively integrate AI into how work is performed, rather than treating it as a tool delivered by technology teams.

As AI adoption accelerates, finance organizations are shifting toward hybrid human–AI operating models, where:

• CFOs and executive leaders set direction, approve judgments, and establish guardrails.
• Controllers and FP&A leaders run hybrid teams and ensure outputs align with strategy and performance objectives.
• Business unit finance leaders provide forward-looking insight and partner more closely with operations.
• Managers and analysts act as human-in-the-loop reviewers, validating outputs and resolving exceptions.
• AI agents handle data aggregation, reconciliations, standard reporting, analysis, and defined actions.

Deloitte research shows how AI and Gen AI can help insurers’ finance functions capture efficiency improvements of over 15%.⁴

For insurance CFOs, AI matters through two connected lenses:

Inside finance, AI is driving productivity, improving forecasting, and shifting teams from compiling numbers to interpreting them. This frees capacity for higher-value analysis and decision support and is reflected in Deloitte’s latest research into Finance Workforce Strategy in the AI Era.

Outside finance, AI is reshaping the economics of insurance itself. Changes in underwriting, claims handling, distribution, and customer engagement are altering cost curves and competitive dynamics, placing greater pressure on pricing discipline, expense management, and capital allocation.

Wherever an organization is on its AI journey, alignment across the C-suite on how AI supports business strategy is a critical success factor. Organizations also must manage the new risks that come with greater automation, model reliance, and complexity.

Reflection 3: The finance workforce must evolve alongside technology

As AI becomes embedded in finance processes, the nature of finance work is changing just as significantly as the enabling technology. Over time, routine task execution will increasingly be handled by intelligent agents and integrated platforms, while human effort concentrates on judgment, accountability, and influence. In Deloitte’s Finance Trends 2026 survey of nearly 1,500 global finance leaders, respondents ranked AI, automation, and data analysis/technology integration as a top finance skills development priority through FY2026, in addition to strategic decision making and leadership and adaptability.  

The key challenge for CFOs is ensuring AI‑enabled operating models preserve accountability, auditability, and confidence in financial outputs as automation scales.

A practical roadmap for CFOs

To move from intent to impact, CFOs should focus on a structured, attainable adoption approach:

Strategic alignment and prioritization

• Align on an AI vision with leadership, define how it supports enterprise goals, and prioritize high‑confidence use cases based on strategic relevance, and execution readiness.

Data readiness

• Identify available, fit‑for‑purpose data that can support near‑term, high‑value AI use cases.
• In parallel, invest in cleaning, standardizing, and governing data to expand what’s possible over time.

Technology foundation

• Assess fit versus gaps to evaluate what your current finance and operational platforms can support, what vendor roadmaps are likely to enable next (including how advanced AI capabilities are being built into solutions), and where true capability gaps remain.
• Use this fit‑gap view to make disciplined build‑versus‑buy decisions, in close alignment with the CIO, CTO, and, where relevant, the Chief Actuary, so technology choices reinforce a shared AI vision and the broader business strategy.

Talent and operating model

• Identify priority upskilling areas and define the future AI operating model.

Change management

• Engage stakeholders early and communicate progress and value delivered.

Budget

• Determine budget for process redesign, software, hardware, people, and training.
• Ensure holistic understanding of AI/token usage and costing across full architecture.

Risk and governance

• Establish guardrails that enable trust and scalability.

How Deloitte can help

Deloitte has experience supporting finance leaders through immersive, outcome-driven experiences like the Finance Lab or Finance AI Simulator Lab, designed to help leaders align strategy, break through complexity, and accelerate value realization. Our leaders would welcome a discussion or short working session to benchmark your finance AI roadmap and operating model against what we are seeing across insurers.

For many finance leaders, the next step is not accelerating pilots, but stepping back to assess whether AI initiatives, governance, and operating models are truly aligned to enterprise strategy. A focused discussion can often help clarify priorities, risks, and the path to scalable impact.