The landscape for life and health insurers is becoming increasingly complex. The sophistication of product portfolios is growing, regulations are getting stricter, and financial reporting teams are under mounting pressure to quickly deliver accurate and comprehensible results. Despite these challenges, operational costs and talent pressures continue to be high. Amid these challenges, artificial intelligence (AI) has emerged as a transformational force with the potential to redefine workflows.
However, the question remains: what role is AI playing in actuarial and financial reporting today, and what could its emergence mean for the people and processes behind the numbers?
Driving Efficiency with AI
Over the past decade, AI technologies have evolved from simple statistical models to advanced foundation models, reasoning engines, and now AI “agents”. This development is no longer theoretical; insurers are already applying standard tools to accelerate routine work, reduce operational burdens, and boost team efficiency by approximately 30%. AI agents are increasingly contributing to human efficiency by leveraging advanced software capabilities and functioning as actuarial accelerators.
One area where AI’s impact is particularly noticeable is model documentation and code translation. For instance, at WTW, we have developed tools that translate actuarial code into clear, natural-language documentation, saving around 75% of the effort on these essential activities. Moreover, AI tools that translate open-source code and Excel spreadsheets, and build from specifications, can reduce overall implementation costs by a similar proportion.
Insurers are also employing AI to support data validation and cleansing, bulk document parsing, trend and variance analysis, narrative drafting, and financial report preparation workflows, in addition to customer service triage. Though these use cases offer incremental gains individually, when combined – especially when used within agentic architectures – the impact compounds quickly. Many insurers are now seeing 20–30% efficiency improvements in reporting cycles where AI has been purposefully embedded.
AI vs Humans: Augment or Replace?
While fears that AI will replace actuarial or financial reporting talent are understandable, currently these fears are exaggerated. Judgment, accountability, regulatory interpretation, and interpersonal communication remain fundamentally human responsibilities.
However, the nature of early and mid-career work is indeed changing. As AI replaces more routine tasks, entry-level roles will rapidly shift towards interpretation, scenario analysis, and communication of results. This transition will necessitate changes in organisational design, skill portfolios, and recruitment patterns.
The biggest hurdle for most teams today is not technology, but limited imagination. The real opportunity lies not just in using AI to fix known errors in a dataset but in leveraging it to validate data for unexpected issues or even to redesign the end-to-end process. Creativity and vision will set the winners apart from the followers.
The Importance of Human Oversight in AI
Even as AI assumes a more prominent role, human oversight remains crucial. This is particularly true in the tightly regulated environment of financial reporting, where model governance frameworks, audit trails, and sign-off processes leave little room for opaque or unexplained AI behaviour. This means AI outputs must be reviewed by accountable humans, controls must evolve to include prompt governance, explanation frameworks, and AI-specific testing, and corporate governance teams should act as partners, not gatekeepers.
The Emergence of Agentic AI
The next leap in AI capability comes from agentic AI – systems that can plan tasks, execute multi-step workflows, interact with IT systems, and use tools semi-autonomously. For financial reporting teams, this could mean real-time answers to “what if?” questions, dashboards that update themselves when the market moves, automated change testing and reconciliation workflows, and reduced delays from specialist technical teams. However, these gains bring governance challenges and the need for transparency to build trust.
AI is moving from being a passive assistant to an active co-worker. It has the potential to add significant value by complementing humans. For insurers, the question is no longer if this technology will transform reporting, but how quickly they can adapt. The future of AI in financial reporting is not mere speculation but a reality that’s unfolding.
Mark Brown, Global Proposition Lead, Life Financial Modelling Insurance Consulting and Technology, WTW
