Unlocking AI’s efficiency with regulatory confidence – Unitary

Insurance is burdened with manual, repetitive tasks. Companies across the insurance distribution chain face relentless pressure to protect and grow margins, making automation essential to reduce manual work, lower operational costs, and free staff for higher-value activities.

Over the years, various tools have emerged to address these challenges. Robotic process automation (RPA) streamlines repetitive, rule-based tasks, intelligent document processing (IDP) extracts data from unstructured documents and artificial intellifence (AI) underwriting platforms deliver powerful risk analytics.

While valuable when implemented well, these tools typically operate in isolation, forcing insurers to manually integrate and manage them. This patchwork approach introduces complexity, limits scalability and often dilutes the potential efficiency gains.

The rise of AI agents presents a chance to transform this landscape.

AI agents are advanced systems capable of reasoning, making decisions and acting independently. Powered by large language models (LLMs), they interpret input, predict logical next steps and interact seamlessly with other tools.

This positions AI agents as a potential all-in-one solution, eliminating the need to juggle multiple disconnected technologies and unlocking genuine, scalable efficiency improvements.

Reliability and risk concerns

That said, AI still carries real risks. While undeniably powerful, it remains fallible. High-profile headlines have highlighted instances of AI systems behaving unpredictably and causing costly, brand-damaging failures.

Earlier this year, an AI coding assistant from Replit ignored instructions and made unauthorised changes to live infrastructure, deleting a company’s entire database.

This risk stems from AI’s probabilistic nature. Unlike traditional software, which follows deterministic rules and produces predictable outcomes, AI generates responses based on likelihoods inferred from patterns.

This enables sophisticated reasoning, but it also introduces inherent unpredictability. As a result, advances in capability do not always translate into improvements in reliability. For insurance, where accuracy, compliance and accountability are vital, this unpredictability is unacceptable.

Harnessing AI responsibly

My team has developed a robust system that enables insurers to safely unlock AI’s value today. We partner with MGAs, brokers and insurers to deploy this at scale. The key lies in combining AI, software and human oversight.

Traditional software is deterministic – it follows pre-defined rules to deliver consistent, reliable results. This software acts as guardrails for AI, allowing it to reason through complex decisions while ensuring outcomes remain dependable every time.

Crucially, the software must be purpose-built and robust so that AI cannot produce unreliable end results.

To maintain governance and build trust, insurers must add a third essential layer – embedded human oversight and clear escalation paths. This multi-layered approach empowers teams to boost operational efficiency while effectively managing risk and meeting regulatory requirements with every decision.

Preparing for future

We’re in a time of profound transformation. I truly believe companies that lay the proper AI foundations now will quickly pull ahead of those stuck piecing together fragmented tools. This is a pivotal moment to build your company’s future success.

By automating repetitive manual tasks, companies can redeploy their talent toward strengthening customer relationships, improving underwriting quality and accelerating strategic growth.

The automation revolution of 2026 and beyond won’t wait. It will favor those who take decisive action today – building intelligent, accountable systems that deliver real, measurable impact and secure long-term competitive advantage.