Continuous underwriting, predictive risk selection, and the end of the annual renewal as we know it

For decades, commercial insurance operated on a simple rhythm: once a year, a broker gathers information, completes proposal forms, and presents a risk to the market. For the next twelve months, nobody looks at it again. That model is dying.

In 2026, AI-enabled tools are unlocking the ability to monitor risk factors in real time throughout the policy term, enabling what the industry now calls ‘continuous underwriting.’ The shift is comparable to the move from annual health checkups to continuous health monitoring through wearable devices.

What AI Is Actually Doing in Insurance Today

AI copilots are processing submissions and recommending actions. Natural language processing is extracting risk-relevant information from unstructured documents. Predictive models are identifying risk correlations that conventional actuarial analysis does not capture. In fleet insurance, telematics data combined with AI can flag drivers developing dangerous behavioural patterns before they cause losses.

Sixty-five percent of South African insurers are now investing in AI for claims automation.

The Governance Question

If your insurer is using AI to price your risk, you deserve to understand what factors are influencing that pricing. If an AI system flags your claim for additional scrutiny, you deserve transparency about why. The broker’s role in this new environment is elevated, becoming an essential interpreter between algorithmic underwriting and client interests.

What This Means for Commercial Buyers

Businesses that invest in high-quality risk data will increasingly be rewarded with more accurate and potentially lower pricing. The annual renewal will not disappear overnight, but it is being supplemented by mid-term adjustments and dynamic pricing triggers.

At Vitari, we view the AI transformation as an amplification of the broker relationship’s value. Our role is to ensure that our clients’ data tells the best possible story and that algorithmic assessments are fair and transparent.

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