How brokers can reduce administrative work with AI

The insurance industry is facing a fundamental shift in how it engages with customers. While many market participants are still testing artificial intelligence in pilot projects, the way customers search for information is already changing. More and more end customers are using AI platforms instead of traditional search engines to resolve complex coverage questions.

For insurance brokers, this means that relevance in the initial contact will increasingly be determined at the interface with digital systems. Those who do not prepare their processes and offerings in a transparent, machine-readable format risk becoming invisible during this digital phase of information gathering.

The Status Quo: Trapped in Administrative Tasks

The real challenge in a broker's daily routine, however, goes deeper. Estimates by Nele Wollert, CSO of muffintech, show that sales staff spend between 60% and 80% of their working time not on consulting, but on documentation, data preparation, and follow-up. Constantly changing legal requirements, growing product portfolios, and documentation obligations exacerbate this administrative burden. These routine tasks tie up valuable resources that are then missing for existing customer care and proactive risk analysis.

In this scenario, artificial intelligence is not a replacement for the human advisor, but a tool to shift the focus back to value creation. Completely replacing humans in regulated sales is unrealistic, both for liability reasons and because of the human need for reassurance. The technology serves as a layer of relief.

Efficiency Gains and Concrete Practical Examples

Where humans and machines work together, significant efficiency gains are already evident. Through the targeted use of artificial intelligence applications in standardized processes, processing times can be reduced by 30% to 60%. Three core areas are shaping modern sales:

• Digital assistance for a 360-degree customer view: By linking various source systems (such as customer databases), the technology consolidates data trails from correspondence, policies, and claims. It filters out relevant information for quick meeting preparation, suggests precise answers, and automatically retrieves the appropriate contract documents.
• Intelligent text dialogue systems to bridge service gaps: Unlike rigid, rule-based systems, modern text dialogue systems use adaptive language models. Trained with company-compliant product information and consulting approaches, they answer complex customer questions flexibly and personally – even outside of regular business hours.
• Automated comparison of insurance terms: Comparing pages of general insurance terms and conditions during policy updates is time-consuming and prone to error. Specialized language models identify differences in content and meaning that go far beyond a simple search function. They immediately recognize whether maximum compensation limits, deductibles, or policyholder obligations have been linguistically modified or if coverage content has been removed.

Furthermore, artificial intelligence acts as a digital advisor during customer interactions. By analyzing successful conversation flows, it provides proven argumentation chains and optimal timing for asking for referrals. This raises the performance of the entire sales team to a consistent, high-quality level.

Proactive portfolio management instead of expensive new customer acquisition

Since reactivating existing customers is on average seven times cheaper than acquiring new ones, artificial intelligence offers an enormous lever for contract optimization here. Using interactive, digitally managed dialogue forms, brokers can automatically determine current customer needs via email. The technology not only asks targeted questions but also answers the customer's follow-up questions directly using existing portfolio data. This interactive format sparks curiosity, achieves high response rates, and uncovers cross-selling potential with minimal effort.

Practical tips: How brokers can successfully implement artificial intelligence

For insurance brokers, it is now crucial not to wait passively for developments, but to actively integrate the technology into their own operations.

• Start with a specific pain point: Do not look for one all-encompassing strategy. Use structured procedural models to systematically test use cases, from business understanding and data preparation to productive deployment. Start with clear pain points such as policy comparisons or automated incoming mail classification.
• Hold service providers and partners accountable: You don't need to develop the technological infrastructure yourself. Leverage your market position. Demand data-compliant tools from your associations, insurers, and software providers that integrate seamlessly into your existing system landscape.
• Treat data protection and system control as the foundation: Handling customer data sensitively is the top priority. Rely exclusively on centrally provided, data-compliant solutions with clear anonymization and encryption. Prevent employees from feeding sensitive customer data into uncontrolled, public tools due to time pressure.
• Proactively maintain data quality: These systems rely on structured, current, and versatile datasets to provide precise recommendations. Use the capacity freed up by automation to clean, structure, and maintain your existing data in the customer database.