Manual underwriting and billing created operational bottlenecks. AI now automates submissions and policy checks, freeing brokers for advisory work.
An insurance brokerage with $1.9 billion in quarterly revenue, which spent over a decade standardizing its data and platforms to prepare for large-scale AI deployment.
Manual, repetitive workflows across underwriting, policy review, and billing created operational bottlenecks that limited throughput and slowed...
“We don’t view AI as a teammate replacement tool.”
Insurance brokerage and risk management services provider.
Brown & Brown's Insurance workflow automation is part of this use case:
Related implementations across industries and use cases
Adjusters spent up to two hours manually reviewing hundreds of claims notes. Now, secure AI summarizes complex case files in minutes.
Fragmented systems buried adjusters in routine admin. Now, a 24/7 AI captures data and routes cases, freeing humans for complex claims.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.
Manual data entry bottlenecked operations. Now, custom agents extract incoming contract details and route them for human verification.
Manual price benchmarking consumed hours per case. AI agents now analyze costs and draft negotiation emails in seconds.
Agents spent up to 6 minutes writing inconsistent notes. Now, AI instantly summarizes 55,000 weekly calls directly into the CRM.
Bond selection took days of manual review. Custom AI agents now surface risks, empowering analysts to execute trades in hours.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.
Reviewing handwritten, unstructured documents took handlers up to an hour per claim. Now, AI extracts and validates data automatically.
Manual underwriting and billing created operational bottlenecks. AI now automates submissions and policy checks, freeing brokers for advisory work.
An insurance brokerage with $1.9 billion in quarterly revenue, which spent over a decade standardizing its data and platforms to prepare for large-scale AI deployment.
Manual, repetitive workflows across underwriting, policy review, and billing created operational bottlenecks that limited throughput and slowed...
“We don’t view AI as a teammate replacement tool.”
Insurance brokerage and risk management services provider.
Brown & Brown's Insurance workflow automation is part of this use case:
Related implementations across industries and use cases
Adjusters spent up to two hours manually reviewing hundreds of claims notes. Now, secure AI summarizes complex case files in minutes.
Fragmented systems buried adjusters in routine admin. Now, a 24/7 AI captures data and routes cases, freeing humans for complex claims.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.
Manual data entry bottlenecked operations. Now, custom agents extract incoming contract details and route them for human verification.
Manual price benchmarking consumed hours per case. AI agents now analyze costs and draft negotiation emails in seconds.
Agents spent up to 6 minutes writing inconsistent notes. Now, AI instantly summarizes 55,000 weekly calls directly into the CRM.
Bond selection took days of manual review. Custom AI agents now surface risks, empowering analysts to execute trades in hours.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.
Reviewing handwritten, unstructured documents took handlers up to an hour per claim. Now, AI extracts and validates data automatically.