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.
Every AI workflow meant engineering approval gates from scratch—employees held back from delegating. Cowork shipped with them baked in.
Fragmented systems buried adjusters in routine admin. Now, a 24/7 AI captures data and routes cases, freeing humans for complex claims.
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.
Reviewing handwritten, unstructured documents took handlers up to an hour per claim. Now, AI extracts and validates data automatically.
Agents spent up to 6 minutes writing inconsistent notes. Now, AI instantly summarizes 55,000 weekly calls directly into the CRM.
Engineers combed through 1,000-page packages to verify steel traceability codes. AI now extracts and matches them in minutes; they validate.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.
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.
Every AI workflow meant engineering approval gates from scratch—employees held back from delegating. Cowork shipped with them baked in.
Fragmented systems buried adjusters in routine admin. Now, a 24/7 AI captures data and routes cases, freeing humans for complex claims.
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.
Reviewing handwritten, unstructured documents took handlers up to an hour per claim. Now, AI extracts and validates data automatically.
Agents spent up to 6 minutes writing inconsistent notes. Now, AI instantly summarizes 55,000 weekly calls directly into the CRM.
Engineers combed through 1,000-page packages to verify steel traceability codes. AI now extracts and matches them in minutes; they validate.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.