Specialty insurers face rising pressure. Submission volumes are increasing by 8% to 12% each year. Brokers expect faster responses. Costs remain tight. Legacy processes struggle with the growing complexity of risks and documentation.
Many insurers are turning to agentic AI. These are small, specialized agents that prepare, validate and monitor work under strict governance. Agentic AI does not replace expertise. It removes noise so judgment can be applied faster and more consistently.
The question for leaders is direct: how do we increase capacity and maintain control at the same time?
These 5 uses show where agentic AI is already delivering measurable impact.
1. Submission Intake That Builds a Decision-Ready Risk View
Document variability and missing information slow down intake. Agentic AI structures and enriches submission packs within minutes.
Results observed:
- 50% to 70% faster first-pass analysis
- 30% to 40% more submissions receiving a meaningful quote
- Missing data surfaced in over 60% of cases
Why it matters: faster triage improves broker responsiveness and hit ratios without adding headcount.
2. Underwriting Preparation That Reduces Cognitive Load
Underwriters spend significant time locating information and validating details. Agentic AI handles these tasks consistently.
Results observed:
- 40% to 65% fewer manual cross-checks
- Up to 25% fewer technical errors
- 20% to 30% less time spent searching through documents
Why it matters: teams gain more time for judgment, broker interaction and risk assessment.
3. Claims Evidence Builders That Improve Cycle Time and Control
Claims files often include inconsistent, unstructured documentation. Agentic AI classifies documents, extracts facts and assembles a clean evidence file.
Results observed:
- 30% to 50% faster evidence assembly
- 10% to 20% reduction in leakage
- 1 to 3 days removed from cycle times
More than 70% of files in one deployment contained inconsistencies detected instantly by agents.
Why it matters: cleaner evidence strengthens reserves and reduces operational exposure.
4. Modernization Accelerators That Reduce Project Risk
Modernization projects stall when discovery and validation take too long. Agentic AI analyzes legacy data and validates samples at scale.
Results observed:
- Weeks of analysis reduced to days
- 60% to 80% of legacy patterns identified automatically
- 20% to 30% fewer reconciliation issues at cutover
Why it matters: transformation becomes faster, more predictable and less resource-heavy.
5. Continuous Compliance Monitoring That Strengthens Governance
Governance checks are often manual and performed after the fact. Agentic AI provides continuous monitoring across submission, policy and claims workflows.
Results observed:
- 100% of submissions checked automatically against appetite
- 20% to 40% reduction in post-bind corrections
- Real-time detection of exposure breaches
In one deployment, missing documentation was identified in over 35% of bound files before audit.
Why it matters: real-time oversight supports safe scaling of automation without weakening control.
What This Means for Insurers
Agentic AI improves accuracy, cycle time and governance across underwriting, claims and modernization. It supports expert judgment and strengthens decision quality. Insurers that adopt these capabilities early gain clear advantages in speed, control and operational resilience.
A key question remains: beyond today’s practical use cases, how can insurers use agentic AI to create new business models, and how do they govern these agents to avoid the known risks such as AI systems feeding each other, creating errors or amplifying false signals?
This is where strategy, guardrails and operating model design matter as much as technology.
To explore these strategic questions and see how agentic AI fits into a full operating model, refer to our latest whitepaper.
→ Download the whitepaper: From buzz to booked business: Agentic AI in Specialty Insurance
→ Talk to our experts about implementing these capabilities safely and at scale.
Sources
McKinsey & Company – Global Insurance Reports
McKinsey – The Future of Underwriting
McKinsey – Generative AI in Insurance
Celent – Insurance Technology and Modernization Research
Celent – Emerging Technologies in Insurance
Datos Insights – Commercial and Specialty Market Research
Everest Group – Insurance and Intelligent Automation
ACORD – Specialty Lines Modernization Trends
EY – Global Insurance Outlook
