AIG Leverages AI for Underwriting Edge
AIG is harnessing generative AI to boost underwriting and claims efficiency. The company reports a significant increase in processing capacity without extra human resources.
American International Group (AIG) is making waves with its use of generative AI, showing impressive gains in underwriting and claims processing. At a recent Investor Day, the company highlighted substantial improvements in throughput and workflow redesign. CEO Peter Zaffino's comments suggest the initial projections were just the beginning.
AI-Powered Efficiency
In 2025, AIG claims it embedded generative AI across its core processes, notably in underwriting and claims. Their internal tool, AIG Assist, is now a staple in most commercial lines. The numbers tell a different story than mere aspirations. Zaffino stated the company surpassed expectations, handling submission flows without increasing human resources.
The implication is clear: AI isn't just a buzzword. It's transforming how AIG operates. Wouldn't you want an AI that processes 370,000 submissions, as seen with AIG’s Lexington Insurance? That's their reality in 2025, a hefty step toward their 2030 target of 500,000 submissions.
The Orchestration Layer
AIG's orchestration layer acts as the conductor of this AI symphony. Coordinating AI agents, the company aims to enhance decision-making and cut costs. It’s a strategy that compresses what's described as a 'front-to-back workflow.' This tighter integration spans intake, risk assessment, and claims handling.
Zaffino goes further, describing AI agents as teammates offering real-time insights and challenging decisions. The architecture matters more than the parameter count here. AIG’s approach ensures agents manage data swiftly and unbiasedly, a major shift for workflow efficiency.
Strategic Applications
AIG's AI stack isn’t just theoretical. When converting Everest’s retail commercial business, AI reduced renewal prioritization time significantly. They built an ontology of Everest's portfolio, blending it with their own. This ontological alignment, though complex, is paying off.
The launch of Lloyd’s Syndicate 2479 shows AIG’s commitment to AI. Partnering with Amwins and Blackstone, they applied LLMs to align risk appetites efficiently. For AI decision-makers, AIG’s case illustrates the practical benefits of embedding generative models in core processes.
So, what's next for AIG? The company hints at a strong pipeline of SPV opportunities. As they continue to refine their AI strategies, one can't help but wonder: Are we seeing the future of insurance unfold?
Key Terms Explained
A dense numerical representation of data (words, images, etc.
AI systems that create new content — text, images, audio, video, or code — rather than just analyzing or classifying existing data.
A value the model learns during training — specifically, the weights and biases in neural network layers.