Insurers' AI ambitions outpace what they can actually deliver
Insurers are rolling out artificial intelligence across their operations, but most are failing to turn early projects into measurable business results, according to consulting firm Baringa.
The problem isn't the technology itself. Legacy systems, fragmented data, and organizational constraints are what's slowing progress, Baringa said in its "Reimagining the insurer in the age of AI" report.
Only a small group of insurers has completed large-scale digital transformation and begun extracting real value from AI. Most others are still in early stages with core system modernization underway, limited AI rollouts, and a widening gap between what they've promised investors and what they've actually achieved.
Where voice AI is working
Voice AI systems developed by PolyAI demonstrate what's possible when the infrastructure is in place. These systems have cut cost per contact by 93% and increased customer satisfaction by 15 points, Baringa found.
The technology lets policyholders file claims, make payments, and update account details through natural conversation rather than navigating phone menus or web forms.
Insurers are also using conversational intelligence tools to review 100% of customer interactions instead of sampling small batches, giving them fuller visibility into customer experience and compliance issues.
Data remains the bottleneck
Accurate, timely data is essential for AI to work across insurance operations. When customer information moves freely between systems, insurers can improve pricing decisions, renewal timing, claims handling, complaint routing, and workflow management.
The most advanced applications would let AI handle claims end-to-end: identifying liability signals at first notice of loss, triggering the right workflow, flagging potential fraud, and updating the customer. Human staff would retain control over judgment calls, oversight, and exceptions.
For insurers looking to build AI capabilities, resources on AI for Insurance and AI Agents & Automation can help teams understand how to structure these implementations.
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