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The insurance industry is undergoing a monumental, AI-powered transformation.
As customer expectations continue to rise and call volumes increase, AI has become a boon for insurers looking to lower contact center costs while providing a more modern experience for policyholders.
A key reason why is that GenAI has made it possible for automation to resolve calls just as effectively as your best agents do. In other words, automation solutions like IVRs, which have traditionally been measured by deflection or routing success, are rapidly becoming a thing of the past.
Instead, AI is giving callers a better way to self-serve and enabling CX leaders to drive contact center efficiency like never before.
Gartner predicts that AI will result in over $80 billion in contact center savings by 2026 and auto, home and life insurance companies are already experiencing the benefits.
Insurance call types where AI has the greatest impact
Calls that are repetitive, high in volume, and represent where agents spend the most time are prime candidates for AI.
Based on data from millions of calls, the five flows that most commonly fit this criteria in insurance are:
1. Claim Status: From first notice of loss (FNOL) to claim completion, the claims process can involve many steps with first and third-party callers, and include a long list of repetitive intake questions and follow-ups that can take hours of an agent’s time each day.
2. Payments: Members calling in to make a payment, confirm receipt of a payment, or update their payment method can represent up to 30% of contact center call volumes; they often involve manual data entry and information capture tasks that agents don’t need to be doing.
3. Update Policy: Policy-related calls can range from adding an asset or beneficiary, renewing a membership, confirming benefits or cancelations. In aggregate, each policy update call is highly repetitive and takes time away from agents that could be spent converting new customers.
4. FAQs: When policyholders call to ask a question, they likely don’t have access to other self-service channels or simply prefer the phone. FAQs like requesting policy documents, confirming coverage, or checking in-network services can all be resolved accurately using AI that integrates seamlessly with your unique knowledge base.
5. Emergency Roadside Service: Requests like Emergency Roadside Service are time-consuming, complex and manual for auto insurers, with a combination of inbound and outbound calls needed to resolve each case. AI has the intelligence and integrations needed to fully automate this process while increasing member satisfaction.
A high resolution rate in even a single one of these call types can have a massive impact on efficiency. Compared to past automation solutions, AI has been shown to decrease average handle time, increases CSAT, reduce agent call volumes, and increase net savings when leveraged for high volume requests.
How AI transforms insurance contact centers
Joe Russo, Assistant Vice President, AAA – The Auto Club Group (ACG), is one industry veteran who has not just taken note of AI, but has joined the innovators setting a new standard for efficiency in insurance customer service.
“I think that three to five years from now we will probably see significantly smoother process flows across business verticals as leaders engage in various levels of automation,” he predicts.
The impact of more efficient flows is already be felt across the industry’s biggest challenge areas:
🚀 A vastly improved policyholder experience:
Policyholders rely on insurers to be there in their greatest times of need, which means customer experience is more crucial in the insurance industry than any other.
“People never start their day with the intention of calling AAA to see how things are going,” Russo says. “Our first touch point with them is typically when they’ve walked out of the house and had a flat tire or a dead battery or, in the worst case, they were driving down the freeway and something went wrong.”
In the case of AAA, AI helped them increase their member satisfaction score by 900 basis points as a result of lower wait times, faster self-service, strikingly natural AI conversations and more available agents for complex requests.
🧑💻 An reimagined agent experience:
A shrinking talent pool and rising labor costs have made the traditional agent model unsustainable. One of the major reasons for adopting AI in customer service is the augmentation it allows CX leaders to bring to the agent experience.
“Our primary motivation has been taking some of the really high value deliverables that are more mundane and consume time and effort but don’t necessarily leverage the skill and expertise of our staff,” Russo says. “Tying those things together makes for a better experience for the employee and I think that’s led to some of the successes we’ve seen in that space.”
💵 Up to 50% lower operational costs:
When agents benefit from automation just as much as customers do, the contact center equation changes. Agent retention goes up, roles become true career paths, and hiring, training and operating costs are significantly reduced.
With AI automating thousands of calls every month, AAA-ACG offloads a call volume equivalent to 25 full time employees at a significantly lower cost. For many contact centers the net savings they see within a year of deploying AI approaches 50% when compared to outsourcing or hiring.
🌤️ Mitigated seasonality-driven challenges:
Whether it’s open enrollment, weather events that increase claim submissions, or week-to-week surges, every insurance contact center experiences seasonality.
With AI acting as a first line of defense, service leaders don’t have to guess how much staff they’ll need to account for future volume increases.
“Where I think this can really improve our ability to serve is in taking some of the ebb and flow away and smoothing out that volume,” Russo says.
AI can scale up or down instantly depending on agent capacity and call volume, giving contact centers the agility needed to be ready for the unpredictable challenges inherent to insurance.
Find your most AI-ready calls
While the above call types represent the most common AI-ready use cases across the insurance industry, your AI roadmap should start with an analysis of your contact center’s unique data.
By identifying high-volume use cases, leaders can clearly communicate the value of AI to stakeholders by tying impact directly to their respective goals. ROI and net hiring savings, for example, are always top of mind for finance and operations, whereas CSAT and SLAs may matter most to CX leaders.
A Call Assessment accomplishes this with a visually impactful custom report that uses a sample of your calls to identify the use cases agents spend the most time on, as well as the short-and long-term cost savings you’d see by resolving them with automation.
