AI Opportunity Assessment

AI Agent Operational Lift for Viant in Naperville, Illinois

AI agents can automate repetitive tasks, enhance customer service, and streamline claims processing for insurance providers like Viant. This assessment outlines potential operational improvements for companies in the insurance sector.

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20-30%

Reduction in claims processing time

Industry Claims Automation Studies

15-25%

Improvement in customer service response times

Insurance Customer Experience Benchmarks

5-10%

Decrease in operational costs

Insurance Operational Efficiency Reports

2-4 wk

Faster policy underwriting cycles

Insurance Technology Adoption Trends

Why now

Why insurance operators in Naperville are moving on AI

In Naperville, Illinois, insurance carriers are facing a critical juncture where the rapid advancement of AI necessitates immediate strategic adaptation to maintain competitive advantage and operational efficiency.

The AI Imperative for Naperville Insurance Carriers

Insurance carriers in the greater Chicago metropolitan area are experiencing intensified pressure from evolving customer expectations and the accelerating adoption of AI by competitors nationwide. Studies indicate that customer service response times are a key differentiator, with many clients now expecting near-instantaneous digital interactions, a benchmark that manual processes struggle to meet. Furthermore, the ability to rapidly analyze vast datasets for underwriting and claims processing is becoming a standard requirement, not a luxury. Industry reports from sources like Novarica show that insurers investing in AI are seeing significant improvements in claims processing cycle times, often reducing them by 15-20% within the first two years of deployment. For a business of Viant’s approximate size, this translates to a substantial opportunity to reallocate resources from transactional tasks to more strategic, value-added functions.

Navigating Staffing and Labor Costs in Illinois Insurance

Businesses in the Illinois insurance sector, particularly those with around 180 employees, are grappling with persistent labor cost inflation and a competitive talent market. The cost of hiring, training, and retaining skilled insurance professionals, from adjusters to customer service representatives, continues to rise. Benchmarks from the U.S. Bureau of Labor Statistics show average wage growth in professional and business services exceeding 4% annually. AI agents offer a powerful solution by automating routine tasks such as data entry, initial claims triage, and policyholder inquiries, which can significantly reduce the need for manual intervention. This operational lift allows existing staff to focus on complex cases and relationship management, thereby improving overall team productivity and potentially mitigating the need for rapid headcount expansion to meet demand. Peers in the broader financial services sector, including wealth management firms, have reported that AI-powered virtual assistants can handle up to 30% of common customer queries, freeing up human agents for higher-value interactions.

Market Consolidation and Competitive Pressures for Regional Insurers

The insurance landscape, much like adjacent verticals such as healthcare administration and third-party claims administration (TPA) services, is characterized by ongoing market consolidation activity. Larger national carriers and well-capitalized insurtech startups are leveraging AI to achieve economies of scale and offer more competitive pricing and services. For regional players in Illinois, failing to adopt advanced automation technologies risks falling behind. Research from industry analysts highlights that companies that proactively integrate AI into their operations are better positioned to withstand pricing pressures and maintain profitability. The ability of AI to enhance underwriting accuracy and fraud detection, for instance, can lead to substantial improvements in loss ratios, a critical metric for insurer health. Operators in this segment are increasingly looking to AI to streamline back-office functions, thereby improving operational efficiency and supporting sustained growth amidst a dynamic competitive environment.

The 24-Month AI Adoption Window for Midwest Insurers

While AI adoption is not new, the current pace of development and deployment across the insurance industry suggests a critical 24-month window for businesses in Naperville and across the Midwest to integrate these capabilities. Companies that delay risk ceding significant ground to more agile competitors. The increasing availability of sophisticated AI agent platforms, capable of handling complex workflows and integrating seamlessly with existing core systems, lowers the barrier to entry. Early adopters are already demonstrating tangible benefits, including enhanced customer satisfaction and more efficient resource allocation. According to a recent survey of insurance executives by Deloitte, over 60% of respondents indicated plans to increase their investment in AI technologies over the next 18 months, signaling a clear industry trend towards widespread AI integration. This creates a compelling case for businesses like Viant to explore AI agent deployments now to secure a competitive edge.

Viant at a glance

What we know about Viant

What they do

Viant encompasses two distinct companies: Viant Medical and Viant Technology. Viant Medical specializes in vertically integrated manufacturing for medical devices and components. They provide end-to-end solutions, from prototyping to full-scale production, ensuring quality and reducing supply chain risks. Their services include agile program management, materials expertise, and automation for device assembly. Viant Medical serves various markets, including orthopedics, surgical technology, cardiac and interventional devices, drug delivery systems, bioprocessing, bioelectronics, and diagnostics. Viant Technology is a leader in people-based advertising technology, offering AI-powered tools for omnichannel programmatic campaigns. Their services include a demand-side platform for campaign planning and execution, a data platform for audience insights, and advanced reporting metrics. Viant Technology supports various channels, including CTV, digital audio, and mobile, and emphasizes innovation and measurement of online and offline results. They have established partnerships with notable companies and integrate with over 70 data providers.

Where they operate

Naperville, Illinois

Size profile

regional multi-site

AI opportunities

6 agent deployments worth exploring for Viant

Automated Claims Triage and Initial Assessment

Insurance claims processing is a high-volume, labor-intensive function. Efficiently categorizing and performing initial assessments of incoming claims is crucial for timely resolution and customer satisfaction. AI agents can rapidly analyze claim details, identify missing information, and route claims to the appropriate adjusters, significantly streamlining the initial stages of the claims lifecycle.

Up to 30% faster initial claim review— Industry analysis of claims processing automation

An AI agent that ingests new claims via various channels, extracts key data points, categorizes claims based on type and complexity, flags potential fraud indicators, and assigns them to the correct processing queue or adjuster.

AI-Powered Underwriting Support

Underwriting involves complex risk assessment based on vast amounts of data. Manual review of applications and associated documents can be time-consuming and prone to human error. AI agents can automate data extraction, identify risk factors, and provide consistent risk scoring, enabling underwriters to focus on more complex cases and make faster, more informed decisions.

10-20% reduction in underwriting cycle time— Insurance industry reports on underwriting automation

An AI agent that reviews insurance applications, gathers data from internal and external sources, assesses risk factors against predefined rules, and provides a preliminary risk assessment score to human underwriters.

Customer Service Chatbot for Policy Inquiries

Insurance customers frequently have questions about their policies, billing, and claims status. Providing immediate, accurate answers to common inquiries can significantly improve customer experience and reduce the burden on human customer service representatives. An AI chatbot can handle a large volume of these routine interactions 24/7.

25-40% of routine customer inquiries handled by AI— Customer service benchmarks for AI-powered support

An AI agent that acts as a virtual assistant, interacting with customers via chat or voice to answer frequently asked questions about policies, provide status updates on claims or payments, and guide users to relevant resources.

Automated Document Processing and Data Extraction

Insurance operations generate and process a massive volume of documents, including applications, policy endorsements, medical records, and legal notices. Manually extracting information from these diverse documents is inefficient and costly. AI agents can automate this process, improving accuracy and speed for data entry and analysis.

50-70% improvement in document processing speed— Studies on intelligent document processing in financial services

An AI agent that reads, understands, and extracts specific data fields from various unstructured and semi-structured documents, such as policy forms, claim reports, and correspondence, populating them into relevant systems.

Fraud Detection and Anomaly Identification

Insurance fraud results in significant financial losses for the industry. Identifying potentially fraudulent claims or policy applications early is critical. AI agents can analyze patterns and anomalies across large datasets that may indicate fraudulent activity, flagging them for further investigation by human experts.

5-15% increase in detected fraudulent claims— Insurance fraud prevention analytics benchmarks

An AI agent that continuously monitors claims and policy data for unusual patterns, inconsistencies, or known fraud typologies, alerting investigators to high-risk cases.

Personalized Policy Recommendation Engine

Matching customers with the most suitable insurance products requires understanding their unique needs and risk profiles. AI can analyze customer data and market offerings to suggest tailored policy options, enhancing cross-selling and up-selling opportunities and improving customer retention.

10-25% uplift in cross-sell/up-sell conversion rates— Insurance sales and marketing AI benchmarks

An AI agent that analyzes customer profiles, past interactions, and available product information to recommend specific insurance policies or coverage add-ons that best fit individual needs.

Frequently asked

Common questions about AI for insurance

What are AI agents and how can they help insurance companies like Viant?

AI agents are specialized software programs that can automate complex, multi-step tasks. In the insurance sector, they can handle tasks such as initial claims intake and data verification, customer service inquiries via chat or email, policy renewal processing, and fraud detection pattern analysis. Insurance carriers typically deploy AI agents to reduce manual processing times and improve accuracy, freeing up human staff for more complex underwriting and customer relationship management.

How do AI agents ensure data privacy and compliance in insurance?

Reputable AI solutions for insurance are built with robust security protocols and adhere to industry regulations like HIPAA and GDPR. They employ data encryption, access controls, and audit trails. Many AI platforms are designed for on-premise or private cloud deployment to maintain maximum data control. Compliance is often managed through configurable workflows and detailed logging that can be reviewed for regulatory purposes.

What is the typical timeline for deploying AI agents in an insurance company?

The deployment timeline for AI agents varies based on the complexity of the use case and the existing IT infrastructure. For common applications like automated customer service or claims data entry, initial deployments can range from 3 to 6 months. More complex integrations, such as AI-powered underwriting assistance or advanced fraud analytics, might take 6 to 12 months or longer. A phased approach is common, starting with a pilot program.

Can insurance companies start with a pilot AI deployment?

Yes, pilot programs are a standard and recommended approach for AI adoption in insurance. A pilot allows an organization to test AI agents on a specific, well-defined use case, such as automating responses to frequently asked questions or processing a specific type of claim. This helps validate the technology's effectiveness, measure its impact, and refine the implementation strategy before a full-scale rollout.

What data and integration capabilities are needed for AI agents in insurance?

AI agents typically require access to structured and unstructured data, including policyholder information, claims history, policy documents, and third-party data sources. Integration with existing core insurance systems (policy administration, claims management, CRM) is crucial. This is often achieved through APIs, database connectors, or secure file transfers. The cleaner and more accessible the data, the more effective the AI deployment will be.

How are AI agents trained, and what training do insurance staff need?

AI agents are trained on large datasets relevant to their specific tasks, such as historical claims data or customer interaction logs. The training process is iterative and often managed by the AI vendor. For insurance staff, training typically focuses on how to interact with the AI agents, how to interpret their outputs, and when to escalate complex cases. It shifts their roles towards higher-value activities requiring human judgment.

How do insurance companies measure the ROI of AI agent deployments?

Return on investment (ROI) for AI agents in insurance is typically measured through improvements in key performance indicators. Common metrics include reductions in claims processing time (e.g., from days to hours), decreased operational costs associated with manual tasks, improved customer satisfaction scores (CSAT), reduced error rates in data entry, and faster policy issuance times. Benchmarks often show significant cost savings in processing efficiency.

Can AI agents support insurance operations across multiple locations?

Absolutely. AI agents are inherently scalable and can be deployed to support operations across numerous branches or departments without geographical limitations. They provide consistent service and processing regardless of location. For multi-location insurance businesses, AI can standardize workflows, ensure uniform data handling, and centralize operational efficiency, often leading to significant cost synergies across the enterprise.

How much could Viant save with AI agents?

Meo estimates Viant could capture $2.6M–$12.3M in annual savings across 4 automation candidates based on its scale, tech stack, and industry cohort. Typical payback is approximately 2 months. Source: Meo Advisors' internal benchmark model.

Industry peers