If 2024 marked the year of AI experimentation, 2025 will be the year it transforms insurance. Pioneers like Aviva and CNA Insurance have already harnessed AI to reimagine workflows, but generative AI’s rise has ignited an industry-wide revolution. Insurers now recognize AI’s potential to automate complex tasks, enrich decisions, and scale operations—but success hinges on strategic integration.
Some insurers saw AI’s potential for process improvements: streamlining the customer experience, improving risk and policy setting, and offloading back-office repetitive tasks, and they started to create prototypes and embed it into processes.
At Appian, we believe AI’s true power lies in its synergy with process automation. Our AI Agents—intelligent systems that blend knowledge, actions, and human collaboration—are driving this shift. Here are six pivotal trends shaping insurance in 2025, powered by AI Agents and Appian’s process-first philosophy.
1. AI Agents Will Elevate Customer Experience Through Hyper-Automation
Customers demand speed and precision. Many insurers still have long, labor-intensive processes where employees have to analyze documents or emails manually.
AI Agents deliver both by automating document-heavy processes like claims intake and underwriting.
Underwriting: AI can easily be trained to extract information from unstructured documents. Underwriters can then review the extracted and summarized data in one central location and rapidly create quotes for medical policies, life insurance, etc. This will cut out much of the wait time for customers and accelerate underwriting time-to-value.
- Claims processing: AI Agents instantly classify emails, extract data from accident reports, and validate policy details, slashing resolution times.
- Policy document generation: By adopting AI classification and extraction, insurance companies will automate the process of creating personalized, lengthy, and complex customer policy documents.
Customer support responses: Insurance organizations face a deluge of incoming customer support communications. AI will be used to automatically categorize emails into categories, extract key information, classify any documents, and extract their data. AI-powered chatbots resolve routine inquiries autonomously, while escalating complex cases to human agents—all orchestrated through Appian.
2. Revenue Growth Through Intelligent Document Processing
Handwritten broker quotes and unstructured submissions delay revenue cycles. Appian’s AI Agents use Data Fabric—a semantic layer unifying enterprise data—to classify and extract critical information in seconds. This enables:
Faster quote-to-policy conversion.
Scalability to handle 10x more submissions without added headcount.
Competitive differentiation through rapid response times.
3. Employee Satisfaction Soars as AI Tackles Tedious Tasks
Repetitive work drains morale. AI Agents liberate teams by automating manual tasks like email triage and data entry. For instance:
- Policy Management: Agents auto-generate personalized policy documents, reducing errors and freeing staff for advisory roles.
- Case Routing: Appian’s Low-Code Tooling ensures seamless handoffs between AI and humans, eliminating process bottlenecks.
Employees shift from clerks to strategists—a win for retention and innovation.
4. Cross-Process Automation Becomes a Strategic Imperative
Beyond the use cases mentioned above, in 2025, insurers will realize that AI can be applied to generate more efficiencies across the organization. They’ll pursue continuous process improvement and expand their AI usage more broadly across the enterprise, targeting enterprise-wide, critical processes like fraud prevention.
Note: To effectively implement AI, insurers will need a firm foundation of data and process automation:
Think. Understanding your data is critical to any AI effort. Too often, data silos prevent the creation of AI models. Scattered data yields poor results. But you can solve this with a data fabric. Data fabric connects data from across the enterprise in a virtual layer, making data more accessible and preventing a lengthy data migration effort.
Act. AI works best within a proccess. The right AI process automation platform offers a process orchestration layer that enables you to easily route work between humans and digital workers.
- Learn. Process HQ gives you fast answers to your most important process and business questions, allowing you to monitor and optimize processes in real time.
5. Ensure Compliance with AI: Human Oversight and Auditable Workflows
As AI regulations tighten, insurers must ensure transparency and fairness. Safeguards must be in place, with these regulations to consider:
The European Union’s Artificial Intelligence Act:classifies applications into low and high risk and sets strict standards for transparency, data quality, and human oversight.
The US National Association of Insurance Commissioners (NAIC) NAIC Model Bulletin standards for AI ethical and fair practices States have also started issuing their own regulations and guidelines for insurers.
Other countries such as Australia have already been releasing frameworks around the responsible use of both AI and digital technologies.
Most of these regulations are driven by weaknesses in AI models.
Fairness model. Because AI operates quickly and often semi (or fully) independently from humans, we could unknowingly entrench unchecked human bias into AI systems. This might cause systems to raise insurance rates for people living in a specific region of a city that heavily overlaps with a protected class. Regulators will seek to reduce biases like these—and it’s critical to reduce your potential risk exposure.
Runaway AI model. Runaway models can be either overly stringent or loose in their decision-making. We’ve seen this in the United States with stories of rampant health insurance claim denials that have led to lawsuits. To combat this, the EU’s AI Act will require insurers to show proof of how their AI system reached a specific decision.
As the news continues focusing on the negatives of AI, expect regulators to continue releasing new guidelines and laws.
6. Data Privacy Defines Competitive Advantage
Insurers build their businesses on years of data acquisition, actuarial calculations, and customer data. Keeping this data private is critical for both compliance and maintaining a competitive advantage.
Unfortunately, many AI providers fall short on privacy. For instance, large public cloud providers may use customer data for their own analytics or even for training AI algorithms they provide to other insurers. This means your competition benefits from your years of hard work. Instead, look for AI and automation providers with private AI to ensure your data remains within your control.
Insurers must also pay attention to their software vendors’ security postures. Review their trust centers to get a good sense of the practices they employ to keep data safe from malicious actors (or non-malicious data leaks).
It’s also worth checking their compliance certifications beyond just their insurance certifications—passing stringent frameworks and regulations like PCI DSS, FEDRAMP, UK Cyber Essentials, or DISA is an excellent indicator of a company that takes security extremely seriously.
Start Your AI Journey with a Process-First Approach
It’s not too late to start adopting AI. Companies who do will start to reap the benefits of effective AI deployments and see bottom-line results. AI embedded in a process makes AI easier, safer, measurable, scalable, structured, and provides it with the data it needs. AI’s value multiplies when embedded in processes. Appian’s AI Agents and Agent Studio simplify deployment by:
Providing pre-built connectors for documents, emails, and core systems.
Offering no-code testing to validate Agent accuracy.
- Enabling seamless scaling from pilot to enterprise.
2025 belongs to insurers who act now. See how Appian is helping other companies like yours generate new efficiencies from AI in process.
