Beyond Productivity: Why It’s Time for Insurance-Native AI

If you’re reading this from your work laptop, there’s an excellent chance you’ve used AI to do work-related tasks faster. The first wave of AI unleashed a flood of individual productivity, with Stanford researchers finding genAI users performed 76% to 176% more efficiently when working on productive digital tasks. Whether it’s writing emails faster, analyzing financial reports more efficiently, or coding an internal app from a prompt, foundational AI models have unlocked all kinds of productivity in a few short years. 

But now that everyone has access to AI models, the competitive landscape has changed. Yes, this horizontal AI has sped up writing, research, coding, summarization, and knowledge retrieval, but these capabilities have become the new baseline. There’s little competitive advantage left to be gained from boosting productivity among individual employees. Instead, the next phase of AI advantage will be vertical industry intelligence that makes organizations smarter, not just employees faster. 

In this blog, we will explore this concept of vertical AI inside the insurance industry. Beginning with why the complexity of highly regulated industries demands organizational intelligence, we will unpack why insurance is becoming AI’s next big proving ground. By embedding vertical AI into their operational workflows, insurers can combine domain expertise, governed workflows, and connected decision making to make their entire organization smarter and lead their industry.  

Why Targeted Productivity from AI Is Not Enough for Insurers 

Insurance does not suffer from a lack of intelligence. Today, AI models assist individual insurance employees in all kinds of useful ways:

• Underwriters rely on AI models to rapidly analyze data related to customer assets, geographic and regulatory details, climate patterns, and more to generate quotes faster and with less risk. 

• Adjusters depend on AI to automatically identify and flag anomalies in claims, making it easier to find suspicious activity worthy of investigation. 

• Customer-facing agents use AI chatbots to swiftly understand each customer’s unique situation, then use generative AI to search internal documents and write targeted, relevant communications that address customer problems with care.  

However, because these AI applications are commonplace, none of them are difference makers in today’s insurance landscape. At the same time, many of these AI applications are too siloed for insurers to scale them up to operational intelligence. As discussed in our earlier blog about AIOS for insurance, there are many homegrown and 3rd-party AI tools that haven't integrated across departments. If an AI application that manages claims data fails to integrate with the automated system facilitating customer service interactions, that will lead to inaccurate information and frustrated customers — no matter how efficiently each AI is working.  

How Industry Intelligence Is Delivering Transformative Change 

Instead of AI focused only on optimizing individual employees, insurers need insurance-native AI that actually delivers operational intelligence. This treats the efficiency improvements of horizontal AI as a starting point, adding cross-department analysis and connective insight for a more holistic view of insurance operations. In short, it takes horizontal AI and scales it to become vertical AI designed for insurance specifically. 

The foundation of this vertical AI is industry intelligence, where AI platforms are built by experts who understand the unique business context of their customers’ industry. This enables AI designed with end-to-end domain expertise, helping it deliver better governance, explainability, and regulatory awareness in its decision making. In addition, industry intelligence makes it easier to design AI systems that effectively integrate data across departments, avoiding frustrating silos and miscommunications. By operationalizing industry knowledge with vertical AI, organizations can escape the diminishing returns of chasing efficiency and find new competitive advantage. 

Why Insurance Demands Industry Intelligence over Horizontal AI 

The insurance industry’s unique complexities and possibilities position it to especially benefit from industry intelligence. Like healthcare, insurance is a highly regulated industry with many rules and laws to consider. However, insurance goes beyond healthcare’s regulatory challenges by also facing a wide variety of distinct rules and laws that vary across states and municipalities. This makes explainability, auditability, and governance essential.  

If an insurer relies on siloed AI tools that don’t grasp this regulatory complexity, it can lead to cascading problems. Imagine a disputed claim where a customer demands transparency into an AI-enabled decision. When the customer service employee asks the AI to explain how it evaluated the claim, the AI not only cannot explain adequately but also reveals it didn’t properly document its process. Then it comes out that the AI did not comply with a data privacy regulation specific to the customer’s home state. Now the insurer is exposed to significant legal action and financial penalties simply because its AI tool wasn’t built with insurance operations in mind. 

The inherent complexity of insurance means that a vertical AI platform designed with insurance domain expertise would deliver exceptional value. This insurance-native AI would connect analysis and decisions across pricing, underwriting, claims, and customer engagement while ensuring strong governance and auditing from end to end. Not only would this protect insurers from the nightmare scenario described earlier, but also would enable each department to share insights automatically as their AI tools learn from every employee and from each other. 

How Earnix Delivers Insurance-Native AI through AIOS 

To bring this vision for insurance-native AI to life, Earnix begins with its 25-year history of enabling intelligent operations for the insurance industry across the world. Our solutions have helped global insurance leaders like AXA, Assicurazioni Generali, Mapfre, and Matmut simplify their pricing, underwriting, claims management, and customer engagement. Most importantly, we implemented all these solutions as part of a connected ecosystem that empowered each client with intelligent insurance operations. 

This holistic approach is integral to how Earnix delivers industry intelligence for insurance. Our AI Orchestration System (AIOS) extends Earnix’s intelligent decisioning capabilities across the insurance lifecycle, helping insurers apply AI to the decisions that have the greatest impact on business performance. It brings greater speed, governance, and consistency to high-stakes decisions across risk evaluation, underwriting, claims, and customer engagement, while providing the explainability and visibility insurers need to maintain regulatory control. 

The Competitive Advantage of Insurance-Native AI  

Now that employees across your organization have learned how to boost their individual productivity with AI tools, it’s time to explore what’s next. By adopting insurance-native AI built by experts with deep understanding of the complexities of your industry, you can make your operations smarter through governed workflows and connected decisioning. Best of all, both your human experts and AI agents can constantly learn from shared insights to find new and better ways to lead your industry.  

To further explore how vertical AI can empower insurance operations, visit earnix.com.