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In March 2024, we attended InsurTech, a conference gathering insurance executives, established insurers, investors, and companies with insurtech offerings – like us.
This allowed us to learn more about the challenges the insurance industry faces in regards to adopting Generative AI. Here’s a recap of what we learned and how it helps us improve our services within the industry.
Key Takeaways
- Most insurance companies are still discovering the true potential of AI and are in the testing phase.
- The insurance sector doesn’t want AI automation that replaces its existing workflow.
- Companies are highly focused on ROI.
- Fully automated AI workflows are risky for the insurance industry.
What is InsurTech?
InsurTech is a conference that brings traditional insurers, insurtech companies, investors, and other solution providers that could help drive the insurance industry forward. The conference is usually split into two sections:
- property and casualty insurance, and
- life and health insurance.
InsurTech brings together influencers and changemakers in the industry in order to present innovations that can help insurers save costs and improve efficiency. It focuses on simplifying and expediting processes in commercial insurance through automated systems and interfaces.
We attended because we provide solutions that automate and enhance insurance claims management and underwriting.
What We Discussed at InsurTech
We discussed interesting topics with insurance leaders involving artificial intelligence, machine learning, data collection and analytics, and other emerging technologies that can help transform the industry.
The insurance industry is undergoing its most substantial transformation in decades. We discussed specifics of how Generative AI can help insurance industries automate workflows even when they’re highly specific and require human-level intelligence.
We also discussed how the insurance sector requires flexible systems that can adjust to unique cases on the fly and learn to evolve with new big data. Besides positively impacting business expenses, such systems would significantly improve customer experience.
We met with many professionals one-on-one, and even interviewed some of them on our Pioneers podcast.
What We Learned at InsurTech
Here are our main takeaways from InsurTech.
1. Exploration Is Still in Early Stages
Insurance providers, managing general agents, and third-party administrators are interested in exploring new technologies such as AI, automated systems, and data analysis. However, the exploration is still in the beginning stages.
Therefore, many attendees were yet to learn about the possibilities of the available technologies. Some companies are experimenting with pilot programs with their team or outside companies. Only some have finished the tests and use the solutions in everyday business operations.
2. Laborious Integration Hinders Adoption
One of the biggest challenges insurance companies face is the integration of insurtech solutions with their current workflow and employees. Instead of finding a solution that requires changing current workflows, insurers want solutions that can seamlessly integrate into their existing systems.
3. Focus Is on ROI
Calculating the AI ROI is challenging because of many variables; it depends on initial cost, complexity of the implementation, and many other factors. Still, having a clear overview of the AI investment’s gain and the cost can ensure that the benefits outweigh the implementation costs, and is often necessary for getting stakeholders and other business leaders on board.
4. Automated Decision Making Is Risky
We also learned that most insurance companies don’t want AI solutions to handle their entire workflow and make decisions for them. They consider it to be too risky, as it could potentially lead to legal and compliance issues.
5. Other Takeaways
- Insurers want data and software on their infrastructure rather than in the cloud.
- Most don’t have big data teams that can work on software implementation.
- The primary driving factor is reducing costs and improving revenue by providing enhanced experiences with the help of AI.
How We Help Insurance Companies Overcome Almost All Identified Challenges
InsurTech helped us learn more about the challenges that insurers face. We already have and will continue to use these insights to further improve our AI Agents for the insurance and insurtech industry.
Our specialized AI Agents help automate various insurance operations, such as:
- Routine tasks, like sorting policy details
- Risk analysis
- Decision-making processes
- Risk data processing and analysis
- Policy management
Attending InsurTech also made us realize that our current process can already help insurers overcome many obstacles and minimize fears around AI implementation. To be more specific, here’s what we do differently from many AI vendors?
- We create PoCs for a fraction of the full price.
- We tailor AI Agents to existing workflows.
- We calculate the potential ROI during our discovery process.
- We allow companies to decide exactly what to automate and how.
- We deploy solutions on client’s private VPCs.
Here’s how these steps solve many problems that insurance and insurtech companies face when adopting AI.
1. Proof of Concept (PoC)
One of the biggest issues we’ve encountered is that the exploration of AI solutions is still in the early stages. Most companies still struggle with understanding which AI technologies are relevant to their business and how to implement them effectively.
As a result, many are resistant to change or skeptical about the potential benefits of AI. This can hinder innovation and growth, potentially leading companies to fall behind competitors who are further along on their AI journeys.
We counteract this by providing Proof of Concept (PoC) before we go into full development. This gives companies a clearer picture of what to expect and minimizes any skepticism around AI or the benefits it can deliver.
It also gives companies a chance to discuss and request changes early on in the project.
2. Company-Specific AI Agent Customization
The second biggest challenge is that integrating AI solutions is usually difficult because it requires employees to change the way they work. We eliminate this issue by tailoring our solutions according to existing company workflows.
We train our AI Agents (Document AI, Decision AI, Database AI, Conversational AI, and Content AI) on existing workflows and company-specific data – which could be compared to onboarding new employees for our clients.
We adjust AI solutions to end users and existing processes instead of expecting users to adjust to them.
This decreases friction, allows for faster adoption, and minimizes resistance to change.
3. AI ROI Calculation
Besides PoC, we also provide AI ROI estimates that help companies understand what to expect before and after deployment. Our team calculates the potential ROI during discovery by considering various variables, such as the chosen AI solution, target tasks, and more.
4. Automation Selection
We leave it up to the companies to decide whether they want end-to-end workflow automation or just partial automation of specific tasks. One size doesn’t fit all.
We do, however, help clients choose the best use case for their business during our initial engagement process.
5. Secure Solution Deployment
Security is another important challenge. We help overcome it by deploying solutions on the client’s virtual private network, which minimizes any risks of data breaches.
Additionally, we make sure our solutions are as accurate and safe as possible by training them on company-specific data, as well as relevant and up-to-date regulations – such as GDPR and different national regulations.
Learn How Our Insights and Experience Can Enhance Your Business
If you’re looking for a quality AI to implement in your workflow or an AI partner you can trust - please schedule a 30-minute call with our experts. We can discuss your needs and the best ways to integrate AI into your workflow, as well as demonstrate how our AI Agents work live.
