-
-
-
-
URL copied!
The insurance sector is facing increased claims, disruption from InsurTech companies, and changing client needs. Customers are coming to expect a superior experience in their dealings with insurance companies. When customers get frustrated by delays, they quickly change their policies.
Which technologies can insurance companies employ to boost customer retention? Learn the difference between Narrow and General AI, the challenges faced by the insurance industry, and how AI-based deep machine learning can provide solutions. In this whitepaper, you’ll also discover use cases for vehicle damage inspection, drone roof assessments, and acquiring new clients using chatbots.
Let’s Work Together
Related Content
Accelerating Digital Transformation with Structured AI Outputs
Enterprises increasingly rely on large language models (LLMs) to derive insights, automate processes, and improve decision-making. However, there are two significant challenges to the use of LLMs: transforming structured and semi-structured data into suitable formats for LLM prompts and converting LLM outputs back into forms that integrate with enterprise systems. OpenAI's recent introduction of structured … Continue reading Use of Artificial Intelligence for Customer Retention & Satisfaction in the Insurance Industry →
Learn More
Connected Vehicle Cybersecurity Considerations That Vehicle Manufacturers Need to Know
According to Deloitte, there will be 470 million connected vehicles on highways worldwide by 2025. These connected vehicles provide opportunities and have a higher cybersecurity risk than any other connected devices; even the FBI had to make a statement about it. A typical new model car runs over 100 million lines of code and has … Continue reading Use of Artificial Intelligence for Customer Retention & Satisfaction in the Insurance Industry →
Learn More
Accelerating Enterprise Value with AI
As many organizations are continuing to navigate the chasm between AI/GenAI pilots and enterprise deployment, Hitachi is already making significant strides. In this article, GlobaLogic discusses the importance of grounding any AI/GenAI initiative in three core principles: 1) thoughtful consideration of enterprise objectives and desired outcomes; 2) the selection and/or development of AI systems that are purpose-built for an organization’s industry, its existing technology, and its data; and 3) an intrinsic commitment to responsible AI. The article will explain how Hitachi is addressing those principles with the Hitachi GenAI Platform-of-Platforms. GlobalLogic has architected this enterprise-grade solution to enable responsible, reliable, and reusable AI that unlocks a high level of operational and technical agility. It's a modular solution that GlobalLogic can use to rapidly build solutions for enterprises across industries as they use AI/GenAI to pursue new revenue streams, greater operational efficiency, and higher workforce productivity.
Learn More
Share this page:
-
-
-
-
URL copied!