Summary

Denise Garth, Chief Strategy Officer at Majesco, discusses the importance of a holistic approach to AI in the insurance industry. She emphasizes the need for a robust data strategy and foundation, as well as access to clean and valid data. Garth highlights the challenges faced by insurers with legacy systems and the importance of modern technology architecture. She also discusses the role of core systems in enabling AI and the need for data ownership and stewardship.

Garth concludes by emphasizing the value of AI in revolutionizing and transforming the insurance industry. The conversation explores the importance of data ownership and governance in the insurance industry. It emphasizes the need for collaboration between IT and business teams to ensure accurate and valuable data.

The discussion also highlights the significance of curiosity and cognitive dexterity in leveraging AI and driving innovation. The speakers discuss the challenges of finding talent with both technical and business expertise. They stress the need for organizations to develop a data and analytics strategy, reallocate resources to prioritize important initiatives, and stop investing in outdated systems. The conversation concludes with a call to action for the industry to embrace a new operating model and technology foundation to stay competitive.

Takeaways:

A robust data strategy and foundation are crucial for successful AI implementation in the insurance industry.

Legacy systems pose challenges in terms of data access and consistency, highlighting the need for modern technology architecture.

Core systems should go beyond transactional data and enable access to raw data for advanced analytics and AI.

Data ownership and stewardship are essential for effective AI implementation.

AI has the potential to revolutionize and transform the insurance industry. Data ownership and governance should be a collaborative effort between IT and business teams.

Curiosity and cognitive dexterity are essential for leveraging AI and driving innovation.

Finding talent with both technical and business expertise is a challenge.

Organizations should develop a data and analytics strategy and reallocate resources to prioritize important initiatives.

Investing in outdated systems hinders progress and innovation.

The industry needs to embrace a new operating model and technology foundation to stay competitive.

Sound Bites:

"We as an industry have so much depth, but we're missing the latitudinal cross-section."

"I personally do not see GEN AI as a point solution. I think it minimizes the potential of GEN AI tremendously."

"Your technology foundation is absolutely critical in making decisions because it's going to allow you to do things or not allow you to do things."

"No, the business owns the data. It's about the business."

"That stewardshipness and that governance require some discipline and require some understanding of technology. But it more so requires an understanding of the business and the definitions and the value of the data and how it's being used."

"I forced myself, I was like, I can't run my business without technology, almost as a linguistic foundation, like Latin, like I needed to know technology the way somebody studying language would need to know roots."

Chapters:

00:00 Introduction and Background

03:02 The Importance of a Holistic Approach to AI in Insurance

05:25 GEN AI as a Holistic Solution

10:42 Technology Foundation and Decision Making

16:12 Enabling AI through Data Access and Architecture

23:16 The Potential of AI in the Insurance Industry

23:57 Data Ownership and Governance

26:43 Curiosity and Cognitive Dexterity in AI and Innovation

29:45 Challenges of Finding Talent with Technical and Business Expertise

35:02 Developing a Data and Analytics Strategy

36:02 Reallocating Resources for Priority Initiatives

37:47 Moving Away from Outdated Systems

41:15 Embracing a New Operating Model and Technology Foundation

Keywords:

AI, data strategy, data foundation, legacy systems, technology architecture, core systems, data ownership, data stewardship, insurance industry, data ownership, data governance, collaboration, IT, business, curiosity, cognitive dexterity, AI, innovation, talent, data and analytics strategy, resource allocation, outdated systems, operating model, technology foundation