Unlocking Generative AI Success with Quality Engineering

Generative AI’s adoption pace has been extraordinary. The technology’s advanced cognitive capabilities and ability to understand nuanced situations to generate context-aware outputs mark a significant leap in the intelligent systems space. Generative AI’s adoption is also due to its distinctive out-of-the-box accessibility, which grants enterprises effortless access to generative AI systems. However, the technology’s unchecked use has risks. Improper adoption can lead to confidential data leakage, IP violations, regulatory issues, and quality risks, such as model performance issues, biased outputs, and integrity concerns.

In this viewpoint, we explore how pivotal a role quality function must play to assure enterprise generative AI adoption journey. We examine the role of quality function in mitigating all the associated adoption risks. This report benefits enterprises who wants to understand this strategic confluence of generative AI and quality function.

Scope

All industries and geographies

Contents

In this report, we examine:

• Generative AI adoption’s current status among enterprises
• The strategic confluence of generative AI and the quality function
• Anticipated developments in this space in 2024 and beyond

Membership(s)

Application Services

Sourcing and Vendor Management