GenAI Engineering in the Enterprise and Why It Matters

Description

This IDC Perspective discusses the importance of GenAI Engineering in enterprises, highlighting its potential to drive business growth and innovation. It provides an in-depth analysis of the current state of GenAI adoption, the challenges organizations face, and the need for a systematic approach to maximize the value of GenAI implementations. This content also emphasizes the role of data governance, collaboration, and a phased approach in successful GenAI implementations. It concludes with advice for technology buyers on establishing a GenAI Engineering discipline and leveraging data intelligence."Every organization needs to develop a corporate discipline that is charged with bridging strategy and implementation; this discipline must also be charged with consistently applying key patterns and principles to GenAI implementation projects to ensure they deliver sustainable value," said Neil Ward-Dutton, VP AI, Automation and Analytics Europe, IDC. "That discipline is GenAI Engineering."

Product Code: EUR151907224

Executive Snapshot

Situation Overview

Generic Consumer Services Created the GenAI Boom in Enterprises, Too
Enterprise Needs and Values Point Beyond the Generic
GenAI Engineering: A Discipline Every Organization Needs
- Introducing GenAI Engineering
- GenAI Engineering Integrates Discipline Across Three Domains
- GenAI Engineering Shapes Implementation According to Three Governing Factors
GenAI Engineering in the Models Domain: Dealing With a Cambrian Explosion of GenAI Models
- The Role of AI Platforms
GenAI Engineering in the Outcomes Domain: Dealing with a Range of Implementation Choices
GenAI Engineering in the Data Domain: Reflecting Data's Value
- The Role of Data Governance
- Data Value Chains Are Critical for GenAI
GenAI Engineering: A Collaborative Discipline
Key Roles Involved in GenAI Engineering
GenAI Engineering and the Role of a COE