As enterprises navigate today’s ever-evolving digital landscape, rapid time-to-value is increasingly essential to stay competitive. To drive efficiency, agility, and new business models, enterprises are investing in digital transformation initiatives, with generative AI emerging as a key enabler.

Generative AI can automate processes, enhance decision-making, and fuel innovation, yet its adoption presents challenges in data complexity, security, and scalability and operational reliability. Intelligent Automation Platforms (IAPs) offer a robust framework to overcome these limitations, providing governance, security, and scalability to maximize generative AI’s potential. Through integration with IAPs, generative AI can support complex use cases, increase flexibility, and improve data flow management, making AI-driven applications more reliable and effective.

In this viewpoint, we examine enterprises’ priorities to scale digital transformation, explore risks associated with generative AI adoption, and detail how IAPs can mitigate these challenges. It aims to guide IT leaders, business excellence teams, and digital transformation decision-makers in harnessing the combined power of generative AI and IAPs to achieve digital transformation objectives.

Scope

All industries and geographies

Contents

In this report, we assess:

• Enterprises’ priorities to scale digital transformation initiatives
• Key risks associated with generative AI adoption
• How enterprises can mitigate generative AI risks using IAPs
• The integration of generative AI and IAPs to empower digital transformation

Membership(s)

Service Optimization Technologies (SOT)

Sourcing and Vendor Management