Anoop Sagoo, Accenture's Southeast Asia CEO, said firms are moving from AI experimentation toward deployment but struggle to embed the technology into operations.

This shift is critical because the ability to scale AI determines whether companies can move from isolated pilots to realizing actual revenue growth. Without a systemic approach, AI remains a siloed tool rather than a core operational driver.

Speaking at the ATxSummit in Singapore, Sagoo said that many organizations face roadblocks when attempting to integrate artificial intelligence into their daily workflows [1]. He said that firms require stronger data foundations to unlock the full potential of these tools and ensure that adoption is systemic rather than fragmented [1], [2].

The challenge lies in the transition from "AI pilots" to full-scale implementation [3]. While many companies have successfully tested AI in small-scale environments, embedding that logic into the broader organizational structure requires a fundamental change in how data is managed and accessed [2].

Broader market trends indicate a significant push toward enterprise adoption. Some private equity firms are currently offering AI labs a $14 billion shortcut to accelerate this process of enterprise integration [4]. This financial influx suggests a high-stakes race to move AI out of the laboratory and into the marketplace.

Sagoo said that the goal for regional firms is to move away from siloed adoption [2]. By building a more robust infrastructure, companies can ensure that AI supports every level of the business rather than existing as a standalone project [1].

“Firms are moving from AI experimentation toward deployment but struggle to embed the technology into operations.”

The transition from experimental AI to systemic adoption marks a second phase of the AI boom. While the first phase focused on the capabilities of Large Language Models, the current phase focuses on the 'plumbing'—the data architecture and operational workflows required to make AI a reliable part of a company's revenue engine. The involvement of private equity indicates that the market now views AI integration as a scalable asset rather than a speculative venture.