SAS showcases enterprise AI strategy in Singapore

Promotes stacking technologies to better operationalize AI, while focusing on the urgent need for trust and governance.

SAS believes enterprises should go beyond adopting agentic AI in a silo and stack technologies that best fit the business’ use case to unlock greater outcomes.

“If you look at enterprise use cases, the main goal of agentic AI is [to] break down the silos — data silos, organizational silos — but also to automate business processes so they can scale,” said Patrick Xhonneux, senior vice president, Marketing at SAS.

“Their focus shifts from material to the accuracy, and especially the repeatability of the process itself.”

Speaking at SAS Innovate Singapore, Xhonneux focused on three aspects of agentic AI that customers should consider to realize successful outcomes — managing compound error or risk, as well as building trust, while also enabling a repeatable blueprint for AI-assisted processes.

He also made a case for enterprises to tap on converging technologies and build digital twins to minimize costs and create greater business opportunities. For instance, on top of enabling agentic AI to manage complex workflows, enterprises can tap on machine learning like generative AI, as well as computer vision to detect patterns and safely turn risks into opportunities.

“Optimization is [about] choose the best outcome from all these techniques involved and when these capabilities come together, you don’t just get better models, you get the digital twin,” he said.

SAS struck a partnership with Unreal Engine (UE) from Epic Games in 2025 to enhance their digital twins solution by combining its SAS Viya analytics software with UE’s 3D simulations. At the Innovate event, Xhonneux shared successful digital twin pilots with global customers in manufacturing and healthcare.

Separately, SAS has shared that while banks and financial services are primarily the vendor’s key customers, the increasing use of AI has seen the need for SAS solutions in other industries.

Hence, beyond reaching out to potential customers in manufacturing and healthcare at the Innovate event this year, the SAS team shared use cases for its solutions in the energy sector. For instance, SAS helped an oil and gas customer create digital hedges to detect unsafe working conditions and keep workers safe as well as prevent expensive repairs.

‘How do we trust AI?’

Additionally, just like Xhonneux, Craig Jennings, SAS’ vice president of Financial Services for Australia, New Zealand, and ASEAN, also talked about how enterprises are increasingly asking about trust and governance as they consider investing in AI.

“Just 12 months ago, organizations were asking, how do we adopt AI as fast as possible?” said Jennings in his opening keynote.

“Today, they're asking something much bigger: How do we trust it? How do we govern it, manage it, and attempt to control it? And how do we ensure that every AI investment we make is delivering measurable value?

“Success won’t belong to the organization that simply uses the most AI. It will belong to those that apply AI intelligently, responsibly, and with purpose. That is why trusted AI matters. You need the confidence that your AI is transparent, governed, and delivering value.”