Enterprise infrastructure is undergoing a seismic transformation as generative artificial intelligence and agentic systems push demands on cloud, data and compute to unprecedented levels. What was once back-end plumbing is now the engine room of competitive advantage.

From data-driven decision-making to reasoning-capable agents, the role of infrastructure has shifted from supporting business to actively shaping it. Organizations are no longer just lifting and shifting workloads to the cloud — they’re rebuilding their foundations for a future where AI-native applications, real-time insights and workload autonomy are the norm. Token economics, model specialization and hybrid deployment are no longer emerging trends — they’re defining the next era of enterprise tech strategy, according to Matt Garman (pictured), chief executive officer of Amazon Web Services Inc.

AWS’ Matt Garman talks with theCUBE about enterprise infrastructure.

“People are finally realizing that it is their industry is going to change, their business is going to change, the jobs of every employee that they have are going to fundamentally change,” Garman said. “They have to change along with that and move quickly.”

Garman spoke with John Furrier at the AWS Mid-Year Leadership Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how generative AI and agentic systems are accelerating a major shift in enterprise infrastructure, with Garman outlining how cloud, data and developer tools are reshaping business strategy, operations and innovation.

The new demands reshaping enterprise infrastructure

Across sectors, organizations are turning to the cloud not just for flexibility but to unlock the full potential of their data. Leaders are increasingly aware that their intellectual property lies in the data they collect and how they apply it using AI. As the shift accelerates, enterprise infrastructure must deliver both performance and precision, according to Garman.

“It all starts with helping them figure out how they get their data in a cloud world and organized in such a way that they can take advantage of it,” he said. “I think increasingly enterprises and startups and everyone are realizing that their data is going to be their IP. That’s the thing that’s going to differentiate what they can do versus others.”

As enterprises embrace AI-powered workflows, many are running into new pressures: cost management, latency and the hunger of agentic systems for compute tokens. Cloud infrastructure needs to meet these demands with scalability and efficiency while also supporting the developer ecosystem that builds on top of it, Garman explained.

“Agents eat tokens for breakfast, lunch and dinner,” he said. “This dynamic of tokens becomes a really big deal in this age of reasoning because it puts more pressure on tokens and they don’t have unlimited budgets. They’re looking at a kind of a, not reset, but like a re-architecture because the demand for tokens is putting pressure on more large-scale systems.”

Agentic workflows, developer momentum and cloud-native expansion

AI is no longer a side project for startups — it’s a core enabler of enterprise operations. From hiring pipelines to software development, companies are embedding agentic workflows to accelerate performance and decision-making. Internal tools such as Amazon Q Developer and the Strands Agents SDK demonstrate how deeply integrated these technologies have become, delivering significant gains across day-to-day functions, according to Garman.

“When they’re developing with that, sometimes I hear developers saying that they get two, three, four X performance boost gains because we’re building agentic workflows across everything that they do,” he said. “It’s not just code completion, but it’s writing documentation for them. It’s writing unit tests for them; it’s actually helping them reason about what the architecture of a system looks like. Agentic is one of those things that’s changing that math equation.”

Meanwhile, the startup ecosystem is evolving in step with enterprise needs. Builders are shifting their focus away from consumer apps and toward domain-specific solutions that drive measurable value. This new wave of startups is building on mature infrastructure and targeting real-world challenges with purpose-built models and tools, Garman added.

“There’s a bunch of startups that are moving from not just building consumer applications, where a lot of startups were back in the day, but just really focusing on ‘how do I help enterprises move quickly and get value from that data?’ Some of that is bringing sources of data together,” he said.

This new agility is becoming essential as businesses face global uncertainty and evolving technology demands. A cloud-native foundation gives organizations the freedom to scale, adapt and evolve quickly — without waiting on legacy processes or rigid systems, Garman pointed out.

“Whether there’s geopolitical change, whether there’s technology change, whether there’s a global pandemic, whatever the thing is that happens, customers and companies need to be ready to deal with that change,” he said. “Being in a cloud world allows you to be agile, scale up and down, move to different geographies, change technology stacks, whatever you need to do much more quickly.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the AWS Mid-Year Leadership Summit:

Photo: SiliconANGLE