Enterprise AI readiness is trailing industry rhetoric as organizations struggle to modernize infrastructure, control costs and choose appropriate applications. That gap is becoming more visible as companies attempt to move from limited experimentation into systems embedded in core business operations.
Much of today’s adoption remains concentrated in large language models, edge systems and agents for calendaring, software development and process automation. Businesses have yet to broadly extend AI into supply chains, inventory management and other core functions with more demanding data, security and governance requirements, according to David Linthicum, founder and lead researcher at Linthicum Research.
“Right now we’re just getting started with AI. I know everybody thinks there’s a huge AI party out there and they haven’t been invited, but the reality is businesses and enterprises are just getting going,” he said. “They’re figuring out their infrastructure. They’re figuring out how much it’s going to cost.”
Linthicum spoke with theCUBE Research’s Christophe Bertrand and co-host Alison Kosik at VMware Explore, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed enterprise adoption, Broadcom Inc.’s private cloud strategy and the risks of embracing autonomous agents without adequate business justification. (* Disclosure below.)
Enterprise AI readiness requires infrastructure — and restraint
Infrastructure remains the immediate obstacle for companies seeking to move beyond experimentation. Broadcom’s VMware AI Factory, built on VMware Cloud Foundation, seeks to simplify private AI deployment by automating the path from bare-metal infrastructure to model deployment.
“I’m talking to a lot of people here at the event. They’re not ready for the AI systems yet,” he said. “They’re looking for a path to make it happen, and they’re looking for a partner to … modernize their infrastructure and kind of take things to the next level so they can run AI on premises.”
Enterprise AI readiness also requires judgment about when autonomous agents add value. Linthicum estimated that most of the agentic applications he encounters introduce complexity, operational overhead and security concerns without requiring an agent-based architecture.
“The reality is people just need to calm down with the agent stuff. Probably 95% of the applications that I see that are agentic AI applications don’t need to be, and they’re hitting a thumbtack with a sledgehammer,” he said. “There are reasons to use it and reasons not to use it.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of VMware Explore:
(* Disclosure: TheCUBE is a paid media partner for the VMware Explore event. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)
