Rick Sherlund says the next phase of artificial intelligence will be defined less by flashy applications and more by what happens behind the scenes as AI becomes embedded in everyday business operations.
In a new CNBC interview, the Wall Street legend and senior adviser at Wedbush says that after several years of experimentation, AI is now moving directly into core enterprise workflows, changing how companies actually run.
He says that the shift is being driven by the rise of agents and agentic systems that collaborate across complex tasks inside organizations.
“After three years on the market now, it’s finally becoming part of business processes and workflows, how a company actually conducts business. So this involves the use of agents or agentics and how they collaborate and do complex workflows. As a result, the amount of inference that’s going to be required is going to explode.”
He explains that while a basic chatbot query may only require a single interaction with a model, real enterprise workflows demand far more computation.
“A single call to a chatbot means it’s one call to the LLM to give you the answer for inference. If it’s a workflow-related question, particularly for complex workflows, it could be 10 or 50 trips back to the LLM. So LLMs are going to really be stressed by enterprise systems. We’ve got reasoning we’re asking these models to do now. They’re not built for reasoning. So they just kind of throw a lot of weight into this GPU saying, give me 100 answers, and I’ll pick the best one.”
Sherlund believes that the dynamic makes AI inference the central engine of the modern economy, with implications far beyond software alone.
“So I think for all these reasons, you know, the inference is going to be the heartbeat of American global business. It’s how it runs.”
He closes by tying that inference surge directly to sustained demand for physical infrastructure.
“So that’s going to create enormous demand for data centers. So the data center trade, you know, I’m not worried about it.”
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