Asset management company Ares CEO: Avoiding AI chip financing due to business complexity.

date
14/11/2026
Ares Management Corp. is steering clear of financing the high-performance processors that run advanced AI models, instead investing in the data centers that house those chips. The asset manager is concerned that investing in GPUs could leave it stuck with assets facing obsolescence shortly after they come to market, according to a person familiar with the matter, who asked not to be identified because the information isn't public. "Frankly, the data center project due diligence is simpler, and the relative returns are very attractive," Chief Executive Officer Michael Arougheti said Thursday on an analyst call, referring to data center financing versus GPU chip financing. He added that this isn't a rejection of the GPU financing business, but that investment opportunities in data centers and supporting power infrastructure are more attractive to them. Arougheti said the data center financing market is enormous in size, while the capital available to deploy is relatively limited. The firm estimates that AI-related capital expenditure demand is about $5 trillion, of which roughly $2 trillion is for physical AI facilities and supporting infrastructure construction, and $3 trillion is for purchasing GPU chips. Arougheti said on the earnings call that he cannot conduct due diligence assessments of the value decay and depreciation curves of this type of technology. "At least at this stage, we choose to go deep in the half of the market we know best and where we have the deepest accumulated capabilities," he said.
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On November 12, at the opening ceremony of Baidu World 2026, Baidu founder Robin Li turned his attention to the downstream end of the AI technology stack: organizational capability. He judged that the next act of artificial intelligence is the intelligent organization, and that enterprises must redesign their organizations just as they would redesign a factory, and for the first time proposed the "three principles of organizational evolution." The first principle is to break down job boundaries and unleash organizational vitality. Jobs are the unit of the industrial age, while tasks are the unit of the intelligent age, and the future organization will be a network of tasks. He believes that jobs will not disappear, but will converge into two categories: Builders, who are responsible for creating new things, and Sellers, who are responsible for communication and connection between people. The second principle is to precipitate tacit knowledge and build organizational intelligence. The biggest difference between organizational intelligence and individual capability is the externalization of tacit knowledge. "True organizational intelligence is about making this knowledge explicit, precipitating it onto the company's platform, so that it can continuously accumulate, be called upon at any time, and be available to everyone. Organizational intelligence is the deepest moat for an enterprise." The third principle is to design closed-loop processes and drive organizational evolution. He stated that an intelligent organization is an intelligent system capable of autonomous evolution, and proposed the formula "Measurable + Looping = Continuous Evolution."
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