January 6, 2026
Finance

AMD CEO Lisa Su Foresees Exponential Growth in Global AI Computing Demand in 'Yottascale' Era

At CES 2026, Su highlights the collaboration and expansive infrastructure necessary to support the rapid advancement of AI technologies beyond data centers

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Summary

During her keynote address at CES 2026, AMD CEO Lisa Su outlined a transformative period for artificial intelligence computing, characterizing the industry’s trajectory as entering the 'yottascale' era. Su detailed the significant expansion in computing resources required to support increasingly complex AI models, emphasizing that meeting this growth demands diverse computing solutions spanning cloud systems, AI-enabled personal computers, and embedded devices. She further highlighted the critical need for an open, collaborative industry ecosystem to support long-term structural changes in AI deployment and capacity.

Key Points

AMD CEO Lisa Su introduced the concept of a 'yottascale' era at CES 2026, indicating a massive increase in global computing demands driven by advanced AI models.
Meeting the expanding AI compute needs will require diverse solutions spanning large-scale cloud systems, AI personal computers, and embedded computing devices.
Su emphasized the necessity of an open, collaborative ecosystem based on industry standards to sustainably advance AI technologies.
Discussion of AI infrastructure investment highlights concerns about potential constraints due to power shortages and financial limitations, as well as a shift toward localized AI computation.

At the Consumer Electronics Show (CES) in 2026, Lisa Su, Chief Executive Officer of Advanced Micro Devices Inc. (NASDAQ: AMD), presented a comprehensive outlook on the evolving landscape of artificial intelligence computing. Central to her remarks was the identification of an emerging 'yottascale' era, defined by the accelerating deployment of ultra-powerful AI models that necessitate a dramatic escalation in global computing capabilities.

Su articulated a vision where the proliferation of AI technologies surpasses traditional limits, driving compute demand to unprecedented magnitudes. "This moment in tech not only feels different; AI is different," Su remarked during her keynote. She characterized AI as "the most powerful technology that has ever been created," emphasizing its potential ubiquity and accessibility across diverse applications and geographies.

Explaining the implications of this rapid growth, Su stressed that realizing the potential of AI at such scale will require a computing footprint broader than what previous technology cycles have necessitated. She described this as a multifaceted infrastructure challenge involving integrated solutions encompassing expansive cloud-based systems, AI-enabled personal computing platforms, and embedded computing architectures in devices.

Importantly, Su conveyed that the pursuit of these advancements cannot occur in a siloed manner. Instead, it requires an inclusive, open ecosystem founded upon established industry standards and built through collaborative efforts among diverse technology sector participants. She pointed to this approach as essential for fostering innovation and ensuring scalable, sustainable AI deployment.

The AMD CEO framed this phase less as a transient trend and more as a structural shift with long-lasting ramifications. She highlighted that addressing the most significant global challenges will depend on harmonized action from across the industry ecosystem, indicating a need for sustained cooperation and strategic alignment.

Conversations about AI infrastructure investment growth have recently been accompanied by concerns regarding the sustainability of current spending momentum. Despite the robust capital expenditures by major technology companies, questions persist about how resource limitations such as power shortages and fiscal considerations might cap infrastructure expansion rates needed to meet intensifying demand.

Echoing these dynamics, Aravind Srinivas, CEO of Perplexity AI, recently underscored a potential paradigm shift away from conventional, centralized data center models. As AI capabilities become increasingly integrated and optimized for local devices, the necessity for extensive, centralized inference processing could significantly diminish.

"The biggest threat to a data center is if the intelligence can be packed locally on a chip that's running on the device," Srinivas noted, highlighting a technological evolution that could redefine AI infrastructure deployment in coming years.

Regarding AMD's market performance, the company's share price declined by 1.07% on Monday, closing at $221.08. Overnight trading showed a modest increase of 0.4%. In Benzinga’s Edge Stock Rankings, AMD scores strongly on Momentum, reflecting favorable trends over medium and long-term horizons.

The view presented by Su outlines a vision where AI's impact is vast, necessitating extensive computing innovation and industry-wide collaboration, with implications well beyond the confines of current data center-centric paradigms.

Risks
  • The rapid rise in AI compute demand could be limited by physical constraints such as power availability and financial pressures on infrastructure investment.
  • A shift toward embedding AI capabilities locally on devices may reduce dependence on centralized data center infrastructure, potentially disrupting current investment models.
  • Failure to establish and maintain an open and collaborative ecosystem across the technology industry may slow the adoption and scaling of AI technologies.
  • Uncertainties remain over how quickly global infrastructure can adapt to the surging compute requirements anticipated during the 'yottascale' era.
Disclosure
Education only / not financial advice
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