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Data Center News > Blog > Global Market > Cisco: Infrastructure, trust, model development are key AI challenges
Global Market

Cisco: Infrastructure, trust, model development are key AI challenges

Last updated: February 4, 2026 1:46 am
Published February 4, 2026
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Cisco CEO Chuck Robbins says 2026 goes to mark a turning level for enterprise and large-scale AI use. He led off at present’s Cisco AI Summit, telling attendees that this would be the 12 months of agentic functions and constructing higher belief and safety into AI.

“There are many questions and discussions about what does it imply to your enterprise infrastructure? What does it imply to your safety posture? What does it imply to utility improvement cycles?” Robbins stated. 

[ Related: More Cisco news and insights ]

“One factor that bothers us is belief, the place there’s belief in what’s going to occur to your knowledge, belief within the fashions, belief in your infrastructure, belief within the brokers, belief within the companions that you simply’re working with – these are necessary points that the business must proceed to handle with AI going ahead,” Robbins stated.

AI obstacles

There are three predominant constraints which might be holding AI again, added Jeetu Patel, Cisco’s president and chief product officer.

“The primary one is that we have now an infrastructure constraint. We simply don’t have sufficient energy, compute and community bandwidth. In order that’s going to be an space that we’re spending billions on at Cisco. And I believe the business is spending trillions in ensuring that we will… exit and fulfill the wants of AI,” Patel stated. “We’re working very laborious to guarantee that we will construct out the vital infrastructure for AI.”

Patel pointed to Cisco’s P200 chip and the Cisco 8223 routing system introduced final October that shall be on the coronary heart of constructing Cisco-networked AI clusters.

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“The P200 chip was for the size out, as a result of what’s taking place now could be these fashions are getting greater the place they don’t simply match inside a single knowledge middle. You don’t have sufficient energy to simply pull right into a single knowledge middle,” Patel stated. “So now it is advisable to have knowledge facilities that may be a whole bunch of kilometers aside, that function like an ultra-cluster which might be coherent. And in order that requires a totally completely different chip structure to just remember to have capabilities like deep buffering and so forth and so forth… You might want to guarantee that these knowledge facilities might be scaled throughout bodily boundaries.” 

“As well as, we’re reaching the bodily limits of copper and optics, and coherent optics particularly are going to be extraordinarily necessary as we go begin constructing out this knowledge middle infrastructure. In order that’s an space that you simply’re beginning to see an incredible quantity of progress being made,” Patel stated.

The second constraint is the AI belief deficit, Patel stated. “We presently have to guarantee that these techniques are trusted by the individuals which might be utilizing them, as a result of should you don’t belief these techniques, you’ll by no means use them,” Patel stated.

“That is the primary time that safety is definitely turning into a prerequisite for adoption. Prior to now, you all the time ask the query whether or not you need to be safe, otherwise you need to be productive. And people had been type of wants that offset one another,” Patel stated. “We have to guarantee that we belief not simply utilizing AI for cyber protection, however we belief AI itself,” Patel stated.

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The third constraint is the notion of an information hole.

AI fashions get educated on human-generated knowledge that’s publicly out there on the Web, however “we’re working out,” Patel stated. “And what you’re beginning to see occur is artificial knowledge is attending to be extraordinarily potent in coaching these fashions.” The very best knowledge development is that of machine-generated knowledge, he stated. “As brokers get increasingly prolific, and as you might have these brokers working 24/7, you will notice continued quantities of acceleration and exponential development on machine-generated knowledge. At Cisco, it seems we’re the middle of all of these things,” Patel stated.

Patel additionally famous how AI programming has altered among the software program improvement occurring inside the corporate.

“It appeared like a far-fetched purpose at first of 2025, however now 70% of all AI merchandise now being developed at Cisco are utilizing code that’s generated by AI. I’d say that throughout the 12 months 2026, we can have no less than near a half a dozen merchandise that’ll have 100% of the code written by AI reasonably than written by people,” Patel stated. “People will nonetheless have a really invaluable position to play as a result of they’re going to guarantee that they’re writing specs they usually’re ensuring that they’re really going out and reviewing the code. However the bottleneck is now not going to be across the writing of the code exercise. The bottleneck goes to be across the studying and reviewing of the code exercise.”

Extra Cisco information:

  • Cisco provides clever coverage enforcement to mesh firewall household
  • Actively exploited Cisco UC bug requires immediate, version‑specific patching
  • Cisco’s 2026 agenda prioritizes AI-ready infrastructure, connectivity
  • Cisco lastly patches seven-week-old zero-day flaw in Safe Electronic mail Gateway merchandise
  • Cisco routers knocked out on account of Cloudflare DNS change
  • Cisco identifies vulnerability in ISE community entry management gadgets
  • Attackers bring their own passwords to Cisco and Palo Alto VPNs
  • Cisco confirms zero-day exploitation of Secure Email products
  • Cisco defines AI safety framework for enterprise safety
  • Cisco initiative targets system safety
  • Key takeaways from Cisco Associate Summit
  • AI networking demand fueled Cisco’s upbeat Q1 monetary
  • Cisco launches AI infrastructure, AI practitioner certifications
  • Cisco centralizes buyer expertise round AI
  • Cisco unveils built-in edge platform for AI
See also  .NET Aspire cloud development stack launches

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TAGGED: Challenges, Cisco, Development, infrastructure, Key, Model, Trust
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