Jeetu Patel: Cisco's AI infrastructure orders hit $9.3 billion in two years

Cisco positions itself as the "picks and shovels" company of the AI era

Jeetu Patel, Cisco's president and chief product officer, described the company's role as providing infrastructure so that "AI just runs the way that you want it to and it runs securely and safely." He said this framing of Cisco did not exist four years ago and represents a deliberate transformation of a company already operating at enormous scale.

Patel credited the shift to setting direction, hiring the right people, and identifying which markets to pursue, while stressing that the engineering teams, not leadership, did the actual work.

Patel runs Cisco in "founder mode," calling it the "world's largest startup"

Patel said he operates as if he were "a latestage co-founder of Cisco," despite joining 36 years after the company's founding. He described a "rule of thirds" for his leadership team: a third are Cisco veterans who know how to maneuver the company, a third are outside hires who are systems thinkers, and a third are founders and CEOs of acquired companies given charters larger than the businesses they sold.

"I feel like Cisco is in wartime right now." — Jeetu Patel

He argued that operating "with speed and scale" simultaneously is what distinguishes a startup mentality applied at large-company scale, rather than being merely fast or merely big.

Patel expects AI to require more engineers, not fewer

Patel rejected framing Cisco's internal AI adoption around efficiency. "My strong assumption is moving forward that we will actually need more engineers, not less," he said, arguing that every step-function improvement in AI creates a new human bottleneck — automating coding shifts the bottleneck to code review, then to judgment about what to build.

To drive adoption among 32,000 engineers, Cisco guaranteed employees that failing to use AI, not using it, would put their jobs at risk, and gave unlimited tokens initially. Patel cited an engineering leader who told him Cisco had refactored "half a million lines of code" into "120,000 lines of code" within two weeks, a roughly 5x improvement, as a turning point in internal confidence. Cisco also became an early design partner with OpenAI and Codex.

Hardware and silicon adopt AI more slowly than software

Patel said Cisco's software, hardware, and silicon businesses each have different AI adoption cycles. Software moves fastest; hardware shows emerging design patterns but lags; silicon teams have been more cautious due to concerns about IP and data leaving the company. He noted silicon requires roughly a five-year planning cycle from IP development to at-scale production, compared with 18-24 months for hardware, 12-18 months for operating systems, and weekly to three-month cycles for models and agents.

Cisco's AI infrastructure orders scaled from zero to $9.3 billion in two years

Patel detailed the networking shift driving data center buildouts: from single-GPU training runs, to multi-GPU servers, to racks, to "scale out" networking across rows, and now "scale across" networking linking data centers that may be hundreds of kilometers apart due to power constraints. Cisco focuses on scale-out and scale-across networking, including silicon, switch trays, and photonics.

He said Cisco projected $1 billion in hyperscaler AI orders in year one but reached $2.3 billion; it then targeted $5 billion for year two but reached $9 billion (totaling $9.3 billion since inception), against total company revenue of $63 billion. He estimated a gigawatt of data center capacity now costs close to $50 billion, with networking representing roughly 10-15% of that.

Patel argues there is no AI infrastructure bubble

Asked whether the industry is overbuilding, Patel said "categorically not," distinguishing the current buildout from the dot-com era by arguing that infrastructure today is consumed almost instantly rather than waiting for demand to catch up. He cited a claim that an AI agent is "450% more consumptive" of network bandwidth than a human performing the same task, and noted that under 2% of people currently use agents in any power-user capacity.

He allowed that some individual company valuations could be "frothy" amid experimentation, but said that does not constitute a bubble unless the underlying secular shift itself is in question, which he said is hard to argue against.

Security and "trusted delegation" are framed as the next major constraint

Patel said that after compute availability, the larger looming problem is whether users can trust AI systems enough to delegate work to them. "The difference between trusted delegation and untrusted delegation is the difference between market leadership and complete abject bankruptcy," he said. He pointed to Cisco's AI Defense product, launched a year and a half earlier, and the acquisition of a company called Galileo, as part of a broader agentic security platform covering model visibility, non-human identity management, red-teaming, and runtime guardrails.

On his personal life, Patel described growing up in India with a father he called "a high stakes con man," moving to the U.S. at 19, waiting tables at Sizzler, and later taking out loans to buy into a market research company he ran for 17 years before joining EMC, then Box, then Cisco. He described staying in that first business as his "biggest mistake," driven by ego rather than learning, and urged founders to align their ambitions with their business model and not squander whatever platform or opportunity they are given.