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How AI Investing Shapes the Next Tech Cycle
AI became expensive the same way anything does: by outpacing the world around it.
Join us in this episode with Noah Yago, Vice President of Cisco Investments at Cisco, to trace how generative AI reached this moment and what comes next. Drawing on decades of experience across venture capital, corporate development, and global investing, Noah walks through how Cisco thinks about AI not as a single breakthrough, but as a sequence of bets across models, data, infrastructure, and geography.
We tackled early machine learning investments to today’s foundation models, then forward into world models, spatial intelligence, and sovereign AI stacks. Noah also explains why capital concentration shapes outcomes, why enterprise adoption looks different from consumer hype, and why regional data and regulation are quietly redefining how AI systems are built and deployed.
Rather than predicting a single winner, this episode explores how AI markets actually form, how costs eventually fall, and why staying close to the fastest growers matters more than betting on any one narrative.
In this episode, you’ll learn:
Why AI markets reward early scale and how access to capital directly affects talent, cost structures, and long-term survival
How world models and spatial intelligence change compute economics and improve reasoning beyond text-based systems
What enterprise and public sector adoption reveal about on-premise AI, regulatory pressure, and hybrid deployment strategies
Things to listen for:
(00:00) Meet Noah Yago
(01:15) From founder to venture investor inside Cisco
(03:59) How Cisco began treating AI as a core investment focus
(05:32) The four AI categories Cisco invests in
(07:31) Competing foundation models and concentrated capital
(09:45) Regional AI stacks and data sovereignty pressures
(13:54) Why model performance is flattening
(15:21) World models and the next phase of AI reasoning
(18:19) Data as a moat across text, video, and 3D
(19:32) Sovereign AI clouds and state-driven infrastructure
(22:56) Why enterprises are reconsidering on-prem AI
(28:42) Capital intensity and winner-take-all dynamics
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By BigID
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AI became expensive the same way anything does: by outpacing the world around it.
Join us in this episode with Noah Yago, Vice President of Cisco Investments at Cisco, to trace how generative AI reached this moment and what comes next. Drawing on decades of experience across venture capital, corporate development, and global investing, Noah walks through how Cisco thinks about AI not as a single breakthrough, but as a sequence of bets across models, data, infrastructure, and geography.
We tackled early machine learning investments to today’s foundation models, then forward into world models, spatial intelligence, and sovereign AI stacks. Noah also explains why capital concentration shapes outcomes, why enterprise adoption looks different from consumer hype, and why regional data and regulation are quietly redefining how AI systems are built and deployed.
Rather than predicting a single winner, this episode explores how AI markets actually form, how costs eventually fall, and why staying close to the fastest growers matters more than betting on any one narrative.
In this episode, you’ll learn:
Why AI markets reward early scale and how access to capital directly affects talent, cost structures, and long-term survival
How world models and spatial intelligence change compute economics and improve reasoning beyond text-based systems
What enterprise and public sector adoption reveal about on-premise AI, regulatory pressure, and hybrid deployment strategies
Things to listen for:
(00:00) Meet Noah Yago
(01:15) From founder to venture investor inside Cisco
(03:59) How Cisco began treating AI as a core investment focus
(05:32) The four AI categories Cisco invests in
(07:31) Competing foundation models and concentrated capital
(09:45) Regional AI stacks and data sovereignty pressures
(13:54) Why model performance is flattening
(15:21) World models and the next phase of AI reasoning
(18:19) Data as a moat across text, video, and 3D
(19:32) Sovereign AI clouds and state-driven infrastructure
(22:56) Why enterprises are reconsidering on-prem AI
(28:42) Capital intensity and winner-take-all dynamics