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| Cisco CEO warns the AI boom looks like a bubble — but says AI will be bigger than the internet | |
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| Cisco CEO Chuck Robbins says AI will be bigger than the internet but today’s market is probably a bubble. Here’s what that means for jobs, security and investors. | |
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| Cisco CEO warns the AI boom looks like a bubble — but says AI will be bigger than the internet | |
| Nature | |
| Climate | |
| Cisco CEO on the AI ‘bubble’: why the crash can still leave winners | |
| / | |
| Technology | |
| / By | |
| Admin | |
| Summary: | |
| Cisco CEO Chuck Robbins says AI could be | |
| bigger than the internet | |
| , but he expects a painful shakeout first—“winners will emerge, and there’ll be carnage along the way.” That’s not a throwaway quote. Robbins lived through the dot‑com boom as Cisco became the most valuable company in the world in 2000, then lost roughly 80% of its value when the bubble burst. | |
| The core message is nuanced: AI is real and transformative, but today’s investment cycle is overheated, and not every company (or job role) survives the transition. | |
| What Robbins is actually saying (not the headline version) | |
| From the report: | |
| AI will “change everything” and may be bigger than the internet. | |
| The current market is “probably” a bubble. | |
| Some companies “won’t make it.” | |
| Some jobs will change or be eliminated, especially in areas like customer service. | |
| The bigger risk for workers is not “AI taking your job,” but “someone using AI well taking your job.” | |
| AI will improve cyber attacks and scams; security becomes more important. | |
| The UK has “pretty good odds” of becoming an AI superpower if it embraces AI. | |
| The theme is not “panic.” It’s “embrace the shift, but be honest about disruption.” | |
| Why the dot-com analogy is useful (and where it misleads) | |
| The dot‑com bubble is often invoked lazily, as if it means “hype now, crash later.” The more useful lesson is structural: | |
| What the bubble built | |
| Even though many internet companies died, the era built: | |
| data centres | |
| fibre networks | |
| software infrastructure | |
| consumer behaviours around online services | |
| The underlying technology won. | |
| What the bubble destroyed | |
| Speculative equity value in companies without durable products or distribution. | |
| Robbins’ “carnage” framing is basically that: capital and companies get wiped out, but the platform shift still happens. | |
| Cisco’s vantage point: infrastructure, not apps | |
| Cisco is not primarily an “AI app” company. It sells and builds infrastructure that enables AI to run: | |
| networking | |
| security | |
| data centre systems | |
| So when Cisco talks about AI, it’s often speaking from the layer that survives bubbles. | |
| App companies come and go; infrastructure and distribution winners often persist. | |
| Why networking becomes a bottleneck in AI | |
| Large models are trained across many accelerators. The more chips you use, the more your system becomes limited by: | |
| network latency (how fast nodes can coordinate) | |
| bandwidth (how much data can move) | |
| reliability (a single failure can slow or interrupt training runs) | |
| That’s why companies talk about “AI clusters” like they’re supercomputers. In that world, networking isn’t plumbing—it’s a competitive differentiator. | |
| The jobs angle: what changes first | |
| Robbins points to customer service as a category where companies may need fewer people. | |
| Why customer service is the first target | |
| Support workflows often have: | |
| high volume | |
| repeated questions | |
| known policy rules | |
| text-based inputs and outputs | |
| That makes them a natural fit for AI triage and partial automation. The first wave is usually “deflection” (answers without a human), followed by “agent assist” (humans supported by AI), and then automation of the easiest end-to-end cases. | |
| That’s plausible because customer support has many: | |
| repetitive questions | |
| standard workflows | |
| text-based interactions | |
| But the deeper point is: AI doesn’t replace “jobs.” It replaces | |
| tasks | |
| . | |
| A typical job is a bundle of tasks: | |
| some automatable (drafting, summarising, triage) | |
| some not (judgement, empathy, accountability, negotiation) | |
| So the workforce impact is uneven: | |
| people who adapt become more productive and more valuable | |
| people in roles dominated by repeatable tasks face displacement pressure | |
| “Someone good at AI will take your job” — what to do with that | |
| This line is uncomfortable because it’s true. | |
| In practical terms, it suggests a survival strategy: | |
| learn the tools early | |
| build workflows and checklists | |
| become the person who can combine AI speed with human judgement | |
| The competitive advantage is not knowing prompts—it’s knowing: | |
| what to ask | |
| what to verify | |
| what the output should look like | |
| where the risk lives | |
| Security: AI makes scams and attacks better | |
| Robbins warns that AI will make cyber attacks better and phishing more convincing. | |
| That’s already visible in: | |
| better-written scam emails | |
| more believable impersonation | |
| deepfake audio/video used for fraud | |
| So the “AI revolution” has a parallel revolution in: | |
| identity verification | |
| fraud detection | |
| secure communications | |
| Security is not a side topic. It’s one of the primary battlegrounds of AI adoption. | |
| What does “AI bigger than the internet” actually mean? | |
| If you strip away rhetoric, “bigger than the internet” could mean: | |
| Another interpretation: the internet connected people and systems, but most work still required humans to translate information into action. AI reduces that translation cost. If that’s true, AI becomes a general productivity layer the way electricity became a general capability—visible in every sector, not just “tech.” | |
| AI becomes the interface to information (search changes) | |
| AI becomes the interface to work (agents in workflows) | |
| AI becomes embedded in every product (from banking to healthcare) | |
| The internet connected systems. AI changes what those systems can | |
| do | |
| So the claim is that AI isn’t merely a new app category; it’s a capability layer that rewrites software economics. | |
| The UK as an AI superpower: conditions that matter | |
| Robbins says the UK has “pretty good odds” if it embraces AI. | |
| What “embrace” usually means in policy terms: | |
| make it easy for responsible experimentation to happen in business and government | |
| invest in skills so adoption isn’t limited to a small elite | |
| fund research and commercialisation bridges (not just academic work) | |
| maintain credible regulation that targets harms without freezing innovation | |
| The UK has strengths (research, talent, finance, a strong startup culture) but also constraints (compute access and competition with the US/China for top labs). The likely path to “superpower” status is not beating the US and China at scale, but building competitive clusters and high-value specialisations. | |
| In practice, “embrace AI” means: | |
| research strength + talent pipelines | |
| compute access (or partnerships) | |
| supportive but realistic regulation | |
| adoption in government and industry | |
| Countries that adopt earlier may gain productivity advantages and attract investment. | |
| What a “healthy” AI buildout looks like | |
| A bubble narrative is compelling, but it’s also possible to have both hype and real progress at once. | |
| A healthier buildout tends to show: | |
| clear ROI use cases (cost reduction or revenue lift you can measure) | |
| consistent deployment in workflows (not just demos) | |
| improving safety practices (monitoring, evals, red-teaming) | |
| consolidation around standards and platforms | |
| That’s different from a frothy market where most value is in announcements and fundraising. | |
| What to watch next (signals of a real bubble vs a healthy buildout) | |
| If this is a bubble, you should expect: | |
| Crowding in apps | |
| Many similar products competing on thin differentiation. | |
| Margin pressure | |
| Companies spending heavily on compute without clear revenue payback. | |
| Consolidation | |
| Stronger players acquiring or outlasting weaker ones. | |
| Infrastructure winners | |
| Network, chip, cloud, and security providers benefiting regardless of which apps win. | |
| Regulatory shock | |
| A major incident (fraud, deepfakes, model misuse) can accelerate rules that change economics. | |
| Practical advice: how to be on the winning side of the transition | |
| For individuals: | |
| learn how to use AI tools in your domain (not just generic prompting) | |
| build verification habits (what do you trust, how do you check it?) | |
| focus on tasks where humans are still accountable: judgement, relationships, strategy, safety | |
| For organisations: | |
| start with measurable use cases (support, analytics, code review) | |
| invest in security and fraud defence early | |
| treat AI as a process change, not a “tool rollout” | |
| Bottom line | |
| Robbins’ message is not anti-AI. It’s a realistic diagnosis of platform transitions: | |
| the technology will reshape work and security | |
| the investment cycle is overheated | |
| many firms will fail | |
| If you’re building or investing, the long-run winners will be those who turn AI into durable distribution, trusted products, and measurable value—not just bigger demos. | |
| Bottom line (one sentence) | |
| AI is a real platform shift, but the market is behaving like a bubble; the winners will be the companies that turn AI into trusted, measurable value while surviving the shakeout. | |
| Sources | |
| BBC News (Technology): | |
| https://www.bbc.com/news/articles/cr57p2ve8glo?at_medium=RSS&at_campaign=rss | |
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| TikTok US: when outages look like censorship (and why trust breaks fast) | |
| Iran’s internet returns in fragments: how ‘rationed connectivity’ actually works | |
| Cisco CEO Chuck Robbins says AI will be bigger than the internet but today’s market is probably a bubble. Here’s what that means for jobs, security and investors. | |
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