Izvršni direktor Cisca o "mehurčku" umetne inteligence: zakaj lahko po zlomu še vedno zmagajo

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Povzetek:Izvršni direktor Cisca Chuck Robbins pravi, da bi lahko bila umetna inteligencavečji od interneta, vendar pričakuje, da bo najprej boleč pretres – »pojavili se bodo zmagovalci, na poti pa bo pokol.« To ni izrečen citat. Robbins je preživel razcvet dot-com podjetij, ko je Cisco leta 2000 postal najvrednejše podjetje na svetu, nato pa je ob poku mehurčka izgubil približno 80 % svoje vrednosti.

Osrednje sporočilo je niansirano: umetna inteligenca je resnična in transformativna, vendar je današnji investicijski cikel pregret in ne preživi vsako podjetje (ali delovno mesto) prehoda.

Kaj Robbins dejansko pravi (ne naslovna različica)

Iz poročila:

  • Umetna inteligenca bo »spremenila vse« in bo morda večja od interneta.
  • Trenutni trg je "verjetno" mehurček.
  • Nekatera podjetja "ne bodo uspela".
  • Nekatera delovna mesta se bodo spremenila ali ukinila, zlasti na področjih, kot je storitev za stranke.
  • Večje tveganje za delavce ni »umetna inteligenca, ki vam bo vzela službo«, temveč »nekdo, ki bo dobro uporabljal umetno inteligenco, vam bo vzel službo«.
  • Umetna inteligenca bo izboljšala kibernetske napade in prevare; varnost postane pomembnejša.
  • Združeno kraljestvo ima "precej dobre možnosti", da postane velesila umetne inteligence, če jo bo sprejelo.

Tema ni »panika«. Gre za »sprejemanje spremembe, a iskrenost glede motenj«.

Zakaj je analogija z dot-com koristna (in kje zavaja)

Mehurček dot-com se pogosto omenja lenobno, kot da pomeni »zdaj hype, kasneje pa crash«. Bolj uporaben nauk je strukturen:

Kaj je zgradil mehurček

Čeprav je veliko internetnih podjetij propadlo, je ta doba zgradila:

  • podatkovni centri
  • optična omrežja
  • programska infrastruktura
  • vedenje potrošnikov v zvezi s spletnimi storitvami

Zmagala je osnovna tehnologija.

Kaj je mehurček uničil

Špekulativna vrednost lastniškega kapitala v podjetjih brez trajnih izdelkov ali distribucije.

Robbinsova uokviritev "pokola" je v bistvu tole: kapital in podjetja so izbrisana, vendar se premik platforme še vedno zgodi.

Ciscovo izhodišče: infrastruktura, ne aplikacije

Cisco ni primarno podjetje za "aplikacije umetne inteligence". Prodaja in gradi infrastrukturo, ki omogoča delovanje umetne inteligence:

  • mreženje
  • varnost
  • sistemi podatkovnih centrov

Ko Cisco govori o umetni inteligenci, pogosto govori z vidika plasti, ki preživi mehurčke.

Podjetja za aplikacije prihajajo in odhajajo; zmagovalci na področju infrastrukture in distribucije pogosto vztrajajo.

Zakaj mreženje postane ozko grlo v umetni inteligenci

Veliki modeli se učijo v številnih pospeševalnikih. Več čipov kot uporabljate, bolj je vaš sistem omejen z:

  • omrežna latenca (kako hitro se lahko vozlišča usklajujejo)
  • pasovna širina (koliko podatkov se lahko prenese)
  • zanesljivost (že ena sama napaka lahko upočasni ali prekine vadbene postopke)

Zato podjetja govorijo o »gručah umetne inteligence«, kot da bi bili superračunalniki. V tem svetu mreženje ni vodovod – je konkurenčna prednost.

Z vidika delovnih mest: kaj se najprej spremeni

Robbins opozarja na storitve za stranke kot kategorijo, kjer podjetja morda potrebujejo manj ljudi.

Zakaj je storitev za stranke prvi cilj

Podporni delovni tokovi imajo pogosto:

  • velika glasnost
  • ponavljajoča se vprašanja
  • znana pravila politike
  • vhodni in izhodni podatki na osnovi besedila

Zaradi tega so naravno primerni za triažo z umetno inteligenco in delno avtomatizacijo. Prvi val je običajno »preusmeritev« (odgovori brez človeka), sledi »pomoč agenta« (ljudje, ki jih podpira umetna inteligenca) in nato avtomatizacija najlažjih primerov od začetka do konca.

To je verjetno, ker ima podpora strankam veliko:

  • ponavljajoča se vprašanja
  • standardni delovni tokovi
  • interakcije na podlagi besedila

Globlje bistvo pa je: umetna inteligenca ne nadomešča »služb«. Nadomeščanaloge.

Tipično delo je sklop nalog:

  • nekatere avtomatizirane (osnutek, povzemanje, triaža)
  • nekateri ne (presojanje, empatija, odgovornost, pogajanje)

Torej je vpliv na delovno silo neenakomeren:

  • Ljudje, ki se prilagajajo, postanejo bolj produktivni in bolj dragoceni
  • Ljudje v vlogah, v katerih prevladujejo ponovljive naloge, se soočajo s pritiskom premestitve

»Nekdo, ki je dober v umetni inteligenci, vam bo vzel službo« – kaj storiti s tem

Ta stavek je neprijetna, ker je resničen.

V praksi to predlaga strategijo preživetja:

  • zgodaj se naučite orodij
  • izdelava delovnih procesov in kontrolnih seznamov
  • postanite oseba, ki lahko združi hitrost umetne inteligence s človeško presojo

Konkurenčna prednost ni poznavanje pozivov – temveč poznavanje:

  • kaj vprašati
  • kaj preveriti
  • kako naj bi izgledal izhod
  • kjer se skriva tveganje

Varnost: Umetna inteligenca izboljšuje prevare in napade

Robbins opozarja, da bo umetna inteligenca izboljšala kibernetske napade in lažno predstavljanje naredila prepričljivejše.

To je že vidno v:

  • bolje napisana lažna e-poštna sporočila
  • bolj verodostojna imitacija
  • globoko ponarejen zvok/videoposnetek, uporabljen za goljufijo

Torej ima »revolucija umetne inteligence« vzporedno revolucijo v:

  • preverjanje identitete
  • odkrivanje goljufij
  • varne komunikacije

Varnost ni stranska tema. Je eno glavnih bojnih področij uvajanja umetne inteligence.

Kaj pravzaprav pomeni »umetna inteligenca, večja od interneta«?

Če odmislimo retoriko, bi lahko »večji od interneta« pomenil:

Druga razlaga: internet je povezal ljudi in sisteme, vendar je večina dela še vedno zahtevala, da ljudje pretvarjajo informacije v dejanja. Umetna inteligenca zmanjšuje te stroške prevajanja. Če to drži, postane umetna inteligenca splošna plast produktivnosti, tako kot je elektrika postala splošna zmogljivost – vidna v vseh sektorjih, ne le v »tehnologiji«.

  • Umetna inteligenca postane vmesnik do informacij (spremembe iskanja)
  • Umetna inteligenca postane vmesnik za delo (agenti v delovnih procesih)
  • Umetna inteligenca se vgradi v vsak izdelek (od bančništva do zdravstva)

Sistemi, povezani z internetom. Umetna inteligenca spreminja, kaj ti sistemi zmorejo.narediti.

Torej trdijo, da umetna inteligenca ni zgolj nova kategorija aplikacij; gre za plast zmogljivosti, ki na novo piše ekonomijo programske opreme.

Združeno kraljestvo kot velesila umetne inteligence: pogoji, ki so pomembni

Robbins pravi, da ima Združeno kraljestvo "precej dobre možnosti", če sprejme umetno inteligenco.

Kaj »sprejeti« običajno pomeni v političnem smislu:

  • olajšati odgovorno eksperimentiranje v podjetjih in vladi
  • vlagajte v znanja in spretnosti, da posvojitev ne bo omejena le na majhno elito
  • financirati raziskave in mostove za komercializacijo (ne le akademskega dela)
  • ohraniti verodostojno regulacijo, ki je usmerjena v škodo, ne da bi pri tem zamrznila inovacije

Združeno kraljestvo ima prednosti (raziskave, talente, finance, močno kulturo zagonskih podjetij), a tudi omejitve (dostop do računalništva in konkurenca z ZDA/Kitajsko za vrhunske laboratorije). Verjetna pot do statusa "velesile" ni premagovanje ZDA in Kitajske v velikem obsegu, temveč gradnja konkurenčnih grozdov in visokokakovostnih specializacij.

V praksi »sprejeti umetno inteligenco« pomeni:

  • raziskovalna moč + cevovodi talentov
  • dostop do računalništva (ali partnerstva)
  • podporna, a realistična ureditev
  • sprejetje v vladi in industriji

Države, ki to uvedejo prej, lahko pridobijo prednosti produktivnosti in privabijo naložbe.

Kako izgleda »zdrava« gradnja umetne inteligence

Pripoved o mehurčkih je prepričljiva, vendar je mogoče hkrati doseči tako navdušenje kot resničen napredek.

Bolj zdrava postava ponavadi kaže:

  • jasni primeri uporabe donosnosti naložbe (zmanjšanje stroškov ali povečanje prihodkov, ki ga lahko izmerite)
  • dosledna uvedba v delovnih procesih (ne le v demonstracijah)
  • izboljšanje varnostnih praks (spremljanje, evalvacije, združevanje v red teame)
  • konsolidacija okoli standardov in platform

To se razlikuje od penastega trga, kjer je največja vrednost v objavah in zbiranju sredstev.

Kaj spremljati naprej (signali pravega mehurčka v primerjavi z zdravo rastjo)

Če gre za mehurček, lahko pričakujete:

  1. Gneča v aplikacijah
    Veliko podobnih izdelkov tekmuje na področju tanke diferenciacije.

  2. Pritisk na maržo
    Podjetja veliko zapravljajo za računalništvo brez jasnega donosa od prihodkov.

  3. Konsolidacija
    Močnejši igralci pridobijo ali prekašajo šibkejše.

  4. Zmagovalci infrastrukture
    Ponudniki omrežij, čipov, oblaka in varnostnih storitev imajo koristi ne glede na to, katere aplikacije zmagajo.

  5. Regulativni šok
    Večji incident (goljufija, ponaredki, zloraba modelov) lahko pospeši pravila, ki spreminjajo ekonomijo.

Praktični nasvet: kako biti na zmagovalni strani prehoda

Za posameznike:

  • Naučite se uporabljati orodja umetne inteligence v svoji domeni (ne le generičnih pozivov)
  • vzpostaviti navade preverjanja (čemu zaupate, kako to preverite?)
  • osredotočite se na naloge, pri katerih so ljudje še vedno odgovorni: presoja, odnosi, strategija, varnost

Za organizacije:

  • začnite z merljivimi primeri uporabe (podpora, analitika, pregled kode)
  • zgodaj investirajte v varnost in zaščito pred goljufijami
  • obravnavajte umetno inteligenco kot spremembo procesa, ne kot "uvedbo orodja"

Bistvo

Robbinsovo sporočilo ni proti umetni inteligenci. Gre za realistično diagnozo prehodov platform:

  • tehnologija bo preoblikovala delo in varnost
  • investicijski cikel je pregret
  • veliko podjetij bo propadlo

Če gradite ali vlagate, bodo dolgoročni zmagovalci tisti, ki bodo umetno inteligenco spremenili v trajno distribucijo, zaupanja vredne izdelke in merljivo vrednost – ne le v večje predstavitve.

Bistvo (en stavek)

Umetna inteligenca je resničen premik platforme, vendar se trg obnaša kot mehurček; zmagovalci bodo podjetja, ki bodo umetno inteligenco spremenila v zaupanja vredno, merljivo vrednost, hkrati pa preživela pretres.

Viri

Document Title
Cisco CEO warns the AI boom looks like a bubble — but says AI will be bigger than the internet
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
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Climate
Cisco CEO on the AI ‘bubble’: why the crash can still leave winners
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Technology
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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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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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