Google is the new IBM

In the same way IBM lost its edge during the rise of personal computing, Google risks becoming obsolete by failing to pivot fast enough in the face of the generative AI.

The rise of LLMs has exposed structural weaknesses in Google's innovation model, and if it doesn't act decisively, it may cede its long held dominance in search and advertising.

Legacy Business Model Anchoring Innovation

Google's overwhelming reliance on its ad driven search engine parallels IBM’s reliance on mainframes in the '80s.
Just as IBM hesitated to embrace PCs out of fear they’d cannibalize its profitable mainframe business, Google appears hesitant to fully embrace LLM-powered search because it undermines its current ad model.

IBM's trap: Holding onto mainframes, failing to dominate the PC market.
Google's trap: Clinging to "10 blue links" and ads, delaying true AI-first search experiences, that is to say a more precise and interactive search experience.

LLMs threaten Google's search monopoly

OpenAI’s ChatGPT and other LLM based tools deliver answers directly, bypassing the traditional Google search experience. This is fundamentally disruptive, you will find this especially true if you are trying to find out technical information and solutions.

LLMs collapse the information seeking process from multiple clicks to ONE interaction.

Users are shifting from “searching” to “asking,” a paradigm that weakens Google’s value prop.

New LLM players are moving fast — Google is moving cautiously.

Internal dysfunction and innovation paralysis

Like IBM before it, Google has become a massive bureaucracy, risk-averse, slow-moving, and gasp siloed.

Google has been working on LLMs (like LaMDA -> PaLM -> PaLM2 -> Gemini) for years but failed to bring them to market in a compelling way before OpenAI's ChatGPT.

Think of the internal politics and turf wars between DeepMind, Google Brain, and other divisions, this mirror IBM’s infamous internal struggles.

Bard, Gemini, NotebookLM launches have been underwhelming at best, plagued by errors and branding confusion, essentially we're just throwing ideas on to the wall and hope it sticks.

Talent drain and the rise of leaner competitors

In the same way IBM lost key talent to Microsoft and others, Google is seeing top AI researchers and engineers leave for OpenAI, Anthropic, and other startups.

The culture of experimentation and bold thinking that once defined Google has faded, this is no longer the Google imagined and ran by engineers, its ran by sales people.

Smaller teams outside Google are building more agile, focused, and rapidly evolving LLM products, we're always one step behind others when it comes to these LLM products. Just look at the recent news of agents vs what was already on the market.

The AI platform shift is Google’s “PC moment” and we're already behind the curve.

In the '80s, IBM let Microsoft control the software layer. Today, Google risks letting OpenAI (with Microsoft’s backing) define the AI interface layer of the future.

If any of the LLM models manage to become the new gateway to the internet, it will replace Google’s role.

And its obvious, Google is reacting instead of leading, a classic sign of decline.

~History doesn’t repeat, but it rhymes~
Google isn’t going away tomorrow, just like IBM didn’t disappear in the '90s. But the signs are there: platform disruption, internal inertia, and rising challengers. The rise of LLMs is a paradigm shift as big as the PC or the internet itself.

If Google doesn’t radically restructure and lead the charge, it risks becoming another IBM: still rich, still relevant in some domains, but no longer the driving force of the tech industry.

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