In 2023, I wrote about a provocative “what if”: What if Google added an AI chatbot to Search, effectively cannibalizing itself?
Fast-forward to 2025, and it’s no longer hypothetical.
With AI Overviews (AIOs) and AI Mode, Google has not only eaten into its own search product, but it has also taken a big bite out of publishers, too.
Cannibalization is usually framed as a risk. But in the right circumstances, it can be a growth driver-or even a survival tactic.
In today’s Memo, I’m revisiting product cannibalization through a fresh AI-era lens, including:
- What cannibalization really is (and why it’s not always bad).
- Iconic examples from Netflix, Apple, Amazon, Google, and Instagram.
- How Google’s AI shift meets the definition of self-cannibalization – and where it doesn’t.
- The four big marketing implications if your brand cannibalizes itself in the AI-boom landscape (for premium subscribers).
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Today’s Memo is an updated version of my previous guide on product cannibalization.
Previously, I wrote about how adding an AI chatbot to Google Search would mean that Google would be cannibalizing itself – which only a few companies in history have successfully accomplished.
In this updated Memo, I’ll walk you through successful product cannibalization examples while we revisit how Google has cannibalized itself through a refreshed lens.
Because … Google has effectively cannibalized itself with the incorporation of AI Overviews (AIOs) and AI Mode, but they haven’t found a way to monetize them yet.
And publishers and brands are suffering as a result.
So who wins here? (Does anyone?) Only time will tell.
Product cannibalization is the replacement of a product with a new one from the same company, typically expressed in sales revenue.
Even though most definitions say that cannibalization occurs when revenue is flat while two products trade market share, there are a number of examples that show revenue can grow as a result of cannibalization.
Product cannibalization, or market cannibalization, is often seen as something bad – but it can be good or even necessary.
Let’s consider a few examples of product cannibalization you’re likely already familiar with:
- Hardware.
- Retail.
- SaaS/Tech.
Hardware companies, for example, need to bring out better and newer chips on a regular basis. The lifecycle of AI training chips is often less than a year because new architectures and higher processing capabilities quickly make the previous generation obsolete.
Right now, chips are the hottest commodity in tech – companies building and training AI models need them in massive quantities, and as soon as the next generation is released, the old one loses most of its value.
As a result, chipmakers are forced to cannibalize their own products, advancing designs to stay competitive not only with rival manufacturers but also with their…
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