In a world racing towards AI supremacy, the elephant in the room isn’t moving. Last week’s federal ruling confirming Google’s monopoly in search isn’t just a legal footnote – it’s a stark revelation of the invisible force holding back the AI revolution we’ve all been promised.
While tech pundits have been breathlessly predicting the AI-powered transformation of search, the reality has been a slow, cautious crawl. But here’s the twist: Google’s sluggish pace isn’t just about technical challenges or cost concerns. In the context of monopoly power, you have to see this as a strategy of a monopoly that has no real incentive to disrupt its own golden goose.
This isn’t another rehash of Google’s market dominance. It’s an exploration of how that dominance is quietly shaping – and potentially stifling – the future of AI in search. As we peel back the layers, we’ll uncover how Google’s monopoly status is creating a paradox: the company best positioned to revolutionize search might be the least motivated to do so.
From internal documents revealing Google’s true motives to the surprising innovations of scrappy competitors, we’re about to dive into the hidden dynamics that are molding the future of how we find information online. Buckle up – this journey might challenge everything you thought you knew about the race for AI-powered search.
Google’s AI strategy and innovation
In our May 2024 article, we predicted a seismic shift in Google’s search landscape. We anticipated that within 12–24 months, Google would start generating AI-powered featured snippets for most search queries, fundamentally changing how we find and consume information online.
We’re still on track for this timeline. Google’s rollout of AI features has been cautious and limited. This cautious approach aligns with our prediction that any AI rollout would be “basic” to keep costs down, but the pace has been even slower than anticipated.
At the heart of this slower-than-expected progress lies a complex web of factors. Cost constraints continue to play a significant role, just as we predicted. Google executives have continued to cite the need to control costs, noting they’re “spending a ton more on machines” due to generative AI. Pair that with increased market skittishness about the billions of dollars being spent on genAI and it’s a tough combination.
Google’s position as the dominant search engine creates a paradox that further explains this cautious approach. Without significant competition, there’s less pressure to implement radical changes quickly. Rapid, transformative changes risk disrupting a highly profitable status quo. This situation contrasts sharply with newer, AI-focused search engines like Perplexity, which offer pretty good AI features for a fee.
We originally saw this as a simple innovation game. Once you throw monopoly power in here, the dynamics shift significantly. Google’s cautious approach isn’t just about managing costs or technical challenges; it’s also about maintaining market dominance. This monopoly status allows Google to innovate at its own pace. There’s still no answer to the question of how Google will make money with genAI results. It now seems more reasonable to see this as a balancing act between innovation and control.
Generative AI in search: Google vs. competitors
While Google cautiously navigates the integration of generative AI into its search engine, competitors are pushing forward with more aggressive implementations. This contrast provides valuable insights into the potential future of search and the challenges that lie ahead.
Take, for instance, Perplexity, a newer search engine that has embraced AI-powered responses. Perplexity does have a limited free plan, but its Pro option costs a huge $20/month. Whilst Google executives have floated the idea of paying for Google, this is surely impossible for the core product. But, unrestrained by the need to control costs, Perplexity can offer a really very good product experience.
The implementation of generative AI in search isn’t just about providing answers; it’s about the quality and usefulness of those answers. My wife’s reaction to her first encounter with a genAI answer in search results was telling: “How do I turn this off?” And, indeed, the high-profile and embarrassing examples of Google’s genAI answers suggesting users should eat rocks show the challenge of the always-on, un-dismissible genAI response.
Kagi, another newer search engine, offers an interesting middle ground with its “Quick Answer” feature. This opt-in approach generates AI responses based on top search results when requested by the user. It’s a solution that respects user choice and solves the challenge of knowing when to trigger the genAI response by delegating this to the user.
For specific queries requiring objective answers, like “How many grams of coffee should be in my new dripper?”, this approach is great. I use it a lot and like it. For anything more complex, it’s obviously not suitable, but it’s also not trying to deliver on that.
Google’s challenge lies in finding a way to implement generative AI that enhances rather than disrupts the search experience. The company is playing on hard mode by insisting on showing generated answers for specific queries by default. An opt-in model like Kagi’s could provide a smoother transition, allowing users to become accustomed to AI-generated responses at their own pace.
Google’s long-term strategy: lessons from internal documents
While Google’s cautious approach to AI in search might seem puzzling, recently unsealed internal documents from 2017 offer revealing insights into the company’s long-term strategy. These documents, related to Google’s online advertising efforts, expose a pattern of behavior that sheds light on the company’s current AI tactics.
A key revelation is Google’s relentless focus on data acquisition. Take the Accelerated Mobile Pages (AMP) project, for instance. Publicly touted as a way to improve mobile web performance, internal documents suggest a different primary motivation:
“When Google is serving AMP from Search or News, we cache a copy of the content on our servers, which gives us the opportunity to treat ads on cached AMP as another O&O [owned and operated] property, with O&O-level access to Google consumer data.”
This strategy of turning the open web into Google-owned and operated properties mirrors the company’s current approach to AI in search. Just as AMP was used to gather more data and serve more ads, Google’s slow AI rollout could be seen as a way to maintain control over the search ecosystem and the valuable data it generates.
Moreover, these documents reveal how Google has historically used its search dominance as leverage to push the adoption of other technologies. This pattern suggests that Google’s current AI strategy isn’t just about technical challenges or costs – it’s about maintaining and extending its monopoly power.
By connecting these past behaviors to Google’s current AI approach, we can see a consistent strategy: cautious innovation that prioritizes data control and market dominance over rapid transformation. This insight helps explain why Google, despite its vast resources and technical capabilities, isn’t leading the charge in AI-powered search.
The future of search: a monopoly’s dilemma
As we stand at the crossroads of AI and search, the implications of Google’s monopoly loom larger than ever. The tech giant’s cautious dance with AI isn’t just a business strategy – it’s a glimpse into a future where innovation and market dominance are locked in a complex tango.
Google’s monopoly has created a paradoxical landscape. On one hand, the company possesses unparalleled resources and data to revolutionize search with AI. On the other hand, its very dominance acts as a brake on rapid transformation.
The rise of AI-focused competitors like Perplexity and Kagi is a testament to the innovation vacuum created by Google’s monopoly. You understand this isn’t a dichotomy: these are innovators, but they’re also small, niche, and expensive. I like Kagi but I don’t see it as a mainstream product. Their success – or failure – will be a litmus test for the health of a search ecosystem that a judge ruled to be a monopoly.
For businesses and SEO professionals, the message is clear: diversification is key. While Google remains the dominant player, the search landscape is more dynamic than it has been in years. Ignoring emerging AI-powered platforms could mean missing out on the next big shift in discovery. We’re working on this for our clients.
Regulators and policymakers face an equally daunting challenge. How do you foster innovation in a market dominated by a single player? The outcome of current antitrust efforts against Google could reshape the open web for decades to come.
Ultimately, the future of search hangs in the balance. Will Google’s monopoly continue to slow-walk us into the AI era, or will external pressures force a more rapid evolution? The next chapter in the story of search is being written now.
