I’ve always been fascinated by how Google Search has driven innovation by rewarding high-quality content with visibility and traffic. In the last article, I explored the risks of Google AI over-personalizing results and reinforcing filter bubbles.
This time, I’m examining a different concern. If Google’s new AI results lean toward uniformity, favoring big brands and consensus views, it might stifle creativity and innovation, while speeding up the web’s commodification.
Some might think this worry is naive, as the internet is largely commodified. Historically, however, small websites believed they had a shot at ranking and driving traffic. The internet has been perceived as a vast digital marketplace of ideas. But with AI models seeking consensus, appearing in AI search when you diverge from mainstream could become challenging.
AI systems & consensus
Consider the companies that lost all their traffic and rankings in the Helpful Content Updates. Small affiliate sites, which added valuable content through product reviews and comparisons, were mostly eliminated from organic rankings.
To gain traffic via Google, these companies now resort to buying ads or leveraging platforms like TikTok and Instagram. Most choose the latter, abandoning efforts to rank in Google entirely. Not all sites losing visibility lacked editorial quality—some offered high-value, human-focused content.
The core issue is that if these companies vanish, the diversity of information indexed by Google—and now utilized in AI search—becomes limited. Prodding smaller publishers to migrate to social platforms could further diminish web diversity. If independent creators face consistent exclusion from rankings, their drive to share unique perspectives might dwindle.
Social media could serve as a counterbalance in Google’s strategy, which is somewhat promising. Google recently decided to rank YouTube Shorts within Discover, and has a ‘Short Video’ tab on many results. It’s also showing increased interest in posts from Reddit and LinkedIn. Maybe, in Google’s perspective, unique opinions should emerge from independent creators, while mainstream views stem from larger brands. Only time will reveal the truth.
The impact of advertising
Ads in AI Overviews are already appearing, giving us a glimpse into Google’s monetization plans for AI. Meanwhile, we can analyze how Google has altered ads and ecommerce to accommodate AI.
The move to Performance Max (PMAX) bidding in Google Ads has perplexed many advertisers. Its opaque system limits control and data visibility, potentially making advertisers complacent as Google assures better returns with reduced effort. However, what happens if advertisers wish to understand their audience deeply?
When Google manages PMAX bidding without disclosing what works, it learns about your customers using your resources without sharing insights. This deprives you of applying these learnings across other advertising channels. In some sectors, Google might learn enough to bypass you with customers, similar to Google Travel integrating Flights, Hotels, and more. Truly, AI is a double-edged sword.
This tactic could extend to Google Merchant Center. By pooling retailer data, Google refines PMAX campaigns, delivering precise ads at ideal times, boosting conversion, and using AI tools like Circle to Search and Google Lens.
Google’s aggressiveness in promoting its ad options strikes me distinctly. I encountered an ad via a full-screen takeover on an organic SERP—a rarity for Google whose full-screen takeovers usually signal terms changes or opt-ins.
Recent Terms and Conditions underline Google’s user data sharing across Alphabet properties to personalize advertising. This sharing combines with modeled data to fine-tune targeting on both micro and macro levels.
It seems Google will continue this path unless opposed. Google’s vast market share limits alternatives for searchers, publishers, and advertisers, offering them few escape options. This enables Google to prioritize monetized AI results over organic traffic, though adjusted ad labeling might blur distinctions further.
The updated Terms and Conditions, shown to EU users, emphasize Google’s data use across platforms. Including Google Ad services in the update illustrates their reach through our ad data, indicating how advertisers fund Google’s platform enhancements, despite limited data access.
So what can we do to protect the health of the internet?
I’m captivated by AI’s potential, often diving in with reckless excitement. I confess to leaning towards “AI doomism,” believing negative scenarios are more probable due to our tendencies and lack of oversight.
Once technology manifests, it cannot be undone, particularly online, where it is ever rememberable. Human memory is flawed, but the internet remembers, so the AI genie is now out of the bottle.
So, how do we prepare for AI’s future and craft frameworks, guidelines, and rules preserving internet health while fostering AI innovation? How do we allow diverse content discoveries without stifling AI progress?
I believe in collaboration between digital marketing and publishing industries, which are already uniting to protect copyright interests. Operating separately won’t generate internet-protecting measures on either side.
Until solid AI regulations are created and enforced, setting collective, collaborative internet protection standards surpasses individual interests. Like unionized workers defend against exploitation by powerful companies, we need collective bargaining and protection.
Some EU movements aim for broader digital and AI regulation, but digital marketing and SEO might benefit from self-developed, community-enforced standards, moving beyond “black hat” or “white hat” labels, especially for AI. It’s a dialogue worth pursuing.
Inspired by this post on Search Engine Land.
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