AI search feels great right now. That won't last.
As AI search gets monetized, it's creating a messier internet around it.
Like it or not, AI search is being forced upon us.
This is happening everywhere: whether it be in traditional search engines like Google, Bing and even DuckDuckGo, or if you're going straight to the Gen AI platform of choice (your ChatGPTs, your Claudes, or your Geminis, for example), there is a steady shift taking place that is moving us away from "search engines" and pushing us toward "answer engines."
And it’s working pretty well. According to McKinsey, around 50% of consumers now actively opt for AI-powered search engines.
The appeal is straightforward: ask a question, get an answer. No sponsored results clogging the top of the page. No screen-filling widgets. No "people also asked" dropdowns. Just the information you were looking for.
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Is AI Search destined to degrade in quality like so many online platforms before it?
(Image: CTech)
After years of traditional search engines prioritizing ads and ecosystem retention over direct answers, AI search offers something refreshingly simple.
But it's worth asking how long this simplicity will last.
The enshittification process
There's a term that's been making the rounds in tech circles: enshittification. Coined by author Cory Doctorow, it refers to a common pattern in online platforms: attract users with good service, then gradually shift focus toward business interests, and eventually optimize primarily for revenue rather than user experience.
Facebook is a textbook example: it started with a clean, friend-centric feed, then prioritized business content and ads, and eventually optimized the entire system around engagement metrics and ad revenue, even when that meant a worse experience for both users and businesses.
Google has been following a similar trajectory. The rise of sponsored search results, the increased prominence of widgets and dropdowns, the general sense that search is designed to keep you searching rather than find what you need and leave. These aren't accidents, they're business decisions.
AI search currently sits at the beginning of this cycle. It's genuinely useful, and users are responding. But the economic realities that shaped Facebook and Google haven't disappeared. Platforms need revenue. Businesses need visibility. The question isn't whether AI search will be monetized, but how that monetization will unfold and what trade-offs will come with it.
Monetization takes shape
For businesses, the shift to AI search has required significant adaptation. Traditional SEO strategies don't necessarily apply when users aren't clicking through lists of links. The usual pathways to visibility have changed.
“At first there were a lot of question marks, a lot of panic; nobody knew where it was going, in terms of advertisements in this new ecosystem. But now, there is direction,” says Tomer Fuss, the Chief Product Officer at Natural Intelligence.
Natural Intelligence is a company that’s at the forefront of online advertising. They work very closely with industry giants like Google and Microsoft to develop the top strategies for getting clients’ marketing materials in front of online consumers, including via search results.
Fuss explains that what companies are figuring out is a new advertising model designed for AI-driven results: personalized ads that can be generated at runtime and integrated more naturally into AI responses.
He describes a scenario where a user searching for insurance information doesn't just get an AI summary with a link to a company's website. Instead, the ad opens a dialogue, gathers context about the user's specific situation, and generates a personalized quote on the spot, all within the AI's response.
This represents a clear evolution in how advertising will work within AI search. These aren't the blunt-force banner ads of the early web. They're more sophisticated, potentially more useful. But they do mark the beginning of commercial interests finding their way into what started as a cleaner experience.
And they’re bringing it soon. Natural Intelligence is already working on integrating “agentic ads” into major AI platforms to herald “ a new era of ads that are agentic and are doing much more than just showing an ad, but helping consumers get personalized offerings.”
The social media spillover
There's another shift happening simultaneously. As businesses try to optimize for AI search visibility, they're discovering that AI systems are increasingly pulling from social media content.
Daniel Kushner, CEO of social media management platform Oktopost, puts it simply: "A lot of results are coming from social media."
It’s commonplace to see AI search sources referring to Reddit, LinkedIn and other social media sites, and it’s for this reason that Kushner believes that companies should aggressively target social media feeds if they want to show up in answer engine results.
This creates an interesting balancing act: a company needs to have widespread presence on social media so that it can get referenced by AI search engines and end up in front of AI searchers, but at the same time the company needs to make sure that it doesn’t annoy and scare away its actual social media followers by clogging up their feeds with 100 promotional posts a day.
So what’s a company supposed to do?
“That's where the power of the employees comes into play,” Kushner explains. “If I’m an organization with 2,000 employees, let me empower those employees to post corporate relevant content onto their personal LinkedIn profiles, so it's not just one company posting to one company page - it’s now something like 500 employees posting on their personal LinkedIn profiles. And if each person is posting one post a day, five days a week. That's two and a half thousand additional LinkedIn posts that have my messaging, my branding, my positioning, which is now the new fuel for the AI search engines and LLMs.”
Kushner calls this solution "employee advocacy”; a system wherein companies incentivize their employees to post about the company they work for on their personal social media accounts.
In order to turn this idea into a scalable solution for their customers, Oktopost intends to launch AI employee advocacy agents in the first quarter of the new year. These agents will generate post templates, distribute them to employees, and track performance through gamification, including point allocation and a leaderboard system.
Collateral damage
From a business perspective, this makes sense. But it does raise questions about what happens when this becomes widespread practice.
If many companies adopt similar systems, social media feeds will naturally see more corporate-adjacent content. Much of it will be AI-generated, approved quickly by employees, and optimized more for search visibility than actual human engagement. Personal posts, human-generated creative content, and organic conversations will be fighting for space against a flood of promotional material.
It's not that any individual company is doing something wildly unreasonable - everybody’s just out to make money in a rapidly-changing tech landscape. But the aggregate effect will shift what social media feels like, particularly for users who are there primarily to follow people rather than brands.
Kushner himself is the first to point out that the automation of social media will cause harm.
“Automation is going to do a lot of harm, whether it’s for news outlets, for social… Good content has always been a supply and demand game, and when the supply is unlimited the value basically plummets,” he admits.
But Kushner believes that at the end of the day, authentic content has a way of rising to the top.
“ There's going to be way, way more noise when it comes to content,” he says. “And that's where the authenticity stands out. When a salesperson is sharing a personal experience that he went through, that can't be done through AI. And those pieces of content are what's going to stand out in the future.”
Changing our minds
Right now, AI search offers some genuine advantages over traditional search engines. The experience is cleaner, faster, and more direct. But it’s creating new pressures on the spaces around it, and those pressures seem to favor automation and scale over authenticity and informality.
Those are structural concerns about the internet's evolution. But there's a more personal trade-off worth considering too.
As we rely more heavily upon AI answer engines, it may interfere with our ability to question the information put in front of us. If that’s the case, we're not just automating content, we're automated consumption.
And in the age of deep fakes and LLMs, it’s hard to think of a worse time for that to happen.
