In 2023, ChatGPT was widely used for SEO. Using AI to generate content became one of ChatGPT’s main selling points, as it significantly saved editors’ time. What used to require a team of 5 editors was reduced to just one person with the help of ChatGPT. Before this, there were many content rewriting tools, like contents scrapers, which typically charged $99/month and had over 10,000 subscribers conservatively estimated.
Because tools like contents scrapers tend to produce content with very poor readability when configured to have less than 30% duplication, they were often used in black-hat SEO. ChatGPT, on the other hand, used AI for content rewriting, which allowed it to understand and rewrite based on multiple inputs. Combined with its free strategy, it wiped out the entire market for content scrapers.
Since ChatGPT is an AI, many users discovered it could answer a wide range of questions. Some people started experimenting with using ChatGPT to design research models and write papers. In less than six months, ChatGPT caused a 25% drop in search engine traffic. This was far more efficient than users manually browsing websites via search engines.
Bold Prediction: Search engines will become fully AI-driven within three years.
In 2024, search engines began partially integrating AI. By 2025, they had become AI-powered.
By 2026, it’s estimated that search engines will no longer look like they do today. The results shown by AI-driven search engines are what we now call AIEO.
The AI transformation of search engines has fundamentally changed how results are delivered. Originally, users had to browse multiple sites and summarize on their own. Now, search engines understand the user’s search behavior and directly output results.
AIEO refers to AI-powered search result optimization — the outcome of AI-integrated search engines.
If a website’s content lacks differentiation, its links won’t be indexed by AI.
Traditional SEO relied on 1) writing massive amounts of website content, and 2) building backlinks — these two actions were key to ranking in search.
The role of the search engine has shifted from “webpage ranking” to “understanding user queries and directly providing results.”
Search engines *are* a form of AI. The main reason they don’t fully switch to AI-based result displays is that understanding user queries and generating answers consumes computational power. With tens of billions of searches per day, that means tens of billions of queries — which would drastically reduce company profits.
To answer this, we need to go back to the years 2000–2005.
The main entry point to internet traffic was portals like Yahoo. Yahoo SEO was very easy before 2004 — just registering a keyword domain would land that keyword on the first page of Yahoo’s local search. Companies that entered the internet early profited significantly from this trend.
However, this also led to Yahoo’s search results being filled with all kinds of questionable and inappropriate website content.
Google made two major improvements over Yahoo:
1. Switching from manually curated content to automatic crawling.
2. Implementing algorithms to analyze and rank search results.
As a result, Google indexed 10 times more content than Yahoo — even indexing content at a rate 10 times higher daily. Users began to switch en masse to Google.
Traditional industries moved online mainly via Google Ads. SEO competition increased year by year, and search engines continually upgraded their algorithms to prevent SEO manipulation.
In both the first and second phases, it took most companies five years to go from accepting internet search engines to actively using them and transforming their customer acquisition models.
The previous stage helped companies move from traditional business models into the digital realm. Phase Three is pushing them to transform again:
1. Companies are shifting from selling products and services to becoming knowledge providers. The focus becomes: *What problems do your products or services solve?* Search has moved from keywords to answering questions.
2. Industry knowledge gateways will be monopolized by platform-level enterprises — because search engine AIs still have shortcomings in niche areas.
3. Search engine services will evolve into household AI robots and AI compute leasing platforms.
The logical outcome of Phase Three:
The core of SEO competition in Phase Two was content and internet marketing. To succeed during that phase:
1. You needed to produce more content than competitors to cover more keywords.
2. You had to invest heavily in online marketing, ensuring all sites could include links that could be indexed by search engines.
Therefore, content and products/services must be separated, and
web presentation must prioritize content, while
selling products or encouraging users to use services should come second.
Take the exchange Coinbase as an example: when you visit the Coinbase website, you don’t immediately see traditional trading candlestick charts. Instead, there is a large amount of written content.
In contrast, many other exchanges feature tools and functionality on the homepage, using content only as a traffic funnel. These sites expect users — who may not even trust the product or service yet — to immediately start using it upon first visit.
The important role of a website — an information provider. Push sales directly contradict the original intent of search engines. The essence of a search engine is to help users quickly find answers, which means that at its core, a search engine is also AI.
With search engines becoming fully AI-driven, the need to “quickly find answers” becomes even more prominent. This means that before businesses even figure out how to present their information, they already face the challenge of upgrading to submitting knowledge to the search engine AI. — To continue getting traffic from AI, businesses are inevitably being forced to shift into the role of a knowledge provider.
There are two main weaknesses in AI-generated search results:
This can’t be done by a simple product website. It requires a comprehensive knowledge-based website — an industry-level AI.
For websites with only a small number of products or services, they still need to capture traffic. The only option is — to adopt existing AI frameworks and rent computing power.
If small and medium-sized businesses continue using outdated SEO mindsets to manipulate search AI answers, they will be eliminated in the next 2 years. If customer acquisition costs can’t go down, they’ll only increase. And if they still use outdated thinking to apply AI tools for SEO, there is no future — it’s just burning money.
| Aspect | AIEO | Google SEO |
| Result Display | Understands the user’s query and outputs an answer | Website ranking |
| On-site Algorithms | Structured SEO language Summarized content in sections Logical flow and readability Content uniqueness Registered trademark information |
Involves over 200 factors, including: Meta titles and descriptions Academic-style structure Volume of content (number of URLs) Indexing frequency Bounce rate Google Business submission |
| Optimization Goal | Feed data to AI. Gain traffic from data source links | Boost keyword rankings on websites |
| Keyword Length | Over 20 words | Average of 4 words |
| Measurement Metrics | Whether AI remembers the content Number of data source links indexed by AI |
Website click-through rate |
As of the time of writing (July 8, 2025), over 90% of SEO agencies and freelancers are still only using AI to assist in SEO — and have not abandoned traditional SEO strategies.
Rather than asking what AIEO’s business model is, it’s more accurate to ask how regular businesses can survive in the midst of this environmental transformation. In summary, there are only two ways to survive:
Businesses no longer need traditional SEO to boost website rankings — because it no longer matters. What they need is AIEO: to turn their websites into AI-friendly knowledge hubs, and to present products and services *after* AI-driven content. If the budget allows, there are less than two years to either become a leader — or be completely eliminated.
SEO already requires a broad knowledge base, including: marketing, HTML, UX, and PHP. You don’t need to be an expert in all, but at least capable of understanding and applying them. AIEO builds on this foundation by adding AI models to the mix.
A common misconception is that hiring experts in those fields will enable a business to implement AIEO. The reality is the opposite: specialists in those areas are often too focused to balance across disciplines. This imbalance can cause a disconnection between the AI in search engines and the company’s own AI — especially when companies forget that the true essence of industry AI is to *monopolize the knowledge gateway* within a niche sector.
The worst-case example is the contrast between Coinbase and typical exchanges. While websites now need to be fully AI-powered on the homepage, some still cling to the outdated “must showcase product and service first” mentality from the early days of the internet.
GEO stands for **Generative Engine Optimization** — it shares the same concept as AIEO. The term appears to have been coined by A16Z (Andreessen Horowitz), the famous investment firm that gained prominence through its focus on Web3. Much like how ChatGPT first gained traction in China, GEO also originated in China. However, Google has not embraced the term, likely because “SEO” was coined by Google itself — and Google wouldn’t want another company setting the standards it believes it should define.
Just like with SEO, Google will likely come up with its own terminology and a complete set of guidelines to instruct site owners on how to feed data to the search engine’s AI. Whether that term will be AIEO remains to be seen.
It seems I said long ago — around 2015 — that SEO companies had no future. At the time, the reasoning was that SEO companies were inefficient and full of tricks. Ten years have passed, and many SEO firms are still doing well.
But with search engines becoming AI-driven, the evolution that took 10 years may now happen in just 2 years — because of massive efficiency gains. So my pessimistic view of SEO companies still stands, but the reason has changed.
Where should SEO companies go from here?
They should transition into helping businesses make their websites AI-compatible, or pivot into becoming advertising agencies.
In the Yahoo era, not having a website meant missing out on the internet.
In the Google era, not knowing SEO meant burning cash for traffic.
In the AI era, not having AI and not doing AIEO means **handing your business over to your competitors**.