Editorial
The Gist
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The rise of AI search. AI-powered search engines are reshaping traditional search and offering more organized and relevant results.
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Google’s dominance. Despite the rise of AI search, Google remains dominant with its vast data advantage, making it difficult for competitors to catch up.
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SEO shifts ahead. As AI-powered search engines evolve, SEO strategies must adapt, focusing on user intent rather than traditional keyword strategies.
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Will AI replace search? These AI platforms are changing the capabilities of search, but it's uncertain if they can take over established search platforms.
Search has had a good run. It’s been the ultimate cash cow for decades. But will AI kill traditional search as we know it?
Google's search algorithm has been in use since the launch of Google's search engine on September 4, 1998. Google handles more than 8.5 billion search queries on a daily basis, and there are approximately 6.3 million searches conducted on Google every minute.
The original algorithm, called PageRank, was created by Google founders Larry Page and Sergey Brin. PageRank ranked search results based on the number and quality of links to a page. PageRank operated "by counting the number and quality of links to a page to determine a rough estimate of how important the website is.” The underlying assumption was that more important websites were likely to receive more links from other websites.
This changed the way people would use the internet forever.
As generative AI platforms begin to launch their own AI-powered search engines, every major search engine — including Alphabet’s Google, Microsoft’s Bing and Baidu in China — are scrambling to add their own generative AI capabilities to their search platform to avoid disruption.
Will this be enough to preserve the monopoly search has had on the internet? Will these tools remain separate or converge over time? And what does this mean for marketers?
Google’s Rise to the Top
Google Wasn’t the First
Early on, many companies were in the search game, including Archie, Lycos, AskJeeves, WebCrawler, Yahoo, Infoseek, AltaVista and others. These first search engines were pretty basic and were frequently simple directories of websites that were split into topic categories, allowing users to source information they required from relevant websites. This worked fine when the internet was a small community of servers, but when it grew, it became harder to manually index information. Automated web crawlers were introduced, capable of scanning an entire web page and indexing its content for search engine users.
The decades that followed saw search engines become more sophisticated, with a focus on optimizing search results for relevance and speed. Users could now receive millions of results for a query within a split second, which has led to our reliance on search engines today. Mobile devices quickly became the primary device used to access the internet and forced the creation of responsive websites. As algorithms evolved, new disciplines like SEO, search engine marketing and advertising emerged. This ultimately led to the creation of a global $980 billion advertising market dominated today by Google.
Why Did Google Win?
It’s not just one capability that catapulted Google to success; it was a series of deliberate choices. Most important was relevance and speed. The platform had high performance and produced relevant search results very quickly. Google also indexed more web pages, and therefore it had more search results than any other search platform.
Google also focused on simplicity. Its interface was minimalistic and clean with a simple search box on a web page. All other search engines had very cluttered interfaces with banner ads and other distractions.
Why Hasn’t Anyone Caught Up to Google?
For starters, Google's main focus as a company has been to build the best search engine in the world. Focus and investment can drive amazing market results.
Google also benefits from a data advantage. Most search engine algorithms rely on past user data to power their algorithms. Because of Google’s market share, they consistently had five to six times the data to analyze and use for its algorithms. All things being equal, bigger and better data wins over better algorithms. This means even if a search platform uses the exact same algorithms as Google, they will still not perform as well because of less data.
Lastly, Google was the first to understand what customers truly wanted. They continued to evolve and innovate the search engine experience by introducing new features like RankBrain to improve relevance, Mobilegeddon to encourage mobile-friendly websites, Possum to attack local spam sites, Hummingbird to understand human intent, and BERT and the Multitask Unified Model (MUM) to understand complex search queries.
These innovations have made it difficult for other search competitors to scale.
Related Link: Google vs. SearchGPT: What Marketers Need to Know
Google’s Competition Has Struggled to Compete
Building Search Engines Is Hard
Big companies like Microsoft have put significant investments into their search platform Bing, and they still have under 10% market share. Meanwhile, between 2014 and 2024, Google has maintained an average 85% market share in search.
Startups Have Also Struggled to Compete
Some startups have been trying for years. DuckDuckGo is an internet search engine founded by Gabriel Weinberg in 2008. It made a brand around protecting user privacy. They don’t collect or store your personal information, and they don’t target you with ads. Its default setting is private. It comes with over a dozen powerful privacy protections built-in and doesn't track search history. They have managed to survive and service over 3 billion searches a month; they even turned a profit in 2014. However, they have struggled to get more than 1% in market share.
More recently, Neeva — an ad-free search engine that focused on protecting user privacy and avoiding bias — gained early momentum but had to shut down in June 2023.
Neeva set out to be an ad-free environment through a paid subscription model. Instead of having to scroll through numerous sponsored results to get to relevant links, Neeva delivered what it deemed to be the most relevant results at the top of the page.
Another selling point was the ability to filter out specific information sources. For example, if you didn’t want to buy from Amazon, you can tell Neeva to not include it in future results.
Traditional search engine experiences are cluttered with ads, pop-ups and algorithm-optimized content. When your business model relies on ad-based revenue, it’s hard to maintain purity as the information portal to the web. The signature “10 blue links” are so buried in advertisements that it consumes many cycles to get to valuable content, and it creates a frustrating user experience in the process.
However, this was not enough to sway a user base from traditional search engines.
Neeva founder Sridhar Ramaswamy, who worked at Google for 16 years and ran its ad business, finally recognized that, “It’s one thing to build a search engine and an entirely different thing to convince regular users of the need to switch to a better choice.”
AI-Powered Search Engines Transforming the Search Landscape
AI is now changing the search game, most likely forever.
It’s not surprising that OpenAI entered the search engine game. They already had a partnership with Bing, and it was only a matter of time before they went after Google.
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SearchGPT is OpenAI’s prototype search engine launched in July 2024. And OpenAI officially rolled out ChatGPT Search late last month. This much-anticipated feature provides more organized and meaningful search results by summarizing and contextualizing information rather than returning lists of links. SearchGPT is trying to improve user experience, introducing new paradigms like the sidebar which provides more links relevant to the search query. OpenAI unified the SearchGPT to the ChatGPT interface.
Maybe the future of web searching lies in a hybrid between traditional search and AI search. For example, Perplexity was founded in August 2022, and it offers a different kind of experience when browsing the web. It offers a web search alternative using AI-powered research coupled with a custom search engine to generate more precise answers to queries.
Perplexity is powered by several large language models (LLMs), blending foundational LLMs with proprietary ones. The paid version offers access to many models, including GPT, Sonar Lage and Claude versions. Perplexity integrates a web crawler with LLMs using its own web crawler, PerplexityBot. Perplexity can therefore perform two core functions, both acting as a search engine and generating original content.
Perplexity’s strength is in complex queries that would require a lot of navigation and summarization. Perplexity focuses on speed and accuracy, with the goal of making people save time, compared to Google where you quickly get a results list but need to spend time to find the right answer.
Perplexity really shines with LLM-friendly queries such as “how-to guides,” complex summarization and complex questioning. When you ask a question, Perplexity doesn’t give you back a list of links. Instead, it scours the web for you and uses AI to write a summary of what it finds. These answers are annotated with links to the sources the AI used, which also appear in a panel above the response. These source links are invaluable for fact-checking and academic research, ensuring credibility and easy verification
Related Article: Marketers: What's Your AI-Powered Search Strategy?
Search Is About More Than Just Getting Answers
While AI-powered search engines may certainly be better at summarizing information related to specific research queries, it’s not necessarily able to perform all the functions of today’s search engines.
Google is much more than just a research tool. For many, it’s the portal to the internet. For instance, if customers want to go to their bank’s website, they’ll frequently bring up Google and type their bank name rather than entering the name of the bank URL into the browser. When you do a navigational Google search like this, it’s exceedingly rare that the first result isn’t what you’re looking for.
AI-powered search engines are not very good at navigational queries. They like to think for a few seconds and then provide a stream of information about the company when all you want is a link.
Traditional search also excels at real-time information like “today’s weather,” “NFL scores” and “current time in London.” Google presents accurate information quickly, but AI search takes a few seconds and can sometimes give outdated information like last night’s scores or yesterday’s weather.
Over the past several years, Google Search has been experimenting with ways to give users more instant answers by providing companion results to the traditional search engine results page (SERP). An example is the “Google Answer Box,” a snippet that sits above all organic search results and provides quick and easy answers to queries by providing a snippet of content from one of the result pages. The Answer Box has become the holy grail for SEO platforms to target as the propensity to click on answers in the box is much higher.
Another key feature is “People Also Ask” (PAA), which is a snippet offering users additional information related to their initial query. Google pulls the answers from relevant websites and presents them as snippets, along with a link to the original website. The answers are presented in various formats such as paragraphs, lists, images, tables or even videos.
These are typically presented as other questions for users to ask to explore their search topic further. When you click on a question, the answer appears below it. It also triggers more questions to appear, which you can expand by clicking on the down arrow icon. This process can frequently get you to your desired answer faster.
Through these search capabilities, traditional search engines are now trying to deliver quicker, more direct answers, similar to how AI-powered search engines work.
The Third-Party Cookie Saga Continues
The saga of the end of third-party cookies took on a new life as Google announced in July 2024 that it would indefinitely delay the removal of third-party cookies from Chrome. This was a significant reversal of policy after years of delays,
Third-party cookies are pieces of tracking codes placed on a user’s computer when they visit a website, and they trigger re-targeted ads when a user visits other websites. These cookies have become the standard for advertising and tracking purposes, allowing advertisers to track user behavior across multiple websites.
Google’s alternative plan to third-party cookies, the Privacy Sandbox initiative, aimed to create technologies that both protect people's privacy online and give companies and marketers tools to build advertising campaigns to grow their businesses. Recent experiments to assess the impact of third-party cookie removal were mixed.
The way that Privacy Sandbox works is that your information doesn't leave your computer. As you browse the web, your web browser adds categories of interest -– for example car shopping, clothing or food. When advertisers want to sell an ad, they go to Google and request a specific ad be sent to all the people in your category of interest. The problem here is that customer information is a lot less granular and specific. Advertisers are finding this really lowers their profits.
Key findings from enabling the Privacy Sandbox showed positive results for conversion-focused campaigns, with a 97% recovery in conversion per dollar (CPD) in Google Display Ads. However, remarketing results showed only a 55% spend recovery in Google Ads due to the remarketing reliance on third-party cookies. This is likely a big factor in the reversal decision.
This reversal comes at an interesting time when AI-powered search engines are beginning to threaten the lucrative ads business. Advertisers have expressed concerns that eliminating cookies from Chrome would restrict their capacity to gather data for ad personalization. Fewer ads means less revenue.
As the digital landscape evolves, there’s a growing emphasis on privacy, leading to changes in how third-party cookies are used and regulated. Privacy advocates are not happy and are likely to continue to put pressure on regulation that forces an end to third-party cookies.
Other browser makers have been able to cut off support for third-party cookies without issue. In 2019, Mozilla Firefox started blocking such cookies by default. Apple’s Safari began blocking third-party cookies by default in March 2020, with the major update to its Safari Intelligent Tracking Prevention (ITP). They introduced a privacy feature that allows the company’s web browser to block cookies and prevent advertisers from tracking your web habits.
Why have others removed third-party cookies but Google has not? That’s the million-dollar question, but one can assume that Google is worried about ad revenue cannibalization. Other browser companies are not as concentrated in ad revenues.
The elimination of third-party cookies creates challenges for both traditional search tools and new AI-powered search engines. Without access to extensive browsing data, AI algorithms will need to rely more on first-party data collected directly by websites.
Related Article: Third-Party Cookie Deprecation: Preparing for Marketing's Future
How AI-Powered Search Engines Are Shaping the Future of Search
While AI may not immediately kill traditional search, it will undoubtedly force traditional search engines to rethink their approach to the search experience. Ironically, AI is likely to be a catalyst for enhancing the capabilities of traditional search engines.
AI will help search engines develop more sophistication as they leverage core AI platforms to better understand user intent, personalize results and summarize information. They will be context-aware and will leverage that context for better search results. AI will deeply integrate multi-modal search with images, voice, video and text to create seamless search experiences.
Traditional marketing models will get disrupted by AI search. The era of keyword stuffing is likely coming to an end, replaced by a focus on user intent. As AI-powered search engines evolve to better understand user intent, SEO strategy will shift from focusing on keyword counts to leveraging location-based services.
In the end, AI and search engines are likely to remain companions and not direct competitors. Users want the best of both worlds -– the ability to use generative AI to begin a search and then use search results to dive deeper into a topic.
In the near future, some users will use generative AI often, some will use it intermittently, and others won’t use it at all. But everyone will continue to use search.
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