AI is swiftly transforming the search landscape.
As generative AI reshapes the user experience on search giants like Google and Bing and AI-powered chatbots like ChatGPT and Perplexity gain traction with consumers, advertisers are preparing for a search landscape whose future looks markedly different than its past.
Although Google still dominates the market, early signs of fragmentation are emerging. Last year, Google’s market share dropped below 90% for the first time since 2015. While much of that volume went to established competitors like Bing, Yandex, and Yahoo, newer AI search agents are gaining ground as well, with Gartner predicting that traditional search engine volume will decline by 25% by 2026 due to chatbot-like applications. Gen AI pioneer ChatGPT is projected to claim 1% of search market share this year, and OpenAI’s SearchGPT—which is currently in beta—could further challenge Google’s supremacy.
Future fragmentation aside, the shift towards conversational interfaces on traditional search engines is already impacting organic traffic and advertising opportunities, leaving media teams questioning how to adapt. To succeed in today’s evolving search landscape and ready themselves for success in the future of search engine marketing, advertising leaders must understand how AI is reshaping user behavior and take proactive measures to evolve how their search teams operate.
AI is driving a fundamental change in how consumers search online. Historically, people have used keywords to search (ex. “Miami beachside hotel.”) But AI is spurring a shift from keyword searching to natural language conversations (ex. "Can you find me a beachside hotel in Miami with vacancy on May 23rd?”) This can be seen with the growing popularity of AI agents like ChatGPT and Perplexity, as well as in traditional search engines with features like Google’s AI overviews (AIOs).
The shift towards conversational interactions could also lead to a larger focus on voice search. Google appears to be embracing the possibility, with a recent update to its Gemini tool that allows users to engage with AI much like they would with another person—similar to how Iron Man talks to Jarvis in the Marvel movies. Manus, an AI agent that recently went viral, is another AI agent that offers advanced conversational voice interactivity, and OpenAI has offered an Advanced Voice Mode since Q3 2024.
As consumer adoption of generative AI increases in the coming years—and competition among companies providing AI-powered chatbots rises—the overall search market will likely grow increasingly fragmented. While we’ll eventually see a decline in the use of traditional search engines, we’ll likely also see a net positive engagement with generative AI-powered search engine-like queries.
Currently, the biggest AI-related change that marketers are seeing with their search performance is a drop in organic traffic from Google and other traditional search engines. Industry experts predict that AIOs could result in as much as a 60% decrease in organic traffic, and an April 2025 study found that search results featuring an AI Overview were associated with a 34.5% lower average clickthrough rate (CTR).
While Google could work to mitigate the drop off in organic traffic with future updates, the current outlook has advertisers and businesses concerned. Earlier this year, education technology company Chegg filed a lawsuit against Google, claiming that AIOs have negatively impacted the company’s traffic and revenue.
AIOs are also making brands feel like they have fewer avenues for effectively leveraging search advertising (at least for the time being). This change might push advertisers to invest more in programmatic, video, and other non-search channels.
In my conversations with brand and agency leaders, I’ve heard an equal amount of fear and excitement around how AI will change both the search landscape and digital advertising as a whole. Ensuring teams grow their AI expertise and increase their familiarity with these new tools is one way organizations can prepare for—and adapt to—the coming changes.
Marketing teams should use AI-powered targeting to continuously test and learn what resonates with target audiences in today’s evolving search environment. This tactic is growing even more important in the context of signal loss, offering a privacy-friendly way to reach target audiences on search platforms like Google and Bing, while simultaneously giving media teams hands-on experience with the machine learning-based systems that are increasingly shaping search. By leaning into these tools now, teams can build the agility and expertise they’ll need to stay competitive as search becomes increasingly AI-driven.
Nearly all (97.7%) advertising agencies are using generative AI today, with 38.6% of agency professionals using it daily and over 90% using it at least weekly. To make the most of the technology, marketing teams should actively experiment with various generative AI tools to better understand how and where they can make the campaign process more efficient and data driven.
At the same time, AI comes with risks such as inaccuracies and bias, and leaders must make sure to put the proper guardrails in place to minimize risk—particularly when it comes to generating creative content and analyzing consumer data.
Google’s Performance Max (PMax) is one of the most prominent examples of how AI is shaping the future of advertising, particularly when it comes to using generative AI to create ads. For instance, within PMax, an advertiser can upload a picture of their product and tell PMax to generate an image of that product on a beach at sunset. PMax will then spit out four variations of that basic image for use in an ensuing campaign. There are some enormous time- and cost-efficiency benefits to this: Advertisers can cut thousands of dollars that would typically be spent on production and go to market much more quickly. They can even download that asset and use it on other channels for greater creative continuity.
While advertisers may not love the levels of control and transparency offered by PMax, using it to test and learn will help marketing teams gain expertise with AI-driven systems and better understand their benefits and drawbacks.
The shift to AI overviews and resulting decline in organic traffic doesn’t mean that brands should deprioritize their SEO efforts. Brands that continue to invest in SEO will be better positioned to have their content featured as a source in Google’s AI overviews, which often include clickable links that drive traffic back to a brand’s site.
However, knowing that Google’s AIOs are driving a drop in clickthrough rate, as well as allowing more relevant—but often lesser ranked—listings to drive answers, marketing teams should also develop a separate strategy for appearing in AIOs. This strategy should focus on optimizing content not just to appear as a direct answer, but also to address potential follow-up questions and offer context, rationale, and detailed information about the products or services being promoted.
One of the greatest benefits that AI offers advertisers is its ability to quickly process and analyze huge amounts of data. As the technology develops, data-related insights will become more widely available, and businesses will need the infrastructure and the know-how to use those insights effectively.
Data-driven cultures prioritize using data to guide decision-making—and invest time, energy, and money into the people, processes, and tools that make it possible. For leaders, this might mean improving data quality and consolidation workflows, conducting audits of all existing data sources (e.g., social media, website analytics, customer surveys, etc.), or investing in a CDP to better capitalize on first-party data.
By investing in AI-powered tools, data-facing teams will be able to generate new insights, improve accuracy, and automate tasks. And because they’ll be using AI for data-related tasks, teams will likely grow increasingly comfortable with these kinds of tools, which will make it easier for organizations to leverage additional AI-powered solutions as they emerge.
With 67% of marketing and business professionals reporting that a lack of education and training is the top barrier to AI adoption, it’s clear that empowering teams with continuing AI education should be a priority for leaders. This is especially true given how rapidly AI is evolving, and how quickly new tools are coming to market. By partnering with vendors or consultants for tailored workshops, creating AI-focused knowledge-sharing forums, and investing in training and education platforms, advertising leaders can grow teams whose AI expertise gives them an edge over their competitors. Advertising leaders should also work to upskill their teams by prioritizing AI-related skills when hiring new employees.
Lastly, leaders should aim to stay on top of news related to how search engines are changing, monitor what new AI-driven advertising opportunities are available, and pay attention to what successes and failures their peers are having with artificial intelligence tools.
In particular, leaders must stay attuned to the potential challenges and pitfalls posed by artificial intelligence. 100% of marketers agree that generative AI presents a brand safety and misinformation risk. A hallucinating AI chatbot, for example, can make up fake “facts” and generate misinformation that can be difficult for content moderation tools to spot, and the resulting content can represent a threat to brand safety.
There are also many unanswered questions related to AI-generated content and copyright infringement—from the legality of chatbots being trained on unlicensed content, to questions around who owns AI-generated media. In the short term, be sure to keep an eye on how the regulatory landscape develops. While we don’t know exactly how governments will legislate the use of these technologies, it’s all but certain that they will eventually take regulatory action, and staying updated on those developments will be critical.
The quickly evolving search landscape asks a lot of marketing and advertising leaders. Advertisers will need to get comfortable with being uncomfortable in the coming years as artificial intelligence moves the industry towards an uncertain future. Teams that use AI to test and learn, grow data driven cultures, and stay learning will have a leg up on those who are less proactive about adapting to how AI is changing search.
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Want to learn more about how your peers are leveraging AI? We surveyed marketing professionals across brands, agencies, and publishers to find out what tasks marketing teams are using AI for, how AI tools are impacting efficiency, how they predict AI will transform the future of marketing, and more. Check out AI and the Future of Marketing for all the findings.
