According to a recent study of surveyed Americans, “71.5% reported using AI tools for search; 14% use them daily.”1 People are slowly moving to other avenues to search for information - from online forums to social media to AI tools, search engines are no longer the main source for information discovery.
Searching for information has long been associated with traditional search engines such as Google and Bing but in recent years, other channels and platforms have become preferred methods for information discovery. Now with the rise of AI, this creates even newer pathways for people to find information. The traditional search model is becoming a thing of the past and marketers and agencies specializing in search engine optimization (SEO) need to think broadly about the changing search landscape and develop more comprehensive strategies that embrace AI-powered search and even other alternatives like voice interfaces and social platforms as channels for information.
The Evolution of Search Behavior
Google has long been the leader in traditional search since the early 2000s and handles over 80% of online searches worldwide to this day2. However, platforms such as TikTok, Instagram, and Reddit are redefining search behavior among certain groups, particularly Gen Z users. Up to 41% of consumers have used TikTok as a search engine, with 64% of users being Gen Z3. These platforms deliver concise, user-generated, visual content featuring candid perspectives and genuine experiences that reshape our understanding of authenticity and trustworthiness4..jpg?width=427&height=238&name=shutterstock_2455136135%20(1).jpg)
Even voice-enabled smart speakers such as Amazon’s Alexa, Apple’s Siri, and Google Home allow more ways for people to search for information without the use of traditional desktop computers. It is projected that by 2026, voice assistant users will increase to 157 million5.This shift reflects a broader trend where users prefer immediate, direct answers rather than navigating through multiple links and webpages.
Beyond these evolving search behaviors, the introduction of AI-powered alternatives will only reinforce this shift, emphasizing specialized content and advanced reasoning with conversational interactions. Tools like ChatGPT, Claude, and Perplexity are fundamentally changing how users approach information discovery, offering intuitive dialogue-based interfaces that can understand context, remember previous questions, and synthesize complex information into direct, useful responses. Unlike traditional search engines that primarily serve as gateways to other websites, these AI systems aim to be the final destination in the information journey, providing comprehensive answers without requiring users to piece together information from multiple sources6.
How AI Search is Changing Traditional Search
AI-powered search represents a significant shift in how users discover and interact with information, moving beyond the link-focused model that has dominated the internet for decades and introducing several search innovations that create a more intuitive, efficient, and personalized experience.
Conversational vs. Keyword-Based Interactions
Users are conversing with these tools in order to find information instead of using a keyword-focused search query. Rather than crafting the perfect combination of keywords, users can now ask questions naturally, as if speaking to a knowledgeable colleague. This conversational approach allows for more nuanced queries and eliminates the guesswork often required in traditional search.
Context Retention and Follow-Up Capabilities
AI assistants excel at maintaining context throughout a conversation, remembering previous questions and building upon them. This creates a more fluid discovery process where users can refine their queries, ask follow-up questions, and dive deeper into topics without starting from scratch each time.
Direct Answers vs. Link Suggestions
The most significant difference is AI search’s ability to provide comprehensive answers rather than simply suggesting links like traditional search engines do. Users receive immediate, actionable information without the need to click through multiple websites and piece together information from various sources. Frameworks like query fan-out7 allow AI systems to anticipate follow-up information before users need to ask another question, providing a depth of information instead of starting a new conversation.
Multimodal Search Capabilities
Modern AI search tools support text, voice, and image inputs, creating a more versatile search experience. This is done through vector embeddings8 that translate content mathematically and allow AI systems to process different types of content contextually. Users can upload images, videos, audio files, or speak their queries through voice search, making information discovery more accessible and intuitive across different contexts and user preferences. This way of processing information is dramatically different from traditional search engines that leverage keywords in order to produce search results.
Personalization and Adaptation to User Patterns
AI systems learn from user interactions, adapting their responses and recommendations based on individual preferences, search history, and behavioral patterns. In fact, machine-learned personalization in search has led to a reduction in irrelevant result appearances by 30%.9 This creates a more personalized experience that becomes more valuable over time. As AI systems continue to evolve with newer versions, interacting with them will become more intuitive as they continue to learn and understand user behavior and preferences.
The New Information Discovery Ecosystem
The current landscape of search tools is rapidly evolving, with traditional search engines incorporating AI features while specialized AI tools emerge for different information needs. Google has introduced AI Overviews and AI Mode, Microsoft has integrated Copilot into Bing, and Perplexity offers AI-first search experiences.
These systems complement rather than completely replace each other. Traditional search engines remain valuable for navigating the broader web, while AI assistants excel at synthesis and analysis. Social platforms continue to serve as discovery mechanisms for trending topics and peer recommendations, while voice assistants provide convenient access for quick queries and smart home integration.
Looking ahead, we can expect continued convergence of these technologies, with traditional search engines becoming more conversational and AI systems improving their ability to access and cite real-time information from across the web.
Implications for Digital Marketing Strategy
This transformation in search behavior demands a fundamental rethinking of digital marketing strategies:
Visibility and Discoverability Considerations Beyond SEO
While traditional SEO remains important, marketers must now consider how their content appears in AI-generated responses. This means optimizing for featured snippets, ensuring content is easily digestible by AI systems, and creating comprehensive, authoritative content that AI tools are likely to reference and cite. Content must also be structured in ways that AI can easily parse and understand. This includes using clear headings, providing direct answers to common questions, and creating content that serves as authoritative sources on specific topics.
First-Party Data Importance in an AI-Mediated World
As AI systems potentially reduce website traffic, first-party data collection becomes even more critical. Brands need strategies to capture user information and maintain direct relationships even when consumers primarily interact with AI intermediaries.
New Metrics for Measuring Search Success
When it comes to measuring success, traditional metrics like click-through rates, organic traffic, and keyword rankings may become less relevant in an AI-driven search landscape. New success indicators might include AI citation rates, brand mention accuracy, and AI visibility. Some SEO SaaS platforms like SEMrush and Screaming Frog are transforming their service offerings with features around semantics and AI measurement, keeping up with the evolving trends within search.
How Marketers Should Evolve
Modern marketers must adapt their approaches to remain relevant in this changing landscape:
Technology Stack Adaptations
Marketers need to integrate new tools for monitoring AI search performance and optimizing content for AI discoverability. This may include AI content optimization tools, voice search analytics platforms, and specialized monitoring software for AI citation tracking.
Testing and Monitoring Methodologies for AI Visibility
Developing experimentation frameworks and pilots for testing new approaches to AI optimization is crucial. This includes A/B testing content formats for AI performance, monitoring brand accuracy across different AI platforms, and measuring the impact of AI-optimized content on overall brand visibility.
Cross-Channel Strategy Development
Although we can't be sure at this point, we expect that past website visits will factor into the personalization of results. Focusing on driving traffic back to your website may be an effective way to make sure your brand is visible in personalized AI responses.
Client Education and Ethical Responsibility
Agencies must help clients understand these shifts and set appropriate expectations for this new landscape. This includes educating clients about the longer-term nature of AI optimization and the importance of authoritative, comprehensive content creation. As AI systems become more influential in information discovery, agencies also have a responsibility to ensure accurate information representation and maintain transparency in their optimization strategies.
Continue to Build and Maintain Strong Brand Identity
Building a strong brand was always important and will continue to be important moving forward. Strong brands are more likely to be referenced by AI systems and remain top-of-mind for consumers across all search channels.
Conclusion
The search landscape is undergoing its most significant transformation since the early days of Google. The rise of AI-powered search tools, combined with the growing popularity of social media and voice search, is fundamentally changing how people discover information. For modern marketers, this shift presents both challenges and opportunities.
Those who adapt quickly to optimize for AI search, social discovery, and voice interfaces while maintaining strong traditional SEO practices will be best positioned to help their clients succeed in this new environment. The key is developing comprehensive strategies that embrace all channels of information discovery while building direct relationships with audiences through first-party data collection and consistent brand communication.
The future of search is not about replacing one method with another, but about creating integrated approaches that meet users wherever they are in their information discovery journey. Marketers that understand and adapt to this multi-channel reality will thrive in the evolving digital landscape…wherever that may take us.
Chartis is helping leading global brands navigate through this shift to expand their brand discovery in these new channels and listings. We'll add value to your business and help you move forward with confidence! Let’s talk.
Sources:
- https://searchengineland.com/ai-search-gaining-traction-not-replacing-google-survey-451667
- https://www.statista.com/statistics/216573/worldwide-market-share-of-search-engines/
- https://www.adobe.com/express/learn/blog/using-tiktok-as-a-search-engine
- https://searchengineland.com/social-search-gen-z-visibility-453502
- https://www.cmswire.com/digital-marketing/voice-search-optimization-the-role-of-ai-in-the-new-seo-landscape/
- https://www.searchenginejournal.com/alternative-search-engines-2/542095/
- https://www.searchenginejournal.com/google-query-fan-out-patent/547983/
- https://searchengineland.com/the-shift-to-semantic-seo-what-vectors-mean-for-your-strategy-452766
- https://aokmarketing.com/2024-google-search-trends-34-statistics-that-will-change-the-way-you-optimize/