Contributors:
Amol Ghemud Published: September 25, 2025
Summary
What:
An exploration of how traditional SEO strategies, focused on keywords, backlinks, and rankings, are evolving in the age of AI-driven search and generative models. Who:
SEO specialists, digital marketers, CMOs, content strategists, and businesses aiming to adapt to AI-driven search changes. Why:
Traditional SEO methods alone are no longer enough. AI-powered tools prioritize content relevance, context, user intent, and structured authority over basic keyword optimization. When:
In 2025 and beyond, as AI search platforms like Google Gemini, Bing Copilot, Perplexity, and others become dominant channels for user discovery. How:
By integrating AI-focused strategies such as semantic content optimization, structured data markup, user-intent targeting, and cross-platform authority building. Traditional SEO still matters, but must now work alongside approaches that make content discoverable and trusted by AI systems.
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How AI is reshaping traditional SEO strategies, changing ranking factors, and redefining how businesses achieve visibility in 2025
Traditional SEO has long focused on ranking on Google’s first page through keywords, meta tags, and backlinks. For years, businesses measured success with organic traffic, click-through rates, and SERP positions. Content quality, link building, and technical optimization were the foundations of visibility, and following best practices often guaranteed results.
In 2025, the search landscape is rapidly evolving. AI-driven models and generative engines are transforming the way users find information, providing direct answers through AI summaries, voice assistants, and conversational interfaces. Ranking high alone is no longer enough; visibility now depends on relevance, authority, and the ability of content to be trusted and cited by AI systems. Marketers must adapt by combining traditional SEO with AI-aware strategies, ensuring content is not just discoverable but also authoritative, contextually accurate, and aligned with user intent.
Let’s explore how traditional SEO is evolving in the AI era, the elements that remain important, and practical strategies marketers can implement to stay competitive in this new search environment.
What is the role of Traditional SEO in the Age of AI?
Even as AI dominates search, traditional SEO principles remain relevant. Keywords, backlinks, and content quality are still foundational, but AI-driven search now evaluates content for intent, trustworthiness, and context.
Key shifts include:
Focus on User Intent: AI models interpret queries semantically. Optimizing content for intent is as important as targeting exact keywords.
Content Depth and Clarity: AI prefers content that thoroughly answers questions, making detailed, well-structured pages critical.
Authority Signals Beyond Backlinks: Mentions, expert references, and cross-platform citations now complement traditional link-building efforts.
Businesses that blend these AI-aware tactics with traditional SEO are more likely to maintain and improve visibility across modern search ecosystems. Subservices like Authority Building, Content Strategy, and AI-driven Analytics can amplify these results.
AI is transforming not only rankings but also how results are displayed. Featured snippets, knowledge panels, and AI-generated answer boxes are now standard. These elements prioritize content identified as the most relevant and trustworthy by AI.
To appear in these features, content must be structured for AI parsing and clear enough to be referenced confidently. Subservices, such as Structured Content Design and Cross-Platform Citations, help ensure content is AI-ready.
How to Adapt Technical SEO for AI?
Technical SEO is evolving as AI increasingly evaluates user experience and content context. Traditional aspects, such as crawlability, indexing, and page speed, remain critical, but AI introduces new dimensions.
Structured Data: Schema markup enables AI to comprehend the relationships between content elements.
Mobile Optimization: Mobile-friendly pages are crucial for AI to surface content accurately and confidently.
Performance Metrics: Page speed, dwell time, and engagement now influence AI’s content evaluation.
Brands that upgrade their technical SEO with AI in mind improve chances of appearing in both traditional SERPs and AI-driven answer formats. Subservices like Technical SEO Audit and Performance Optimization can support this transformation.
What are the Practical Steps One should practice for AI-led SEO?
To future-proof traditional SEO strategies, marketers should:
Map Content to User Questions: Research intent and craft content that directly answers real queries.
Enhance Authority: Include references, expert quotes, and data-driven insights to boost credibility.
Monitor AI Engagement: Track which content appears in AI-generated summaries, snippets, and voice search results.
Optimize Across Platforms: Share content on forums, social communities, and video platforms to increase citation signals and enhance your online presence.
Integrating subservices, such as content strategy, Authority Building, and AI-driven Analytics, can significantly amplify results.
For a deeper, hands-on approach, you can also explore our Generative Engine Optimization Services, where we help brands implement AI-friendly content strategies, amplify citations, and maximize AI-driven visibility.
How Fi Money Became the Top Authority for Smart Deposit Queries
Fi Money, a digital-first financial app, aimed to dominate AI-driven search results for high-intent queries, such as “smart deposit interest rates” and “how Fi Smart Deposit works.” Their initial content was generic, lacked trust signals, and was buried under competitors’ traditional banking content.
upGrowth implemented a (GEO) strategy by creating a comprehensive Smart Deposit Knowledge Hub targeting 20+ long-tail queries, adding comparative tables, and embedding dynamic tools like an ROI calculator to help users understand returns. They strengthened authority through RBI-registered NBFC partnerships, compliance documentation, and structured schema markup, while also utilizing visual content, infographics, and explainer videos to enhance AI visibility.
The results were remarkable: Fi Money appeared in 92% of AI Overviews for relevant queries, organic traffic to Smart Deposit pages increased by 240%, and engagement with interactive tools drove a 35% rise in account sign-ups.
The brand garnered citations from major publications, including The Economic Times and MoneyControl, and secured over 50 backlinks from fintech blogs and forums. AI Overview visibility surged from 8% to 92%, with the average ranking moving from #7 to #1, demonstrating how structured, credible, and contextually rich content can dominate generative search results.
Want to see more Digital Marketing strategies in action? Explore ourcase studies to learn how data-driven marketing has created a measurable impact for brands across industries.
Conclusion
Traditional SEO remains relevant, but in 2025, relying solely on keywords, backlinks, and page rankings is no longer enough. AI-driven search prioritizes intent, contextual relevance, and trust signals. Businesses that integrate AI-aware strategies into their SEO practices can maintain visibility, build authority, and adapt to the rapidly evolving search landscape.
Adapting to this new era means striking a balance between core SEO fundamentals and AI-informed tactics. Understanding user intent, optimizing content clarity, structuring pages for AI parsing, and building credibility through authoritative citations are essential steps.
Brands that adopt these strategies will not only maintain SERP visibility but also enhance their chances of being surfaced in AI answer boxes, voice search results, and other generative search features.
In short, the future of SEO is not about choosing between traditional methods and AI; it’s about blending both for a comprehensive, forward-looking strategy that positions your brand as trusted, relevant, and discoverable.
Ready to future-proof your GEO strategy?
Start implementing Generative Engine Optimization (GEO) today and ensure your content is trusted, cited, and surfaced by AI-driven search platforms.
Get started with upGrowth’s Analyze → Optimize → Automate framework to craft AI-friendly content, boost cross-platform citations, and dominate the next era of search.
Yes. Core SEO practices, such as keywords, backlinks, and content quality, continue to matter for visibility on search engines. However, AI-driven search now adds new layers, including user intent, the trustworthiness of content, and the presence in AI answer boxes and voice search results. Combining traditional SEO with AI-aware strategies ensures maximum reach and impact.
2. How does AI change traditional SEO?
AI transforms SEO by prioritizing semantic relevance, context, and credible citations over exact keyword matching. Search results increasingly include AI-generated summaries, chat-based answers, and voice responses. This means your content must not only be optimized for search engines but also structured and authoritative enough to be surfaced by AI models.
3. Which technical SEO elements matter most for AI?
AI evaluates technical SEO factors more comprehensively and holistically. Key elements include structured data (schema markup), mobile-friendly design, fast page load speeds, and user engagement signals like dwell time and click-through rate. Optimizing these factors improves the likelihood that AI will parse, trust, and display your content in answer boxes.
4. Can traditional SEO and GEO work together?
Absolutely. Traditional SEO establishes a solid foundation for visibility through targeted keywords, high-quality backlinks, and optimized content structure. GEO complements this by optimizing content for AI comprehension, citations, and surfacing in AI-driven search results, ensuring your content reaches users across both conventional and AI-first search environments.
5. How do I track AI visibility?
Track AI visibility by monitoring which pages appear in AI answer boxes, voice search results, and AI-powered summaries. Additionally, check cross-platform mentions, community discussions, and engagement metrics. These insights help refine content strategy to improve surfacing in AI-driven search while maintaining strong SERP performance.
For Curious Minds
AI-driven search engines now define authority through a wider lens that includes contextual relevance, expert validation, and cross-platform consistency. This shift means your credibility is no longer just about who links to you, but about how comprehensively and accurately your content addresses user intent, making it a trusted source for AI to cite. Building this new form of authority is vital for appearing in AI summaries and gaining user trust.
To demonstrate authority effectively for AI:
Develop in-depth content that thoroughly explores topics, leaving no room for ambiguity.
Incorporate citations from and mentions by recognized experts in your field.
Ensure your brand and information are consistently presented across various digital platforms.
Use structured data (Schema markup) to explicitly define your content's context for AI crawlers.
Focusing on these signals proves your content is not just linked-to, but genuinely trustworthy, impacting metrics like dwell time as users engage with valuable information. Discover more about building AI-proof authority in the full analysis.
Optimizing for user intent means creating content that directly solves the underlying problem or answers the core question behind a user's query, rather than just matching keywords. AI systems prioritize pages that deliver comprehensive solutions, so your focus must shift from 'what words did they use' to 'what are they trying to achieve?' This requires a deeper understanding of the user journey from question to solution.
This strategic pivot from keywords to intent involves:
Analyzing the entire SERP to understand what types of content currently satisfy users for a given query.
Structuring your content logically with clear headings that address subsequent or related questions.
Creating detailed pages that cover a topic from multiple angles, fulfilling informational, navigational, and transactional needs.
Instead of just targeting a keyword, you are building a resource that AI can confidently reference, a key factor for being included in AI-generated answers and improving overall SERP positions. Learn how to map your content to user intent by exploring the complete guide.
An AI-aware content strategy focuses on creating definitive, well-structured resources that AI can easily parse and trust, while traditional SEO often prioritizes keyword repetition and link quantity. The former builds long-term authority and relevance for generative engines, whereas the latter can lead to diminishing returns as AI gets smarter. Your choice should be guided by the goal of becoming a citable source for AI summaries.
Consider these factors when allocating resources:
Goal: If you aim for inclusion in features like Google AI Overviews, invest in deep, authoritative content and structured data. If immediate ranking for less competitive terms is the goal, traditional methods may still offer some value.
Competition: In crowded markets, demonstrating superior depth and clarity is a key differentiator for AI.
Longevity: AI-aware content is an investment in future-proof visibility, while traditional tactics may require constant updates to keep up with algorithm changes.
Ultimately, a blended approach is best, using traditional SEO as a foundation and layering AI-focused strategies on top to secure visibility in the modern search ecosystem. Find out how to balance these two approaches in our detailed article.
These AI features provide direct, synthesized answers at the top of the page, often satisfying user queries without requiring a click on a traditional blue link. This transforms the journey from 'search and explore' to 'ask and receive,' placing immense value on being the cited source within the AI-generated response. This is the new top-of-funnel visibility.
Evidence shows these systems prefer content that is:
Well-structured: Pages with clear headings, bullet points, and logical flow are easier for AI to parse.
Data-rich and specific: Content that includes statistics, clear definitions, and step-by-step instructions is frequently cited. For example, mentioning specific performance metrics improves citability.
Unambiguous and factual: AI prioritizes content that presents information clearly and authoritatively, avoiding vague or overly promotional language.
Brands appearing in a Bing Copilot summary, for instance, have demonstrated a high degree of trustworthiness and clarity to the AI model. To understand the precise formatting that gets you cited, read the full report.
The rise of zero-click searches, accelerated by generative AI, means traditional click-through rates (CTR) are no longer the ultimate measure of SEO success. Your content can be highly visible and influential by being featured in an AI answer, even if it doesn't receive a direct click, rendering CTR an incomplete metric for performance. Success is now measured by influence as much as traffic.
Marketers should now track a new set of metrics:
Impressions and Citations in AI Features: Measuring how often your content is shown or cited in AI Overviews or by systems like Perplexity.
Branded Search Volume: An increase suggests your AI-driven visibility is building brand recall.
On-Page Engagement: For the traffic you do get, metrics like dwell time and conversions are more important than ever, indicating content quality.
These indicators provide a more accurate picture of your brand's authority and relevance in the new search ecosystem. Learn how to set up tracking for these AI-era metrics in the complete article.
Adapting technical SEO for AI requires shifting from a purely crawler-focused mindset to one that prioritizes making your content easily understood and contextualized for generative models. This ensures your site is not just indexed, but interpreted as a high-authority source. Think of it as preparing a structured brief for the AI.
Here is a four-step implementation plan:
Audit and Implement Schema Markup: Go beyond basic schema. Use specific types like FAQPage, Article, and Organization markup to explicitly define your content's purpose and entities.
Prioritize Core Web Vitals and Page Speed: AI systems use performance metrics as a proxy for user experience. A fast, stable site is seen as more reliable and authoritative.
Ensure Flawless Mobile Optimization: Since many AI interactions happen on mobile devices, a seamless mobile experience is non-negotiable for AI to surface your content confidently.
Structure Content for Clarity: Use simple HTML tags (H1, H2, UL) logically. This helps AI parse the information hierarchy and identify key takeaways for its summaries.
By systematically upgrading your technical foundation, you improve the chances of your content being selected by engines like Google for AI Overviews. Explore advanced technical strategies in the full guide.
The most frequent error is treating AI as just a smarter keyword matcher, leading to 'AI-optimized' content that is still shallow and lacks true substance. This approach fails because AI evaluates content holistically for expertise, depth, and trustworthiness, not just keyword placement. The solution is to shift from targeting strings of text to building a knowledge base.
To avoid this pitfall and build real authority:
Focus on Topic Clusters: Instead of single-keyword pages, create comprehensive hubs of content that cover a subject from every angle, establishing your site as an authority.
Prioritize Factual Accuracy: Ensure all claims are backed by data and cite reputable sources. AI models cross-reference information to verify its credibility.
Use Structured Data: Implement schema markup to give AI explicit context about your content, authors, and organization, which directly signals trustworthiness.
By creating content that genuinely educates and answers questions thoroughly, you align with the goals of AI search systems like Perplexity, which aim to provide reliable answers. Discover how to conduct a content audit for AI-readiness in the complete article.
Conversational AI is making search more interactive and question-based, effectively transforming every query into a long-tail keyword. This diminishes the value of targeting niche, obscure phrases and instead elevates the importance of providing direct, clear answers to natural language questions. Your content must be structured to function as a direct answer engine.
To prepare for this future, marketers should:
Adopt a Question-and-Answer Format: Structure content with clear questions as headings (e.g., H2s, H3s) and provide concise, direct answers immediately below.
Optimize for Semantic Search: Focus on covering topics and entities comprehensively rather than fixating on exact keyword phrases.
Implement FAQ Schema: Use structured data to explicitly mark the Q&A sections of your pages, making them easily identifiable for voice assistants and AI models.
This approach ensures your content is ready to be pulled into conversational responses by systems from Google and others, positioning your brand for visibility in the next wave of search. Read more about future-proofing your content in the full analysis.
Relying solely on backlinks is a failing strategy because AI evaluates trust based on a wider array of signals that a simple link cannot convey. Generative models look for real-world authority and consensus, making unlinked brand mentions, expert associations, and consistent information across platforms powerful new ranking factors. Your reputation now matters as much as your link profile.
To build authority beyond backlinks, focus on:
Securing Unlinked Mentions: Getting your brand name or key personnel mentioned on reputable industry sites, even without a hyperlink.
Earning Expert Endorsements: Feature quotes or contributions from recognized experts in your content and encourage them to share it.
Maintaining Information Consistency: Ensure your core business information is consistent and accurate across all digital profiles.
These signals provide AI with a clearer picture of your brand’s credibility, influencing your visibility in SERP features beyond what traditional SERP positions can measure. Learn how to build a modern authority profile in the full guide.
Generative Engine Optimization (GEO) implies a future where success depends less on manipulating ranking signals and more on becoming a trusted, citable entity for AI. This elevates the role of SEO professionals from technical specialists to strategic content architects who curate knowledge and build digital authority. Content creators become less like writers and more like subject matter experts.
The necessary evolution in skill sets includes:
Deep Subject Matter Expertise: Creating content that is not just keyword-rich but factually impeccable and deeply insightful.
Data Storytelling: Using structured data and clear information architecture to communicate context to AI engines.
Cross-Platform Brand Management: Ensuring brand messaging and information are consistent everywhere online to build a cohesive authority signal.
Professionals who master these skills will be better equipped to ensure their brands are visible and influential in AI-driven search ecosystems, from Google to Bing Copilot. Prepare for this shift by exploring the foundational principles of GEO in our article.
Smart brands are re-engineering their content to serve two purposes: providing citable, factual snippets for AI summaries and offering deeper, more engaging experiences for users who do click through. They accept that lower organic traffic is a reality but focus on making every visit count more by capturing leads or building brand affinity. The new goal is to win the 'citation' at the top and the 'conversion' on the page.
Successful strategies we are seeing include:
Creating 'Citable Snippets': Placing concise, data-backed definitions and answers high up in the article, making them easy for AI to grab.
Embedding Interactive Tools: Including calculators, quizzes, or configurators that AI cannot replicate, giving users a reason to click.
Gated Deep-Dives: Offering a comprehensive ebook or webinar download in exchange for an email, turning visibility into a lead.
This dual approach ensures brands benefit from being cited by engines like Perplexity while still driving meaningful business outcomes. Dive deeper into these advanced content strategies in the full analysis.
A resource-constrained startup should focus on dominating a narrow niche with unparalleled authority rather than competing broadly. The key is to blend foundational SEO with AI-centric tactics that signal deep expertise, which AI models are designed to recognize and reward. Go deep, not wide, to become the go-to source for AI.
A lean, four-step approach would be:
Identify a Hyper-Specific Niche: Choose a topic where you can realistically become the foremost expert and create pillar content.
Build Foundational Technical SEO: Ensure your site is fast, mobile-friendly, and has a clean architecture. This is a one-time investment with lasting impact.
Create One Piece of Definitive Content: Develop a single, comprehensive guide that answers every possible question on your niche topic, structured with clear headings and data.
Amplify with Authority Signals: Focus on getting mentioned by one or two key experts or publications in your niche instead of chasing dozens of low-quality backlinks.
This disciplined strategy helps you appear authoritative to AI systems like Google's, maximizing your visibility without a massive budget. Find more resource-efficient tactics in the complete guide.
Amol has helped catalyse business growth with his strategic & data-driven methodologies. With a decade of experience in the field of marketing, he has donned multiple hats, from channel optimization, data analytics and creative brand positioning to growth engineering and sales.
Growth Strategy and Planning
