AI and SEO in 2025: Embracing Continuity and Change

I’m thrilled to sit down with Aisha Amaira, a renowned MarTech expert whose passion for blending technology with marketing has transformed how businesses uncover vital customer insights. With her extensive background in CRM marketing technology and customer data platforms, Aisha brings a unique perspective on the evolving landscape of SEO and AI integration. In this interview, we’ll explore the enduring importance of SEO fundamentals, the impact of AI on search strategies, and practical ways businesses can adapt to these changes while staying ahead of the curve.

Can you share your thoughts on why the core principles of SEO remain so critical, even as AI continues to reshape the digital landscape?

Absolutely. I believe that despite all the buzz around AI, the foundation of SEO—things like quality content, technical optimization, authority building, and user experience—still drives the majority of success. These elements are about making sure search engines can understand and prioritize your content for the right audience. AI might change how results are displayed or interpreted, but it doesn’t replace the need for a solid base. If anything, it amplifies the importance of getting those basics right because AI systems rely on clear, structured data to pull insights.

How do you interpret the new buzzwords floating around, like AIO or LLMO, and why do you think they’re causing so much concern among SEO professionals?

These terms often refer to AI-driven optimization or language model-based approaches to search, but at their core, they’re just extensions of traditional SEO concepts. The panic comes from a fear of obsolescence—people worry that their skills won’t keep up with tech advancements. I see these as variations rather than replacements. They’re about adapting to how AI processes and prioritizes content, not starting from scratch. It’s more evolution than revolution, and understanding that can help calm the nerves.

With Google holding over 90% of the search market share, how does this dominance influence the way businesses should craft their SEO strategies?

Google’s dominance means that their algorithms and updates set the tone for the entire industry. Businesses need to align their strategies with Google’s priorities—whether it’s focusing on user intent, mobile-first indexing, or AI-driven features like overviews. Ignoring Google’s ecosystem is simply not an option for most. That said, it’s also about balance; while you optimize for Google, you can’t neglect emerging platforms or user behaviors that might shape future search trends.

Given that AI chatbots account for less than 3% of search traffic, do you think the hype around them as a threat to traditional search is overblown?

I do think the threat is overstated right now. The numbers show that traditional search, especially through Google, still reigns supreme. AI chatbots are more of a complementary tool at this stage—great for quick answers or specific queries, but they lack the depth and ecosystem of a full search engine. However, we shouldn’t dismiss them entirely. They’re a signal of where search could head, and businesses should keep an eye on how user adoption grows over time.

Google has integrated AI into its products with features like AI Overviews. How do you see this changing the way search results are presented to users?

These AI features are shifting search results from a list of links to more curated, summarized answers right at the top of the page. It’s about giving users instant information without needing to click through multiple sites. For example, if you search for a recipe, you might get a quick overview of ingredients and steps extracted from various sources. This means visibility is now about being the source AI pulls from, not just ranking high on the results page. It’s a game-changer for how content needs to be structured.

What are some of the biggest challenges these AI-driven changes pose for businesses trying to maintain visibility in search results?

One major challenge is the reduced click-through rate. If users get their answers directly from an AI summary, they might not visit your site, even if your content is featured. Another issue is the need for precision—AI pulls from content that’s clear, concise, and authoritative, so vague or poorly structured pages won’t cut it. Businesses also face the hurdle of building trust signals that AI recognizes, like consistent brand mentions across the web, which can be resource-intensive.

You’ve mentioned adapting tactics for AI optimization. Can you explain how structuring content in smaller, digestible pieces helps with AI features like overviews?

Structuring content in what I call ‘chunks’ means breaking it into clear, self-contained sections that answer specific questions or cover distinct points. AI systems love this because they can easily extract a snippet to display in an overview. For instance, if you’re writing about ‘best hiking boots,’ have a dedicated section titled ‘Top 3 Boots for Beginners’ with bullet points. That’s easy for AI to grab and present directly to users. It’s about making your content scannable and relevant at a granular level.

Why do you think unlinked brand mentions on forums and other platforms are becoming such a key factor in building authority for AI systems?

AI doesn’t just look at backlinks anymore; it’s scanning the web for context and sentiment around your brand. Unlinked mentions on forums, reviews, or articles signal that people are talking about you naturally, which boosts your credibility. For AI, this paints a picture of trustworthiness and relevance—key factors in determining expertise and authority. It’s less about direct links and more about the broader conversation happening online, which is a shift from traditional link-building strategies.

What technical adjustments do you recommend for businesses to ensure their sites are accessible to AI crawlers and optimized for these new search dynamics?

First, focus on technical SEO basics like fast load times and mobile optimization, because AI systems still prioritize user-friendly sites. Then, dive into specifics like implementing structured data through Schema markup, which helps AI understand the context of your content—think marking up recipes, events, or product details. Also, stay updated on new crawlers or bots that AI systems might use, ensuring your site isn’t blocking them in robots.txt. It’s about removing barriers so AI can interpret your content accurately.

Looking ahead, what is your forecast for the future of AI and SEO integration over the next few years?

I see AI becoming even more embedded in search, not as a replacement for traditional methods but as a layer that refines how content is discovered and presented. We’ll likely see more personalized, predictive search experiences where AI anticipates user needs before they even type a query. For SEO, this means an even stronger focus on user intent, semantic understanding, and building a holistic online presence. I think the balance between fundamentals and innovation will remain, but those who adapt to AI’s nuances—while staying grounded in core principles—will have the edge.

Explore more

Embedded Finance Transforms B2B Into Profit Machines

The Dawn of a New B2B Era More Than Just a Feature The business-to-business landscape is undergoing a seismic shift, driven by a force that is quietly rewiring the DNA of digital platforms: embedded finance. No longer a niche concept, the integration of financial services like payments, lending, and insurance directly into non-financial software is becoming a cornerstone of modern

Embedded Finance Evolves Into a Core Revenue Engine

In the increasingly competitive landscape of digital platforms, the ability to seamlessly integrate financial services is no longer a peripheral advantage but the definitive fault line separating market leaders from the laggards who are falling further behind. A profound transformation is underway, recasting embedded finance from a convenient add-on into the primary engine driving revenue, customer loyalty, and operational resilience.

Keep Your Business Central Implementation on Budget

Embarking on a new Enterprise Resource Planning (ERP) implementation is one of the most significant technological investments a business can make, yet nearly half of these projects ultimately exceed their initial budget. An implementation of a powerful system like Microsoft Dynamics 365 Business Central is intended to be a strategic asset, driving efficiency and growth for years to come. However,

Why Your ERP Needs an Architect From Day One?

The landscape of enterprise resource planning is littered with stories of ambitious projects that spiral out of control, exceeding budgets and timelines while failing to deliver on their initial promise. For years, the blame has been cast on complex software, shifting business requirements, or inadequate training. However, a deeper analysis suggests the problem often begins long before the first line

Business Central Data Quality – Review

Microsoft Dynamics 365 Business Central represents a significant advancement in the Enterprise Resource Planning sector for small and mid-sized businesses, yet its implementation success is frequently undermined by a pervasive, often-ignored factor. This review explores the evolution of data management challenges within this ecosystem, the subsequent failure of traditional data migration tools, and the emergence of a specialized data quality