2025 Midyear report on AI in marketing: The new role of marketers and AI search
The year is 2025, and the game has changed for search marketing and digital marketing. Forget keyword stuffing and generic content: LLM based search engines demand authenticity, personalization, and genuine value. They're prioritizing user experience, rewarding engaging content, and penalizing manipulative tactics. Google is largely rolling out AI-mode which is just another step toward generative search taking the front stage from traditional search. Providing the Gemini based search for free cannot be cheap, so now it’s about market share, and the advertising game will soon hit the stage also.
Shopify is doubling down on AI and MCP servers together with Anthropic. The rise for the market share in ecommerce and shopping is also happening in the generative search interfaces where the big players are hunting for companies to integrate their products and services to improve the AI-driven shopping experience.
As video continues to dominate engagement metrics across social platforms and emerging AI-powered feeds (e.g., generative “Stories” where users can ask follow-up questions about an ad), marketers who lean into VEO or SORA capabilities will be able to scale both creativity and personalization without sacrificing speed or quality.
We’re entering an era where the final resource constraints of producing and scaling high-quality video content have been removed. From here on, it’s just a matter of imagination and brand. -Jere Meriluoto, CEO & Co-Founder, Superlines.
Statistics
This shift requires a fundamental rethinking of how marketers approach their online presence and conversion funnels. As McKinsey & Company highlights, the successful implementation of AI requires not just technological adoption, but also organizational adaptation and a deep understanding of the evolving digital ecosystem. Staying ahead of the curve is no longer a luxury of few, but it's a necessity.
This isn't just about keeping up with the pace. It's about capitalizing on a market explosion. According to SEO.com the AI in the marketing sector is projected to reach a staggering $47.32 billion this year, a testament to its transformative potential. According to SurveyMonkey 88% of marketers already incorporating AI into their daily operations, the question isn't if you should adopt AI, but how you can leverage it most effectively.
The impact on marketing
This widespread adoption of using AI is driven by the real benefits AI offers. From automating repetitive tasks like social media scheduling and email marketing to providing deep data analysis for personalized customer journeys, AI has already changed how marketers work. The biggest wave is happening specifically in generative AI: according to McKinsey & Company 65% of organizations regularly employing this technology in 2024, almost double the adoption rate from the previous year. This indicates a rapid shift towards leveraging AI not just for automation, but also for creative content generation, personalized messaging, and advanced analytics.
The impact of AI on marketing efficiency and performance is undeniable. According to Hubspot’s survey (+1000 marketers) 86 % of marketers say AI saves them more than 1 hour every day. This reclaimed time allows marketers to focus on strategic initiatives, creative problem-solving, and building stronger customer relationships.
The new role of the growth marketer
The demand for specialized skills in AI management, data analysis, and strategic planning is on rise. Marketers are moving from specified deep-knowledge roles to becoming “cross-functional integrators” who can connect data analytics, influencer programs and product-led growth strategies, according to the American Marketing Association. This shift is echoed by Forbes’ notes about AI forcing CMOs and CIOs into shared responsibility where marketers move toward data, tech and partnership orchestration. A few CMOs we’ve spoken with recently also mentioned that they’re starting to rethink how future marketing teams should be structured. With AI and tech becoming more embedded in daily operations, there’s a growing need for marketers with an analyst- or business-oriented mindset. We believe the future of growth marketing favors versatile generalists, people who can navigate both creative and data-driven domains with equal fluency.
A generalist with even a basic understanding of coding will thrive in modern marketing teams like never before—especially now that low-code and no-code platforms make it possible to automate a wide range of tasks. -Kimmo Ihanus, CTO & CO-Founder, Superlines
Optimizing for AI search engines
AI search engines like ChatGPT, Gemini and Perplexity are changing how users interact with information online. Unlike traditional search engines that rely on keyword matching, AI search engines understand context, intent, and nuances in language. This shapes how consumers interact with the internet and is driving a large change in marketers approach to Search Engine Optimization (SEO), moving beyond keyword stuffing and focusing on creating genuinely valuable and comprehensive content. Simply put, optimizing for the age of AI means optimizing for people or conversations, not algorithms.
AI vs. traditional SEO
Traditional SEO focuses on optimizing content for search engine crawlers, prioritizing keyword density, backlinks, and technical SEO. AI search optimization, on the other hand, prioritizes user experience, focusing on providing comprehensive answers, engaging narratives, and anticipating user needs. Think of it this way: traditional SEO is about telling the search engine what your content is about; AI SEO is about showing the AI how your content helps users. This shift requires a move towards:
Semantic Search Optimization: Focus on the meaning and context of your content, using related keywords and concepts to build a comprehensive understanding of your topic.
User-Centric Content: Create content that genuinely answers user questions, provides valuable insights, and addresses their needs. Think beyond keywords and consider the user’s intent.
E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness. While E-A-T has been important for a while, it's paramount for AI SEO. AI can better identify and prioritize credible sources.
Read Superlines’ full guide for Generative Engine Optimization Best Practices here.
Key strategies for AI search optimization
So, how do you practically optimize your content for this new channel? Here are some key strategies:
1. Focus on Long-Form, Comprehensive Content: AI search engines reward in-depth content that thoroughly explores a topic. Instead of short, keyword-focused articles, aim for comprehensive guides, tutorials, and in-depth analyses. For example, instead of writing a 200-word blog post on "AI Marketing," create a comprehensive guide on "Leveraging AI for a Complete Marketing Transformation."
2. Structure Your Content Logically: Use clear headings, subheadings, bullet points, and numbered lists to make your content easy to scan and understand. This not only improves user experience but also helps AI engines grasp the structure and hierarchy of your information. Think of it as providing a clear roadmap for both users and AI.
3. Use Multi-Source Optimization: Incorporate images, videos, and interactive elements to enhance engagement and provide different ways for users to consume information. Visual content can help illustrate complex concepts and make your content more memorable.
4. Optimize for Conversational Queries: People are increasingly using natural language to search online. Optimize your content for conversational queries by anticipating the questions users might ask and providing clear, concise answers. Think about how someone would ask a question about your topic in a conversation and tailor your content accordingly.
5. Build a Strong Online Presence: Establish your brand as a trusted authority in your niche. This includes building a strong social media presence, engaging with your audience, and earning high-quality backlinks.
Brand monitoring, AI-generated content and GEO
The explosion of AI-generated content together with search moving to generative engines presents also a challenge for brands: how to track mentions and manage reputation in a digital landscape that’s increasingly automated and scattered. Traditional brand monitoring tools often fall short in this new environment, failing to effectively identify brand mentions within AI-created text, images, and videos. Also, with generative search, relying solely on tracking clicks to your website might cause missed opportunities in identifying how your brand is being mentioned by the LLM-services. Missing these factors can lead to missed opportunities for engagement and ultimately a loss of market share.
You can read more about how to track LLM visibility and how to track brand mentions in AI search results from Superlines articles.
The future of marketing is tightly connected with AI. Start by:
Integrating AI tools: Explore solutions like Superlines to optimize your content for AI search engines and streamline your generative engine optimization processes.
Upskilling your team: Invest in training to equip your marketers with the skills needed to thrive in the AI-driven future.
Developing an AI strategy: Define clear objectives and identify areas where AI can deliver the greatest value to your business.
Staying informed: Continuously monitor industry trends and best practices to remain competitive in the rapidly evolving AI marketing landscape.
Frequently Asked Questions
How can we prepare our marketing strategies for the rise of AI in marketing, specifically by 2025?
Start by integrating AI tools into your existing workflows. Focus on data collection and analysis to personalize customer experiences. Experiment with AI-powered content creation tools and explore AI-driven SEO strategies to optimize for AI search engines. Begin training your team on using these new technologies. Prioritize building a strong first-party data strategy, as data privacy regulations are likely to become even more stringent. By starting now, you'll be better positioned to leverage AI's full potential in the coming years.
What are the key challenges in optimizing for AI-driven search engines, and how can we overcome them?
AI search engines prioritize user experience and context. Challenges include understanding the algorithms' evolving nature, creating high-quality, contextually relevant content, and ensuring website accessibility and mobile-friendliness. Focus on semantic SEO, using natural language and structured data. Leverage AI tools to analyze search trends and user intent. Regularly monitor your website's performance and adapt to algorithm updates. Building a strong brand reputation and fostering user engagement are crucial for long-term success in AI-driven search.
What are the realistic timelines and costs associated with implementing generative AI for content creation and automation?
Implementing generative AI can range from quick integrations of individual tools (e.g., AI writing assistants) to complex, enterprise-level content automation platforms. Timelines vary from a few weeks for basic implementation to several months for larger projects. Costs depend on the chosen tools, the level of customization required, and ongoing maintenance. Start with a pilot project to assess the potential ROI and adjust your strategy accordingly. Consider factors like content quality control, brand voice consistency, and the need for human oversight.
What are the key features and selection criteria for choosing the right AI marketing platform for our business?
Consider your specific business needs and goals when choosing an AI marketing platform. Key features include data integration capabilities, AI-powered analytics, automation tools, and personalization functionalities. Evaluate platform scalability, ease of use, and integration with existing systems. Look for platforms that offer robust reporting and analytics to measure campaign performance. Consider factors like vendor reputation, customer support, and pricing models. Start with a trial period to test the platform's capabilities before making a long-term commitment.
How can we effectively monitor our brand reputation in the age of AI-generated content, and what are the potential pitfalls?
AI-generated content can spread misinformation quickly. Implement AI-powered brand monitoring tools to track brand mentions, sentiment, and online conversations. Set up alerts for negative mentions and potential crises. Engage with your audience authentically and address concerns promptly. Potential pitfalls include relying solely on automated tools and failing to understand the nuances of online conversations. Combine AI monitoring with human analysis to ensure accuracy and context. Develop a clear crisis communication plan to address any negative impacts from AI-generated content.