“[Clients are] building the foundation right now, with many companies starting to take it seriously—while others are further along, ” said Brandon Biancalani, head of paid advertising at Modifly, a performance media and creative agency. Biancalani added that there isn’t “a code red where everyone must switch immediately due to lost revenue. ” Currently, the dilemma is whether to fully commit to an AI strategy or continue focusing on traditional SEO fundamentals. Digiday has explored this debate, examining the pros and cons of marketers adopting AI-driven search strategies. The case for AI search strategies Although Google remains the leading search engine, generative AI usage is expected to grow by 16. 8% this year, reaching about 34% of the U. S. population, according to eMarketer. Agencies are proposing AI search strategy trials to clients as a way to future-proof brand visibility. Brands’ online content will be integrated into large language models (LLMs) regardless of their preferences, compelling executives to develop strategies that better manage how their brands are represented, industry experts say. “Google has basically categorized all informational search as consensus content, ” explained Ryan Carroll, head of growth at Markacy performance marketing agency. Consensus content, as Carroll describes it, is aggregated material that LLMs pull from and present to users. Consequently, brands find it more difficult to stand out without a distinct perspective. “This shifts the responsibility onto the brand and publisher to convey unique personal experiences, opinions, and timely viewpoints. ” Even a tentative AI approach involving testing and learning enables brands to explore and grasp the broader effects, industry leaders note. AI-powered platforms have introduced features like chatbots and agentic shopping.

Experimenting with these new tools lets marketers be proactive rather than reactive, helping brands maintain organic visibility, said Jen Cornwell, senior director of AI SEO on Tinuiti’s innovation and growth team. “The rules on the platforms themselves are just changing, ” Cornwell emphasized. The case against AI search strategies Despite the shift, there remains a strong argument for continuing traditional SEO practices. Well-structured, accessible, and information-rich content still performs effectively and adapts well to AI environments, according to experts. “If you execute solid SEO with some tweaks to accommodate AI systems, you will perform well on Google search, ” said Ryne Landers, expert lead SEO at Markacy, “and your visibility in AI systems will also improve. ” However, the opaque nature of LLMs persists. Marketers seek to understand key aspects such as return on ad spend on platforms offering ad placements and how LLMs decide what content to show. For instance, Perplexity tested ads in its conversational AI search engine last year, but advertising opportunities have since diminished following the departure of its head of advertising, Taz Patel, and the suspension of new advertisers. Meanwhile, OpenAI reportedly plans to introduce ads, according to Digiday. “A big part of the hesitation stems from lacking a definitive method to measure the effectiveness of current efforts—there's no single source of truth right now, ” said David Dweck, president at Go Fish Digital. Dweck added that without such clarity, it’s challenging to justify fully committing to an AI search strategy. Instead, agencies rely on a mix of tools—brand lift studies, chatbot analytics, and other indicators—to understand user behavior and search patterns. Ultimately, marketers suggest combining traditional tactics with experimental approaches. “The more things change, the more they actually stay the same, ” said Carroll of Markacy. “We’ve learned not to invest all resources into one channel now, because everything is evolving too rapidly. ”