Diverging Paths in AI Search: What Advertisers Need to Do Now

Monetization in AI search is not a question of if, but when and how. Every platform will get there, but the pace and the formats are already starting to diverge.

For now, Google stands as the only AI search player delivering advertising at scale. Through our work with global brands across Google’s Performance Max and AI Max for Search products, PMG has seen firsthand how AI is reshaping visibility and driving new opportunities for discovery. These products enable advertisers to reach consumers across Google’s surfaces, allowing them to build insights that can be applied to other platforms as they follow.

Elsewhere, the approaches seem quite different. Perplexity has scaled back its early ad experiments following adoption challenges, choosing instead to focus on building trust and credibility for its product. OpenAI, meanwhile, is starting to explore what advertising might look like within ChatGPT, as indicated by job postings related to developing in-house ad infrastructure.

 These moves highlight that AI search platforms are at various stages of monetization. Some, like Perplexity, are pausing to focus on users, while others are experimenting with how advertising might develop. What is clear is that monetization will arrive for all of them, though the timing and formats will differ.

Importantly, Perplexity’s early test should not be seen as proof that advertising within AI search is ineffective. Their test was limited in scope and involved a new ad format on a platform where users were not yet accustomed to engaging with ads. Future strategies may favor more familiar formats, such as display, video, or text ads, which consumers already recognize, and adoption could increase quickly once these are introduced.

These developments make one thing clear: AI-driven search will evolve differently across platforms, but readiness can’t wait. PMG’s view is that success will come from learning through today’s opportunities while preparing for tomorrow’s models.

The lesson isn’t to wait for one platform’s timeline—Perplexity may pause while OpenAI accelerates—but to ensure readiness across the board. AI-driven search and discovery will monetize; the only unknowns are when and how. Advertisers who prepare now will be best positioned to capitalize on emerging opportunities.

At PMG, we believe that preparation starts with five priorities:

Lean Into Google’s AI Integrations Today

Google already offers AI-enabled placements that give brands a head start on the discovery landscape. Products like Performance Max and AI Max for Search extend reach across Google surfaces where AI influences visibility and engagement. PMG’s data-driven performance teams are actively testing and learning across these placements, helping brands understand how AI distribution impacts performance today and informing future readiness.

Activating these features now enables brands to gain early insights, strengthen their presence, and shape the evolution of AI search through shared learnings with Google partners.

Optimize Structured Data for Discovery

From product catalogs to location data, structured feeds play a critical role in how AI platforms understand and showcase your brand. Based on our experience helping brands structure data for omnichannel performance, PMG views well-defined feeds as foundational to discovery across AI-driven surfaces.

Product Feeds: Optimize every element with descriptive, keyword-rich titles, high-quality imagery, and videos that bring products to life. These enhancements ensure eligibility in today’s AI-powered surfaces.

Location Feeds: Keep store hours, addresses, and inventory availability accurate. As AI discovery blends online and offline intent, location signals will be essential to driving foot traffic.

Future-Proofing: Documentation from new partners, such as OpenAI and Perplexity, is not yet fully defined, but their requirements are likely to differ from Google’s. Brands should anticipate fields unique to each platform and adapt beyond static product specifications to include contextual descriptors, such as benefits, use cases, and attributes, that align with natural-language queries.

Keep Content Active and Timely

AI platforms draw from diverse signals, including site content, reviews, affiliates, and social activity. Maintaining fresh, optimized, and credible content ensures accurate brand representation as LLMs generate answers and platforms build discovery features. At PMG, we’ve observed that brands maintaining cultural relevance and freshness see stronger visibility in AI-driven discovery moments.

Social Signals: Timely and relevant posts provide cultural context that directly influences visibility. A clear proof point is that Instagram content is now indexing in SERPs, demonstrating how social activity influences search outcomes.

Broader Ecosystem: Reviews, affiliate pages, and website content all contribute to brand authority. When kept current and contextually relevant, they increase the likelihood of being surfaced across AI-driven environments.

Build Measurement Foundations for the AI Era

Holistic and advanced measurement will set brands up for success as AI-driven discovery evolves. Establishing baselines now helps identify emerging opportunities and behavioral shifts. PMG’s analytics and media teams are pioneering advanced measurement frameworks—combining paid and organic data, MMM, and attribution modeling—to evaluate AI placements holistically and connect discovery to performance.

Holistic View: Combine paid search and organic data to capture the true impact of SERP activity, and expand measurement to include how the brand surfaces across LLMs and social. This means tracking not only keyword-driven visibility but also presence in AI-generated answers, snippets, and social indexing moments. By connecting these touchpoints into a single view, brands gain a clearer picture of how discovery is happening across the evolving ecosystem.

Advanced Tools: Many AI-driven placements will live in the discovery phase, meaning they may not always deliver last-touch conversion value. Advanced measurement approaches like MMM will be essential for evaluating these touchpoints holistically, revealing their role in driving awareness and shaping the path to purchase.

Advanced measurement frameworks ultimately tie these pieces together. They prove that discovery-phase interactions contribute to completed purchases and provide the clarity needed as new AI-driven placements begin to scale.

Expand and Activate Audiences with First-Party Data

As AI search evolves, audience strategies will determine flexibility and performance. First-party data will be central to understanding user behavior and adapting to signal loss. PMG’s data and engineering teams are helping brands connect, segment, and activate first-party data to strengthen current performance while building readiness for these new monetization models.