As AI assistants increasingly become the initial point of contact for search, planning, and decision-making, the focus has shifted from whether these platforms will monetize to how they will do so. Companies such as Google, OpenAI, and Perplexity are already establishing a revenue model that integrates advertisements, subscriptions, API usage, and commerce. This evolution alters the very fabric of the internet, while the fundamental principle remains: high intent consistently gravitates toward the most efficient interface.
The introduction of AI Overviews by Google within its search functionality hints at a commercially viable future for conversational interfaces. Although Gemini, Google’s AI initiative, has yet to incorporate confirmed ads, its infrastructure is poised to support such a move. AI Overviews already display ads powered by Google’s existing Search and Shopping systems, which are the backbone of its business model.
Akshay Mathur, Founder and CEO of Unpromptd, articulates this strategic shift: “If Google introduces ads into Gemini, does it become a third performance channel or simply a UX layer on top of Search?” His insights suggest that even if Gemini operates on the same auction and measurement frameworks as Google Ads, it could become a potent high-intent platform. For marketers, conversational queries will offer a fresh rhythmic and in-depth approach compared to traditional keyword searches, yet fundamentally, the monetization logic remains unchanged, involving intent signals, automated bidding, inventory pricing, and attribution.
Concerns about the erosion of organic traffic loom large in the industry. AI Overviews already fulfill a growing proportion of queries without necessitating user clicks, and assistants further this trend by resolving tasks within the conversation itself. The addition of ads could reinforce this trend, as delivering comparison charts, recommendations, and commerce pathways directly within the interface may result in diminished traffic and discoverability for publishers and merchants. Mathur emphasizes that while ads will not initiate this movement, they will undoubtedly amplify it, effectively shifting the locus of value to the assistant layer, which becomes the new gateway to high-intent activities.
Although no AI assistant has rolled out a comprehensive advertising product, early prototypes are visible. Prototypes such as Perplexity‘s sponsored follow-up questions, Google’s contextual cards, and utility-based prompts in AI Overviews offer glimpses into potential ad formats that could maintain user trust. The formats most likely to succeed will be those positioned adjacent to answers rather than merging with them, such as sponsored next steps, product suggestions, and service cards. In contrast, those that blur the boundaries between organic and paid content risk eroding trust, inviting regulatory scrutiny and potential user abandonment.
The most significant commercial shift in AI assistants lies in redefining what constitutes advertising inventory. Instead of a single keyword, a moment within a conversation becomes more valuable. Eligibility for ads will hinge on the flow, tone, depth, and direction of the dialogue. Sponsored follow-up questions will create fewer but more contextually valuable ad slots, which can draw premium bids. Brands will no longer compete solely on a singular input; rather, they will vie for attention across multiple intent signals generated through multi-turn interactions. Google’s automated bidding systems are already adept at optimizing these signals, and the assistant provides a more nuanced understanding of user behavior.
A conversational thread yields more substantial information than any singular query, surfacing user preferences, constraints, comparisons, and readiness. Consequently, targeting will become context-driven, with bidding aligning to the highest points of influence. Attribution will no longer rely solely on last-click logic; it will need to trace contributions throughout the entire conversation. This shift promises a more precise understanding of intent but also creates a more complex landscape for marketers, who must adapt to fluid, dynamic user journeys rather than static keyword funnels.
Sajal Gupta, CEO of Kiaos Marketing, outlines the emerging revenue streams within the industry: “When ads come into conversational AI, you are going to get very relevant advertising inventory. Today search gives you inventory based on keywords. In conversation, it will be based on intent and context.” He further indicates that ads represent just one revenue pillar. The free functionalities prevalent today are unlikely to persist indefinitely; users will eventually need to select a specific AI engine to subscribe to, as utilizing all simultaneously will not be feasible.
According to Gupta, AI platforms will depend on four primary revenue streams: subscriptions, ads, affiliate commissions, and API usage. Affiliate revenue will be especially crucial during high-intent moments, such as when a user requests recommendations for purchasing a phone, and the AI suggests a retailer like Amazon, earning a commission on any resulting sales. This model mirrors the evolution of search but shifts it into a multi-turn context where the assistant actively guides the user journey.
As Gupta highlights, distribution will be a key factor in determining why advertisers choose certain platforms. Gemini will be integrated into Android and Chrome, while Copilot will be embedded in Office 365. OpenAI leads in API utilization and enterprise adoption, while Perplexity is gaining traction for deep research tasks. Each platform will attract advertisers based on user environments and behaviors. In this landscape, human interpretation will remain the creative differentiator, regardless of the AI model employed.
Looking ahead, the trajectory is towards sharper differentiation among platforms. Users are likely to subscribe to a primary AI engine that excels in its unique capabilities. As the advertising economy transitions from traditional search into conversations, the platforms that effectively balance utility with monetization and trust with commercial ambitions will help shape the future of the internet.
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