AI Begins to Shake Google's Search Advertising Business Behind $500 Billion Market Value Erosion

Written by: Cobo

AI is shaking the profit logic of Google Search.

On October 29, Alphabet, Google's parent company, saw its stock price plummet by about 13%, evaporating nearly $500 billion in market value in a single day. The market is concerned that artificial intelligence (AI) is eroding the search advertising model that supports Google's revenue. The latest financial report shows that although the volume of Google search queries has reached its fastest growth in five years, advertising revenue only grew by 12% year-on-year, with an increase of about $79 million compared to the previous quarter. Google's management admits that the monetization capability of the AI model is still inferior to traditional search.

This means that search frequency is higher than ever, but Wall Street is beginning to doubt whether Google can convert this activity into real revenue.

The high value of search advertising lies in its ability to influence people's purchasing decisions. Brands pay for prominent positions in search results, and when users click, Google profits from it. Once AI starts to intervene in searches, comparisons, and even directly places orders on behalf of users, users will no longer go through those ad placements. Even if people continue to search and consume, Google may find it difficult to achieve the same level of revenue as in the past.

But can AI even complete a simple shopping task?

Ironically, these AI entities that threaten the business models of internet giants sometimes cannot even complete a simple shopping task successfully.

A user on the X (formerly Twitter) platform, Maia, recently tested three AI shopping agents, and none successfully completed their tasks: Instinct was intercepted by Sephora's bot detection mechanism; Poke could not place an order on Uber Eats and couldn't even log into DoorDash; Dash completed a checkout at AutoZone, but the order was canceled about 17 hours later. Ultimately, none of these tools completed their tasks and suggested that users make purchases manually.

These three tools are a microcosm of the rapidly rising wave of "Personal Agents." Designed as digital avatars specifically for consumers, their ambition lies not only in providing suggestions but also in directly executing users' intentions, taking over the entire process of logging in, selecting, booking, and even paying. From ambitious startup teams to tech giants like Meta, everyone is rushing into this field. The high frequency, quantifiable nature, and direct collision with real money in shopping scenarios naturally make them an excellent testing ground for the practical capabilities of these AI avatars.

Take Dash as an example: it uses disposable virtual cards to protect users' real card numbers; checks out as a "guest" without needing to obtain the user's account password; and allows the shipping address to differ from the cardholder's information. From a security perspective, these designs are very reasonable. However, in the eyes of traditional payment fraud prevention systems, this combination of features looks very much like credit card fraud behavior—strange devices, virtual cards, and shipping addresses that do not match the cardholder's information can trigger alarms.

Dash's setbacks reflect a fatal flaw in AI shopping today: AI entities have learned to "run errands" for humans, but the entire business world is not yet prepared to verify their identities. From Cloudflare's bot defense lines to the stringent 3D Secure verification at payment endpoints, existing anti-fraud firewalls are indeed robust but "blind"; they cannot distinguish whether the entity on the other side is a malicious crawler or a compliant agent making purchases with real money on behalf of its owner.

Of course, it makes complete sense for merchants to remain cautious. If an AI mistakenly books the wrong flight, inputs the wrong address, or makes a purchase without proper authorization, who will bear the costs of refunds, chargebacks, and customer service? Due to the ambiguity of responsibility, accepting an unverifiable order may pose a greater risk than directly intercepting that order. Even if the agent program (AI entity) brings in customers ready to place orders, many merchants would still consider intercepting orders a safer choice.

Visa, Mastercard, and the "Agentic Commerce Protocol" jointly launched by OpenAI and Stripe are currently working to explore how to identify these agent programs and authorize their payment behaviors. Until these standards are widely adopted, merchants can only continue to use existing anti-fraud rules, even if it means potentially missing out on some legitimate orders.

Why doesn't Amazon welcome shopping agents?

However, security and responsibility issues only explain part of the resistance. For e-commerce giants like Amazon, allowing external AI agents to shop freely could also impact their advertising business, which is crucial for profitability.

Previously, Amazon went so far as to take Perplexity to court, forcing its "shopping agent" tool Comet to completely exit the Amazon platform and successfully obtaining a preliminary injunction; in September of this year, Amazon also banned Meta's shopping agent Muse. Although Amazon's official reasons are authorization, privacy, and security issues, the challenges posed by external shopping agents clearly go beyond that.

Advertising is one of Amazon's core revenue sources. Major brands bid for promotional positions in product search results, hoping consumers will see these ads while browsing, comparing, and filtering products. If AI takes over all of this and can even autonomously select higher-cost-performance products, then consumers will not see these ads at all. Every transaction that bypasses the Amazon platform directly undermines Amazon's control over user purchasing behavior.

Similar pressures are also appearing at Google. As more and more consumers begin to search and shop through AI, traditional search advertising may no longer be a necessary part of the purchasing decision. Through protocols like AP2 and UCP, Google hopes users can complete product discovery, decision-making, and checkout processes directly within "Google Search" and Gemini. Although the monetization efficiency of search advertising may decline, as long as shopping behavior occurs on Google's "territory," it can retain users and have the opportunity to profit from the transactions themselves.

Advertising Giants Begin to Bet on Transaction Business

Similarly reliant on advertising revenue, Google and Meta are experiencing vastly different AI impacts. The former faces pressure on search advertising monetization, while the latter has already begun to reap substantial returns from AI investments. Meta's advertising revenue in the third quarter grew by 26% year-on-year, more than twice the growth rate of Google's search business. CFO Susan Li stated that advertisers who adopted suggestions from Meta's AI business assistant had conversion rates nearly 5% higher than those who did not, with the cost per conversion remaining stable, while these advertisers also increased their spending on ads by 9%. AI has not only improved the effectiveness of Meta's ads but also attracted more advertising budgets.

However, just as the advertising business continues to grow, this company, which derives about 98% of its revenue from advertising, has launched a shopping agent Muse that contains no ads at all. About six weeks after its launch, Muse surpassed 10 million users in the United States and Canada. More than a quarter of its weekly active users shop through it, with an average order value exceeding $200. Zuckerberg stated that it may achieve profitability through transaction commissions or subscription fees in the future.

Meta is simultaneously leveraging AI to increase advertising revenue while seeking new monetization methods for the potential loss of advertising value. As consumers gradually become accustomed to having AI search, compare, and place orders, platforms that control transaction entry may not only sell ads to merchants but also directly earn a share from each transaction.

This change is beginning to transmit downstream to the payment segment, opening up new growth spaces for payment service providers like Stripe.

Meta's Muse, Grok Bot, and Instinct have all integrated Stripe's Link agent wallet. Data released by Stripe at the end of September showed that AI agent purchases completed through Link grew 38 times in the past month. Since Stripe serves a large merchant base, it can enable these shopping agents with payment capabilities and assist merchants in processing payments. Consumers can shop through various different agents, while the underlying payment process is consistently handled by the same company.

As shopping entry points become increasingly fragmented, payment service providers like Stripe are expected to become the "default payment layer" connecting agent tools and merchants. Regardless of which agent tool ultimately prevails, every transaction must go through identity verification, payment authorization, and settlement processes, and each step in these processes contains commercial value.

As Shopping Entry Shifts, Who Can Profit from Transactions?

Google hopes to keep shopping within Search and Gemini, Meta is beginning to explore transaction revenue beyond advertising, and Stripe is providing payment services for different shopping agents. As AI gradually participates in consumers' search, comparison, and purchasing decisions, the revenue originally obtained by search engines and e-commerce platforms may also start to flow to new participants.

For years, search engines and e-commerce platforms have held consumers' "entry points," converting user attention into advertising revenue. Brands pay for impressions and clicks, while platforms have already earned revenue before consumers place orders. In a shopping process dominated by "smart agents," consumers may only need to express their needs, and the remaining tasks of searching, filtering, and placing orders are all handled by the agents. The "discovery" and "recommendation" functions previously borne by advertising are gradually shifting to these smart agents.

This change will give rise to new forms of advertising. Brands will still need to compete for consumers' choices, and smart agents may also establish their own "paid promotion" mechanisms or charge recommendation fees. However, as purchasing decisions shift to AI interfaces, at least part of the value originally captured by search results pages and product listings will flow to those who can guide decisions, facilitate transactions, or handle payments.

Looking back at the divergence between search volume and advertising revenue growth in Google's financial report, for a search giant that relies on advertising, nothing is more unsettling: users are still searching and consuming, but the money is starting to flow elsewhere.

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