Goldman Sachs: Ads and Subscriptions for AI Agents

Key Takeaways

1Goldman Sachs predicts that AI agents will generate revenue through advertising and premium ad-free subscriptions

2Meta's Muse has topped the free apps chart on the US App Store after its launch

3The open-source framework OpenClaw, created by Peter Steinberger, has gone viral, particularly in China

4The business model will depend on user trust for managing sensitive data

Why it matters : AI agents are evolving into tools capable of acting on behalf of users, which presents new challenges for monetization and trust.

AI agents are no longer limited to conversation: they now make purchases and reservations for their users. Goldman Sachs anticipates a monetization model inspired by the web, combining advertising and premium ad-free subscriptions. This evolution comes with new challenges regarding trust and access to data.

Muse Tops App Charts and Breakthrough of Agent Tools

Following its launch, Meta's AI agent Muse reached the top of the free apps chart on Apple's App Store in the United States. This momentum is part of a wave of AI agents offered by OpenAI, Anthropic, and others, capable of browsing the web and completing tasks for users. Meanwhile, the open-source framework OpenClaw, developed by Austrian Peter Steinberger, went viral among developers earlier this year. OpenClaw has seen particular success in China, where it has been adopted by companies and developers to create their own AI agents.

Advertising and Subscriptions: The Backbone of the Business Model

Goldman Sachs identifies the conversion of the popularity of AI agents into revenue as the main upcoming challenge. Eric Sheridan, head of technology, media, and telecommunications research at the bank, believes that the business model will follow familiar patterns, with a mass market funded by advertising and premium ad-free subscription offerings. AI agents are likely to provide free options funded by advertising, in addition to paid proposals devoid of ads. Sheridan notes that AI and machine learning are expected to enhance the efficiency of digital advertising by automating the creation, placement, and evaluation of campaigns.

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User Trust and Access to Sensitive Data

The business model of AI agents will depend on the trust users place in them to manage sensitive information, such as calendars, passwords, and payment data. Broader access to this information would enable agents to perform increasingly complex tasks on behalf of users.

From Infrastructure to Platform: Focus on Action

Eric Sheridan positions the evolution of AI agents as a transition from an infrastructure layer to a true platform layer. He describes the emergence of action-oriented agent commerce aimed at consumers. This evolution accompanies the shift of AI agents from mere conversational interaction to the execution of concrete tasks, a phenomenon that has recently captivated Silicon Valley. The launch of Muse by Meta illustrates this trend. Sheridan presented these insights in an article published Friday on Goldman Sachs' website.