Stock Markets February 18, 2026

Perplexity Ends Advertising Experiment, Sticks With Subscriptions

San Francisco AI start-up pulls sponsored results amid concerns over user trust as peers pursue ad-based monetization

By Derek Hwang
Perplexity Ends Advertising Experiment, Sticks With Subscriptions

Perplexity, an AI start-up based in San Francisco, has halted its advertising experiments and removed sponsored content from its chatbot, saying ads risk undermining user trust. Executives confirmed on Tuesday that advertising will no longer be part of the companys revenue strategy, which currently includes paid subscriptions. The move contrasts with other AI firms that are rolling out ads to monetize free users while managing heavy costs tied to large language model operations.

Key Points

  • Perplexity has stopped using advertising after earlier trials that placed sponsored content beneath chatbot responses in 2024.
  • Company executives confirmed on Tuesday that advertising will not be pursued further; paid subscriptions remain part of Perplexitys business model.
  • Other leading AI firms are introducing ads to monetize free users and satisfy investors while managing the high costs of training and operating large language models - impacting the technology and advertising sectors.

Perplexity, the San Francisco-based artificial intelligence start-up, has abandoned its effort to monetize through advertising, concluding that ads could erode the trust of its user base. The company had been one of the early generative AI firms to trial an advertising format in 2024, placing sponsored content beneath responses generated by its chatbot.

In late 2024 Perplexity began taking those advertisements down, and on Tuesday company executives confirmed there are no plans to revive advertising as a revenue stream. Instead, the firm continues to offer paid subscription options as part of its business model.

The decision arrives as a number of leading AI companies adopt ad-based approaches to monetize free tiers and address investor pressure. Those companies are introducing advertising to capture revenue from users who do not pay, at the same time that they face significant expenses related to training and maintaining the large language models that power their products.

Perplexitys retreat from advertising reflects an internal judgment about a trade-off between short-term revenue and perceived platform integrity. Executives conveyed that concern when they confirmed the company will not pursue ad revenue going forward. The companys retained focus on subscriptions keeps its commercial strategy confined to direct user payments rather than third-party funded content placements.

The broader AI sector continues to weigh similar choices. Some firms are prioritizing advertising to raise funds from nonpaying users and meet investor expectations, while also absorbing continuing costs associated with large-scale model maintenance and development. Perplexitys course diverges from that trend, favoring a user-paid approach over third-party ads.

Beyond the revenue mechanics, the episode highlights the tensions companies face when balancing monetization with user experience and trust. Perplexitys executives concluded that the potential impact on trust outweighed the benefits of an ad channel, leading to the removal of sponsored content that had been visible beneath chatbot replies earlier in 2024.

For now, the companys commercial mix centers on subscriptions and whatever other non-ad strategies it elects to deploy, while peers continue to experiment with ad formats to capture incremental revenue from free users and appease investor demands amid heavy spending on large language models.

Risks

  • Potential erosion of user trust from advertising - relevant to consumer-facing AI platforms and the broader technology sector.
  • Revenue-model pressure on AI companies that choose to avoid advertising, which may affect their ability to monetize free users compared with ad-funded rivals - relevant to investors and technology firms.
  • Sustained high expenditures for training and maintaining large language models could intensify pressure on firms to find scalable revenue sources, affecting corporate finances across the AI industry.

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