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    Home»Tech»Perplexity Abandons AI Advertising Strategy Over Trust Worries
    Tech

    Perplexity Abandons AI Advertising Strategy Over Trust Worries

    February 18, 20264 Mins Read
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    Perplexity Gains Labs for Creating Reports, Spreadsheets, Web Apps and More
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    AI company Perplexity is stepping away from advertising over concerns that it will erode user trust, despite moves by rivals to introduce ads as an alternative money-making strategy.


    Perplexity was one of the first AI services to embrace ads in 2024, after it ran tests where sponsored answers appeared under the chatbot’s answers. That approach however was phased out last year, and executives at the company now say they don’t plan to revisit it, according to the Financial Times.

    “A user needs to believe this is the best possible answer, to keep using the product and be willing to pay for it,” a Perplexity executive told the publication.

    The report follows OpenAI’s move earlier this month to show ads to ChatGPT users who have a free account or a low-cost Go subscription. OpenAI has said ads will not influence the answers that ChatGPT provides, nor will it provide advertisers with content from ChatGPT conversations.

    Anthropic, the makers of Claude, recently mocked OpenAI for its decision to show ads to users and has said it has no plans to do the same. The company argues that including ads in Claude would not be in line with its mission of creating a helpful assistant for work and deep thinking, and that users should not need to second-guess whether an AI is being helpful or “subtly steering the conversation towards something monetizable.”

    Google features advertising in AI mode and in its AI Overviews summaries on traditional search results. However, Google has not introduced ads into its Gemini chatbot so far.

    Ad strategies are one way that AI companies have been looking at as a way to generate revenue from users and reassure investors while spending heavily to train and operate large language models. Meanwhile, the cost of training and running large language models continues to climb, with no profit to show for it.

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