Perplexity has decided to walk away from advertising as a revenue strategy, instead focusing its AI search platform on user trust and subscription-based access rather than sponsored results. Executives confirmed the company has phased out advertising experiments introduced in 2024 and is not currently pursuing new ad partnerships.

The decision comes as AI companies search for sustainable revenue models to fund increasingly expensive AI development and infrastructure. While some firms are introducing advertising into conversational products, Perplexity argues that ads risk undermining confidence in AI-generated answers — especially when users depend on chatbots for factual or professional decisions.

The move highlights a growing divide across the AI industry over how AI assistants should make money: whether conversational systems evolve into ad-supported platforms or remain paid tools optimized for neutrality and accuracy.

Developers, enterprise buyers, and everyday users are directly affected as monetization strategies begin shaping how AI systems present information and earn trust.

Here’s what this means for organizations evaluating AI search platforms and the future economics of conversational AI.

According to executives speaking at industry roundtables reported by Financial Times, Business Insider, and later summarized by The Verge, Perplexity quietly phased out advertising experiments that began in 2024. The company had previously tested labeled sponsored placements appearing beneath chatbot responses.

Leadership concluded that advertising risked damaging user confidence.

An unnamed executive, cited by the Financial Times, said advertising risks undermining confidence in AI responses: “The challenge with ads is that a user would just start doubting everything . . . which is why we don’t see it as a fruitful thing to focus on right now.” The company instead plans to focus on building products consumers are “willing to pay for,” particularly targeting business customers and professional users such as finance professionals, lawyers, doctors, and CEOs.

While one executive did not permanently rule out a return to advertising, they said serving ads was currently “misaligned with what users want” from an AI assistant, adding, “We are in the accuracy business, and the business is giving the truth, the right answers.”

Perplexity’s decision highlights a growing divide across the AI ecosystem over how conversational AI should generate revenue.

Some companies are embracing advertising as a way to support large-scale AI infrastructure costs. OpenAI, for example, has begun testing advertising within free tiers of ChatGPT, displaying sponsored links while maintaining that ads do not influence generated responses or conversation privacy.

Google has taken a different approach by integrating advertising directly into AI Overviews within certain Search results, where sponsored content can appear alongside AI-generated summaries, even as its Gemini chatbot experience remains ad-free for now.

Others are taking the opposite stance. Anthropic has publicly committed to keeping Claude free from advertising, arguing that conversational AI must remain independent from incentives that could bias outputs.

Perplexity now aligns more closely with this trust-first approach, emphasizing neutrality and accuracy as core product differentiators rather than engagement-driven monetization.

The disagreement has increasingly moved into public view, with executives and marketing campaigns openly debating how AI systems should balance revenue generation with credibility.

Rather than monetizing attention, Perplexity is betting on subscription growth.

The company reports more than 100 million users and approximately $200 million in annualized revenue, largely derived from paid tiers ranging from $20 to $200 per month, alongside a free entry-level version designed to attract new users.

Executives argue that long-term sustainability depends on reliability rather than advertising scale. Even clearly labeled ads, they say, could prompt users to second-guess whether answers are objective.

Perplexity has also experimented with shopping comparison features, allowing users to evaluate products directly within conversations. Unlike traditional search platforms, however, Perplexity currently does not collect commissions or monetize purchases through these integrations.

This approach reflects an effort to strengthen perceived neutrality before expanding new revenue opportunities.

In doing so, monetization decisions increasingly become part of product design itself, influencing how users interpret and trust AI-generated answers.

Perplexity’s decision reflects a broader question facing the entire AI industry: how the way AI systems make money may ultimately shape how information is delivered and trusted.

That question is emerging as companies confront a deeper structural challenge — the rising cost of operating advanced models as training, inference, and infrastructure demands continue to expand.

To sustain those costs, companies are currently gravitating toward two primary revenue approaches:

Historically, internet search platforms monetized attention by presenting ads and sponsored links alongside lists of relevant websites. AI assistants, by contrast, generate synthesized answers directly, meaning users often rely on a single response instead of exploring multiple links.

Perplexity’s leadership argues that introducing commercial ads into conversational systems risks blurring the line between neutral answers and paid promotion, potentially making users question whether responses prioritize accuracy or revenue.

At the same time, the industry may not remain limited to advertising or subscriptions alone. As AI systems evolve into agents that complete tasks, coordinate workflows, and participate in economic activity, new monetization models may emerge that do not fit traditional internet business frameworks.

As AI search develops, companies must decide whether assistants function primarily as neutral information utilities, productivity software, advertising platforms — or something entirely new. That decision is likely to shape user expectations and business models across the next phase of the AI industry.

Q: What decision did Perplexity make about advertising?
A: Perplexity has phased out advertising experiments and is not currently pursuing new ad partnerships, choosing instead to focus on subscription-based revenue and enterprise customers.

Q: Why did Perplexity stop using advertising?
A: Company executives said advertising could cause users to question whether AI answers are influenced by commercial incentives. Because Perplexity positions itself as an accuracy-focused AI search platform, leadership believes ads risk undermining user trust.

Q: How does Perplexity’s approach differ from OpenAI and Anthropic?
A: The decision highlights a growing divide in the AI industry. OpenAI has begun testing advertising within free ChatGPT experiences, while Anthropic has committed to keeping Claude ad-free. Perplexity aligns more closely with the trust-first model but emphasizes subscriptions as its primary revenue path.

Q: How will Perplexity generate revenue without advertising?
A: The company is prioritizing paid subscriptions and enterprise customers, including professionals in finance, law, healthcare, and executive leadership roles. Executives believe users will pay for AI tools they trust to deliver unbiased answers.

Q: Why is advertising controversial for AI assistants specifically?
A: Unlike traditional search engines, conversational AI systems generate synthesized answers rather than lists of links. If advertising influences responses, users may struggle to distinguish neutral information from promotion, raising concerns about transparency, reliability, and long-term trust in AI systems.

Q: What does this decision mean for users and organizations choosing AI platforms?
A: Monetization strategy is becoming a key factor in platform selection. Organizations evaluating AI tools must now consider not only model capability but also how revenue incentives might shape responses, data usage, and long-term product direction.

Perplexity’s decision shows how competition in AI is expanding beyond model capability into questions of economic design and user trust. The contrasting strategies of Perplexity, OpenAI, Google, and Anthropic show how monetization choices are becoming as strategically important as model capability.

Who should care: Anyone relying on AI assistants for information — from everyday users to professionals and organizations — should pay attention, because monetization models may influence how answers are presented and trusted.

Why it matters now: AI assistants are moving from experimentation into daily decision-making tools used for research, work, and personal questions. As reliance grows, trust, neutrality, and reliability are becoming product features rather than abstract principles — especially as companies introduce new revenue models to sustain expensive AI infrastructure.

What decision this affects: Organizations evaluating AI tools must consider not only performance and cost, but whether a platform’s business model aligns with unbiased information delivery. At the same time, individual users may increasingly choose AI assistants based on how much they trust the incentives shaping the answers they receive.

As AI search matures, the defining competitive advantage may no longer be which system is smartest, but which system users believe they can trust.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.