OpenAI to Begin Testing Ads in ChatGPT Free and Go Tiers

Jan 18, 2026
OpenAI will start testing advertisements in ChatGPT for Free and Go plan users in the United States. The company says ads will appear under responses and will not affect chatbot answers or data privacy.

OpenAI announced in a blog post that it will begin testing advertisements in the United States for users of its ChatGPT Free and ChatGPT Go plans. The company said the tests will start in the coming weeks and apply only to logged-in adult users. Paid tiers including Plus, Pro, Business, and Enterprise will remain ad-free.

The ads will appear beneath chatbot responses when a relevant sponsored product or service matches the conversation. They will be clearly labeled and separated from ChatGPT’s generated answers. Users will be able to view why an ad was shown, hide specific ads, and disable personalization entirely.

OpenAI stated that it will not show ads to users it believes are under 18 or in conversations involving sensitive topics such as health or politics. The company emphasized that ChatGPT’s answers will remain independent from advertising content and that user data will not be sold to advertisers.

The new ad-supported approach is part of OpenAI’s broader plan to expand access to ChatGPT while maintaining free usage options. The company also recently made the ChatGPT Go plan available globally for $8 per month, offering extended features at a lower cost than higher-tier subscriptions.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Daily AI Brief or Sales & Marketing AI Weekly.

Also, consider following us on social media:

AI Brief AI Brief (X)
Free newsletter

Sales & Marketing AI Weekly

News about AI tools and innovations for Sales and Marketing professionals.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.