For years, OpenAI has been setting the pace for the productive AI revolution with ChatGPT.
Their partnership with Microsoft proved to be invincible, including the creation and distribution of the business. However, the lead they once held is now less.
Faced with evidence that Google’s Gemini has not only caught up but surpassed capabilities in critical areas, OpenAI CEO Sam Altman made the surprising decision to announce an internal “code red.”
Doing so pauses all non-essential programs to focus exclusively on the quality of ChatGPT.
The most significant risk of this change was OpenAI’s plan to introduce advertising to ChatGPT.
It’s important to note that OpenAI’s advertising programs have been postponed, not canceled.
Currently, OpenAI cannot successfully monetize its product while at the same time losing users to its top competitors.
Maintaining a loyal user base by addressing important issues with speed, honesty, and thoughtfulness is a priority, but that doesn’t mean ads are off the table.
To understand why ChatGPT’s ad programs have been suspended, but will be avoided in the future, we need to examine how OpenAI fell behind, the steps it is taking to recover, and what this delay means for the future of AI advertising.
Big stumbles from behind
OpenAI and Microsoft have not slowed down.
Instead, Google’s massive infrastructure investment has paid off, revealing a weakness in the Microsoft-OpenAI alliance.
The main reason for the change in performance lies in the design of the models.
Google’s Gemini 3 is built from the ground up as a “traditional multimodal” model.
It does not process text, images, video, and code separately. It understands them as linked data.
In contrast, ChatGPT includes different, specialized models:
- GPT-4 text.
- DALL-E for graphics.
- Whisper for sound.
This Frankenstein method, while initially sad, eventually becomes slower, clunkier, and less cohesive than Google’s unified approach.
Google used its technology advantage, controlling all components including Gemini:
- Custom designed tensor processing unit (TPU) chips train the models effectively.
- Data centers and the model itself.
- End-user applications, such as Android, Gmail, and Docs.
This allows for a level of development and cost control that Microsoft and OpenAI strive to match.
The Microsoft-OpenAI partnership is heavily dependent on expensive Nvidia GPU integration, a factor in OpenAI’s losses that could reach $140 billion by 2029, according to Deutsche Bank Research.
Ultimately, the absence of an ecosystem contributed greatly to the change in user experience of ChatGPT.
Google has easily embedded Gemini into users’ daily workflows, making it feel like a single, unified assistant across their entire workplace.
Although Microsoft’s Copilot has been criticized for feeling disjointed, as an add-on feature that may not be compatible across Word, Excel, Teams, and Windows.
Recent benchmarks from LMArena showed the Gemini 3’s ChatGPT to outperform in computing, coding, and speed, showing that the compact, integrated machine was beginning to surpass the alliance between Microsoft and ChatGPT.
Dig deeper: OpenAI discusses ad-driven strategy focused on ChatGPT scale and media partnerships
How ChatGPT and Gemini solve the same problem in a different way
Here is an example scenario comparing the processing behavior of both GPTs to show the differences.
Goal: You need to live in Times Square to be close to your office, but you hate the noise. You need a tech-forward “quiet” hotel, a guaranteed workspace nearby (since Times Square hotel rooms are notoriously small), and a quality ramen place that doesn’t require a 2-hour wait.
ChatGPT method
ChatGPT will likely provide a list of popular, high-volume hotels and restaurants that regularly appear on travel blogs.
- Procedure: Searches for “luxury hotels Times Square” and “Ramen near 42nd St.”
- Result: “I recommend the Marriott Marquis or The Knickerbocker. For ramen, Ichiran is highly rated and a few blocks away. You can find their locations on a map.”
- Gap: It may not realize that Ichiran Times Square often has a 90-minute wait on a Tuesday night, or that the Marriott lobby is abuzz with someone trying to take a deep Zoom call.
The way of Gemini
Gemini uses the integration of Google Maps and Workspace to find “niche” results that specifically address the needs of business travelers.
- Process: It identifies hotels by “Quiet/City” room rates, maps the walking distance to WeWork for professionals, and analyzes real-time “Popular Moments” data for restaurants.
- Result: “I really enjoyed your stay in Times Square. I recommend LUMA.” Times Square Hotel. Their ‘City Rooms’ are specially designed to be soundproofed from road noise.
- Integrated logic:
- Working together: Since the LUMA lobby is small, I mapped a 4-minute walk to WeWork at 1460 Broadway. It has a roof terrace with views of the square where you can work with your dog (based on previous search history for ‘Pet Friendly’ offices).
- Restaurant strategy: Instead of the main Ichiran, I suggest Raku on 9th Ave. It’s a 10 minute walk, very quiet, and currently has a 4.7 star rating for ‘low wait times’ on a Tuesday evening.
- Action taken: I added the walking route from LUMA to WeWork to your Google Maps ‘Favorites’ and saved a draft of this trip to your Google Calendar.”
In this situation, Gemini is like a helpful partner who not only talks, but makes things happen.
ChatGPT works like a smart book that tells you the facts.
On the other hand, Gemini:
- Connects in real time to see live traffic.
- It checks your calendar so you don’t drink.
- It also helps you write emails or stories directly in your documents.
It can remember many details and see what is happening now, solving practical problems instead of just answering questions.
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A ‘code red’ response
The “code red” in OpenAI is the acknowledgment that new features and revenue experiments don’t make sense if the foundation breaks down, forcing them to go back to the basics.
OpenAI released GPT-5.2 in December as part of a broader plan to reduce Gemini’s lead in complex reasoning and coding tasks.
The directive within OpenAI is clear:
- Stop seeing things that don’t exist.
- Improve speed.
- Make the model feel authentic and personal again.
They went from a passive chatbot that “talks” and has the ability to serve a system that can reliably perform complex tasks on behalf of the user, an area where Google is currently leading.
Microsoft faces a similar challenge on the product side.
Their priority is to unify the Copilot experience so that it stops feeling like five separate AI tools and starts working as a unified system that understands user context across different applications.
Microsoft also has to solve its data silo problem.
Google wins with personalization because it has access to users’ emails, calendars, and location data.
Microsoft will likely need to use Office 365 data more effectively – and securely – to provide the same personal experience, in addition to reselling OpenAI models.
Survival precedes monetization: An understanding of the hiatus
The ad delay decision is an important indicator of the severity of OpenAI’s competitive problem. Introducing paid ads can cause a conflict in the user experience.
If the product, in this case ChatGPT, is the market leader, users will tolerate friction as the cost of access.
However, now that ChatGPT is no longer the leader, users are tempted by Gemini’s speed and better integration within the free product category.
As a result, the presentation of advertisements on ChatGPT may cause user inconvenience.
OpenAI realized that if they took out ads while the quality of their product was balanced, they wouldn’t just fail to make money – they could permanently stunt their growth.
As a result, maintenance should come before income.
OpenAI needs to offset the loss of its user base by achieving equal or better performance with Gemini.
Once trust is re-established and users feel like ChatGPT is their way again, can they introduce advertising?
Dig deeper: Sergey Brin: Google ‘wasted’ by underinvesting in AI
Designing AI interactive ads
Although the delay is important, it is important to realize that the respite is temporary.
The financial problems facing OpenAI are what make advertising inevitable in the future.
To be profitable, it needs to generate hundreds of billions in revenue by the end of the decade.
A single subscription from users will not be enough; monetizing their free tier with ads will be a must.
However, “code red” and pressure from Google will also change how those ads end up appearing.
The delay buys OpenAI time to develop less intrusive and more reliable ad formats.
This means that recent tests that offer irrelevant app suggestions between conversations will no longer work.
Future ChatGPT ads will need to be integrated and contextual to avoid driving users to Gemini.
The goal will be to present the ads natively without breaking the conversational flow of the brand.
Ultimately, the pause in ChatGPT’s ads is a stepping stone in its growth to compete in the competitive AI space.
It’s a necessary gamble for OpenAI to build a better “brain” fast enough to take on Google.
Potential ad revenue is the ultimate prize, but OpenAI must hone the quality of the product before claiming it.
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