First Impressions of GPT Ads: OpenAI's New Ad Platform Is Still Too Raw

GPT Ads feels less like an advertising revolution and more like a beta that shipped too soon

The first feeling when entering GPT Ads is a curious one: you expect to find something radically new, almost an entirely new category of paid media, but what appears on screen still looks like a very early version of any Ads Manager you've already seen.

That's not necessarily a bad thing.

Every ad platform starts limited. Meta Ads didn't become Meta Ads overnight. Google Ads also spent years getting more sophisticated, more automated, and — let's be honest — more confusing. The difference is that when OpenAI launches an ad platform, the expectation isn't "another campaign manager." The expectation is: "okay, you're the company that's reinventing the internet's interface — now show me how ads work inside a conversation."

And that's where the first expectation gap shows up: right now, GPT Ads is simple. Very simple.

OpenAI officially positions the product as beta, with basic flows for campaign creation, management, and reporting, along with features still in development. The Ads Manager Beta lets you create campaigns, track impressions, clicks, and spend, and export data — but the documentation itself acknowledges that some capabilities are still limited and will be added over time.

In practice, my impression was: this isn't a performance machine yet. It's a paid lab.

Targeting Still Feels Too Shallow Coming From Google, Meta, or LinkedIn Ads

As expected, there aren't many targeting options yet.

And that's probably the point that will frustrate anyone coming from Google Ads, Meta Ads Manager, LinkedIn Campaign Manager, or any platform with years of behavioral data, audiences, lookalikes, lists, exclusions, remarketing, demographic layers, and conversion events.

In GPT Ads, from what I tested, the logic still seems much more context-driven than traditionally targeted. That makes sense for the product. After all, ChatGPT's differentiator isn't knowing that someone is 34 years old, lives in a certain city, and clicked a banner 8 days ago. The differentiator is understanding what the person is trying to solve at that exact moment.

But there's a massive difference between "conversational context" as a promise and "media control" as a working tool.

For a small or mid-sized advertiser, control matters. You don't just want to appear in conversations vaguely related to your market. You want to know which intents, which creatives, which offers — and with what CPA, ROAS, or qualified lead rate.

Right now, the platform still doesn't give you that sense of fine-tuned control.

Market guides describe a logic of "context hints" — phrases that signal relevant conversations, topics, or intents — but these don't function like traditional keywords. This reinforces the idea that GPT Ads shouldn't be treated as Google Search with a different interface.

You Can't Yet Think of GPT Ads as a Conversion Campaign

Another thing that caught my attention: from my experience, I didn't find a mature structure for conversion-oriented campaigns. What showed up was basically reach and click objectives.

That changes the conversation significantly.

When a platform only gives me reach and clicks, it's saying: "I can generate traffic or exposure, but I'm not ready to promise business optimization." For awareness, category discovery, and early testing — fine. For heavy performance — it falls short.

OpenAI already mentions CPC, pixel measurement, and Conversions API to track post-click actions like purchases, leads, or sign-ups. But there's an important difference between measuring conversions and natively optimizing campaigns for conversions. OpenAI itself says the Ads Manager is in beta and continues to expand how brands can buy, measure, and optimize campaigns.

That detail is crucial for any media buyer.

A pixel installed doesn't automatically turn a platform into a performance channel. What does that is volume, learning, delivery stability, attribution clarity, and optimization capability. And on all of those fronts, GPT Ads still looks like it's just getting started.

The Logo Bug Was Small, But Symbolically Significant

During setup, the platform threw a bug when trying to swap the account logo image, saying I wasn't an admin of the account.

Seems like a minor detail. But it isn't.

Anyone who works in paid media knows that an ad platform needs to project operational trust. It's not just about creating a campaign. It's billing, permissions, review, creative, tracking, policy, change history, approval, dispute, support, and governance.

When a simple permission bug shows up right at onboarding, the feeling is: "okay, this really is very beta."

And being beta is fine. The problem is when a beta product starts talking to big brand budgets.

OpenAI Seems to Want the Big Players First, Even as It Opens the Door to Smaller Ones

This is a point that bothered me.

OpenAI communicates that the self-serve Ads Manager makes buying more accessible for companies of all sizes — from SMBs to global brands. They also say they're gradually opening access while testing and refining the experience.

But in practice, the market feel is still very enterprise.

The recommended investment I've seen floating around is campaigns starting at $200,000. That completely changes the advertiser profile. This isn't a small business testing $100 a day. It's a major brand, a large agency, a company with an innovation budget and money to burn on experiments.

And that probably makes sense for OpenAI at this stage.

A new platform needs control. Open it too wide and you get spam, scams, aggressive affiliates, questionable products, miracle promises, and all the garbage we've already seen flood other networks. But there's a real tension: if the channel is born only with large advertisers, the diversity of offers may stay limited. And if diversity stays limited, the promise of "conversational relevance" ends up depending too heavily on whoever has the money to get in first.

That's where the risk lives.

People's Fear Isn't Seeing Ads. It's Not Knowing Where the Answer Ends and the Ad Begins.

Reading Reddit and other discussions, the strongest concern isn't simply "I hate ads."

That exists, of course. It always will.

But the real fear is something different: people are afraid that ads will contaminate responses with bias.

OpenAI states that ads are separate from responses, clearly labeled as sponsored, and don't influence what ChatGPT replies. It also says advertisers don't have access to conversations, history, memories, or personal details — they only receive aggregated performance data like views and clicks.

Even so, the public reaction shows an understandable distrust. In Reddit discussions, users openly talk about fear of "directed" responses from advertisers, paid recommendations disguised as help, and losing trust in the tool altogether.

And here's the core point: ChatGPT is not a timeline.

On Instagram, users already expect interruption. On Google, they already understand that sponsored links appear alongside results. On TikTok, the entire feed is a mix of entertainment, sales, influence, and algorithm.

But on ChatGPT, the psychological expectation is different.

People talk to the tool as if they're asking for help from a consultant, teacher, analyst, informal therapist, developer, travel planner, or strategist. The relationship is more intimate. That's why any sign of commercial interference weighs more.

It's not enough for the ad to be labeled. It needs to be perceived as separate.

I Tested Claude, Gemini, and GPT to Set Up the Ads — and GPT Was Better

One interesting thing: I used Claude, Gemini, and GPT itself to help me configure the ads, using the documentation as a reference along with what people were saying on Reddit.

GPT was better.

That shouldn't surprise anyone, but it's interesting in practice. When the task involves interpreting OpenAI's documentation, structuring a campaign for an OpenAI platform, and organizing creative context for a conversational logic, GPT naturally felt more aligned.

That's not to say Claude and Gemini were bad. They helped. But GPT connected the documentation, the user comments, the setup questions, and the campaign logic better.

That got me thinking: maybe the first big advantage of GPT Ads isn't just in the media placement — it's in the workflow.

If the platform evolves to let ChatGPT itself help create, review, adapt, and diagnose campaigns inside the Ads Manager, that's when the game really changes. Not because the ad shows up in the chat, but because media operations could get dramatically faster.

Right now, though, that integration still feels more like a promise than a reality.

The Manual Business Review Is the Strangest Part of All

Here's the question that kept nagging at me:

Why the hell is a pioneering AI company doing manual review?

The business review required to run ads is still taking a long time. And from what the experience suggests, there's a significant manual process involved.

Documentation and market guides point to verification steps, approval flows, and waiting periods. The setup is described as a flow involving business details, account configuration, identity verification via Persona, and a review period — with manual verification and a wait of several business days for account approval.

I understand the rational reason.

Ads inside AI are sensitive. If OpenAI approves any advertiser, it risks placing scams, miracle supplements, financial promises, regulated products, dubious health claims, or deceptive advertising inside an interface where users trust far more than they trust a banner.

So yes, manual review might be caution.

But it still sounds strange.

A company selling cognitive automation, automated reasoning, agents, APIs, and models capable of reviewing code, contracts, images, text, and data at scale — shouldn't it have a much more intelligent, fast, and transparent vetting layer?

Maybe the answer is legal. Maybe it's compliance. Maybe it's reputational risk. Maybe it's simply because the product is still raw.

But the question remains.

GPT Ads Could Be Powerful, But It's Not for Everyone Yet

My initial impression is that GPT Ads has real potential, especially for categories where the user is researching, comparing, and trying to make a decision.

B2B SaaS, education, travel, higher-value local services, software, consulting, productivity tools, complex products, and offers that require explanation could all benefit earlier.

For impulse e-commerce, low-cost products, tight CPA, and scale-dependent operations — I'd be much more cautious.

Reddit is already showing people trying to figure out CTR, click quality, and initial benchmarks. A recent post on r/PPC shared very preliminary data from three ad groups with CTRs of 0%, 1.15%, and 2.4%, making it clear the sample was far too small for any statistical conclusion. What's most interesting isn't the numbers themselves — it's the uncertainty: nobody yet knows what's good, bad, or normal in this inventory.

That sums up the moment well.

Everyone is looking at this platform trying to figure out whether they're watching the beginning of a new Google Ads — or just another expensive awareness channel.

Conclusion: GPT Ads Was a Major Disappointment — At Least on First Contact

After configuring the first campaigns, my honest impression is: GPT Ads was a significant disappointment.

I expected more from the company pioneering artificial intelligence. Not necessarily a perfect platform — every new product starts with limitations. But I expected a smarter, more fluid experience, one more aligned with what OpenAI seemed to represent.

What I found was an ad platform that, in many ways, feels like it came out of the early 2000s. It resembles the old Google Ads — back when it was still called Google AdWords — but with an AI layer behind the promise, not necessarily behind the operation.

Few targeting options. Still-basic campaign objectives. A limited configuration flow. Bugs in simple permissions, like swapping the account logo. Manual review dragging on. Little clarity on how the system actually understands context, intent, and traffic quality.

And that's the most frustrating part: GPT Ads shouldn't just feel like another Ads Manager. It should feel like the natural evolution of advertising in an AI-mediated internet.

Right now, it doesn't.

It feels like a very early beta — enormous potential, but still locked into an old paid media logic: launch a campaign, pick a simple objective, wait for approval, track clicks, and hope the data starts making sense.

Even so, I've already set up the first campaigns and I'll be watching everything closely. I want to understand not just the obvious numbers — impressions, CTR, CPC, and traffic — but especially the real quality of visits, user intent, post-click behavior, and whether there's any practical edge to advertising inside a conversational experience.

Soon, I'll share the insights from the strategy I used: what worked, what didn't, where GPT Ads looks promising, and where — at least for now — it still looks more like hype than revolution.

My initial takeaway is simple: GPT Ads deserves to be watched, but not to be worshipped.

OpenAI has the opportunity to create an entirely new advertising category. But in this first contact, the feeling is that they delivered a platform with the ambition of the future and the execution of the past.

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