Openai’s decision to test advertisements inside Chatgpt signals a break from the era of heavily subsidized Artificial Intelligence and a pivot toward advertising as a primary revenue engine. After years of rapid model advances and user growth, major labs are confronting the reality that intelligence at scale carries escalating compute and infrastructure costs that grow with every new user and capability. Openai’s new approach means users may pay for a service that still shows ads, reframing chat assistants as ad surfaces and influence channels rather than purely neutral tools.
The financial pressure behind the move is explicit. Openai chief financial officer Sarah Friar said in a blog post that the company’s annualized revenue has surpassed 20 billion in 2025, up from 6 billion in 2024, with growth closely tracking an expansion in computing capacity. However, despite that growth, the company reportedly expects to rack up massive annual losses, including roughly 74 billion in operating losses in 2028 alone. These projections are tied to surging spending on chips, data centers, devices, and other compute infrastructure, which is pushing Openai to treat advertising and subscriptions as necessary pillars of a durable business model. At the same time, competitive pressure is intensifying, with Google’s Gemini 3 posting strong benchmark gains in multimodal reasoning, math, and code and growing to 650 million monthly users in October 2025, prompting Sam Altman to reportedly declare a “code red” to accelerate Chatgpt improvements.
Across the industry, companies are testing different ways to monetize Artificial Intelligence while managing user trust. Google is using Artificial Intelligence overviews to replace traditional “ten blue links” with synthesized answers that can embed “direct buy” buttons and offers, effectively turning its core search experience for 2 billion users worldwide into a more personalized ad surface, even as executives say the standalone Gemini app will remain ad free. Microsoft is positioning Artificial Intelligence as infrastructure, monetizing it primarily through Azure inference services, enterprise Copilot licenses, and subtle integrations into the Bing ad stack on Windows rather than through a standalone assistant. Anthropic is pitching Claude as an ad free, public benefit option for high value professional users, while Meta uses Llama internally to refine its massive ad system so ads feel closer to recommendations. Smaller players reflect similar tradeoffs, with Mistral focused on enterprise apis and Perplexity moving away from a criticized cpm based ad model in 2025 toward a paid Pro subscription in 2026. The article concludes that advertising is not a temporary detour but the economic destination for many Artificial Intelligence assistants, blurring the line between help and persuasion as systems infer user intent and integrate commercial influence directly into seemingly neutral guidance.
