A new set of industry forecasts suggests that OpenAI could have more than 220 million paying users by the end of this decade. Despite the scale projected for its subscription business, analysts say the company may still face challenges in achieving sustainable profitability due to the high cost of running advanced artificial intelligence models. The reports highlight the financial pressure associated with maintaining and expanding large data center infrastructure, particularly as user adoption increases across global markets.
The projections indicate that the majority of paying users will come through subscription offerings such as ChatGPT Plus, enterprise plans and upcoming tiers designed for specialised use cases. The forecasts take into account the rapid acceleration of generative AI adoption since 2023 and the increasing reliance on conversational assistants in education, productivity, creative work and customer support. With generative AI becoming a mainstream digital tool, analysts believe subscription models will remain central to OpenAI’s revenue strategy.
However, even with strong growth in subscriptions, the reports show that operational expenses will continue to rise at an equal or faster rate. Running large language models involves extremely high computational requirements, constant model updates, large scale GPU clusters and investment in reliability and safety systems. According to analysts, these factors may continue to outpace revenue unless significant breakthroughs in efficiency or infrastructure design emerge. Several research notes suggest that OpenAI’s data center requirements could run into hundreds of billions of dollars over the next decade.
The analysis also points to the growing costs of training next generation models. Larger multimodal systems require substantial computational power not only during initial training but through continuous learning and alignment cycles. Industry experts estimate that each new frontier-scale model exceeds the training cost of its predecessor, adding pressure to the company’s long term financial structure. While partnerships with major cloud providers help share infrastructure load, they also introduce dependency and cost sharing complexities.
At the same time, the forecasts acknowledge the company’s ability to expand into new revenue pathways. Enterprise demand for advanced AI features continues to grow, especially in sectors such as financial services, retail, healthcare and technology. Organisations are increasingly integrating ChatGPT into workflows through APIs and custom AI agents. These enterprise channels are expected to become one of the strongest contributors to revenue, offering steadier margins than consumer subscriptions.
OpenAI’s leadership has previously indicated that the company expects to scale both consumer and enterprise services while continuing to invest heavily in model development. This includes new capabilities such as autonomous agents, multimodal reasoning, advanced personalisation and domain-specific versions of ChatGPT. Industry watchers believe these features will help expand the paying user base but may also raise operational expenses due to higher computational requirements.
The report also highlights regional differences in subscription adoption. Markets such as the United States, Europe and parts of Asia continue to show strong willingness to pay for premium AI tools. India, with a rapidly growing AI-literate population, has emerged as one of the most active user bases for free and paid ChatGPT tiers. Business users in India, particularly in SMEs, technological services and education, have become strong contributors to subscription growth. Analysts say that adoption patterns in India may influence pricing and product strategies in other emerging markets.
Economists studying the AI sector argue that OpenAI’s challenge reflects a broader trend across the generative AI industry. While demand continues to rise, the economics of model development are still evolving. High infrastructure cost remains a common barrier for companies building advanced AI systems. The industry is closely watching developments in AI-specific hardware, energy efficient data centers and model optimisation techniques that could help improve margins.
Some financial analysts also point to the competitive landscape. Major players including Google, Anthropic, Meta, Amazon and several Chinese companies have launched their own large scale AI systems. Many competitors are offering free or lower priced subscriptions, which could influence OpenAI’s pricing strategy and revenue forecast. While OpenAI currently benefits from high brand recognition and early market advantage, continued innovation will be necessary to maintain and grow its paying user base.
The reports predict that OpenAI will continue expanding its model offerings, partnerships and enterprise solutions to support revenue growth. They note, however, that long term sustainability will depend on balancing innovation with efficiency. As more users rely on AI tools for daily work and personal productivity, expectations for reliability and speed are likely to increase, adding to the operational burden on providers.
The forecast’s central conclusion is that OpenAI may become one of the world’s largest subscription technology platforms by 2030, with a paying user base that rivals major consumer services. However, profitability is not guaranteed. The path ahead will require careful management of costs, breakthroughs in infrastructure and the ability to scale responsibly without compromising performance or safety.
As generative AI continues to embed itself deeply in global digital ecosystems, the economic models of leading AI companies will be closely monitored. OpenAI’s trajectory is expected to influence broader industry trends, including pricing, innovation cycles and infrastructure investment across the AI landscape.