ChatGPT: When OpenAI's Strategy Reveals Its Flaws

ChatGPT: Illusory Performance

The latest version of ChatGPT, GPT-5.2, has recently achieved impressive results across nearly all industry benchmarks, nearing perfection. However, these outstanding performances on paper do not translate into everyday user experience. Indeed, numerous testimonies on forums indicate a degradation in the quality of responses, erratic behavior, and a notable decline in conversational quality. This paradox between test scores and real-world experience raises questions about the direction OpenAI is taking.

The Limits of Benchmarks

Benchmarks are designed to evaluate specific skills such as formal reasoning, code completion, and document synthesis in controlled environments. However, they do not take into account crucial aspects like everyday reliability, consistency over long conversations, or suitability for professional use cases. It is precisely in these areas that users are noticing deterioration. Since the introduction of GPT-5.x, each update follows a similar pattern: a triumphant announcement followed by massive adoption, then a wave of complaints within 24 to 72 hours. This is not mere coincidence, but a warning signal.

A Strategy Focused on the Enterprise Market

Contrary to what one might think, GPT-5 was not developed for the general public, but to conquer the enterprise market, where Anthropic had already gained a significant lead. This strategic choice is understandable in the context of investor pressures and market maturity. However, the lack of transparency towards users, who continue to pay their subscriptions and structure their workflows around a tool whose parameters change without notice, is problematic. Industry sources indicate that GPT-5.2 was deployed in a hurry, sacrificing quality to respond to competition from Google.

Users Turning Away from ChatGPT

Data from 2026 shows a significant drop in ChatGPT's market share, falling from 60% in early 2025 to less than 45% in the first quarter of 2026. Over 1.5 million subscribers canceled their subscriptions in March 2026. These figures are not anecdotal; they reflect a loss of user trust, as users have begun to evaluate and compare available tools, marking an increased maturity in the market.

An Organizational Vulnerability

Companies should be concerned not about the temporary regression of a language model, but about the excessive reliance on a tool whose parameters can change without notice. Entrusting decision-making processes and internal training to a tool whose roadmap is not controlled is not a technological strategy, but a strategic abdication.

Towards a Rigorous Evaluation of AI Tools

The crucial question is no longer about choosing between "ChatGPT or another," but about defining objective criteria to evaluate AI tools integrated within an organization. These criteria include consistency over time, stability between versions, transparency of updates, documentation of changes, actual usage costs, data hosting, regulatory compliance, and reversibility. Organizations that take the time to test various models on their own use cases often discover that the models dominating the benchmarks are not necessarily the most reliable in everyday use. The true value of a tool is measured over time and in production, not just in rankings.