The Future of Artificial Intelligence according to my opinion and analysis. Artificial Intelligence (AI) as a technological advancement is here to stay and will not disappear. However, there is a profound disconnect between the viability of the technology and the financial sustainability of those who provide it. The business model of the vast majority of current commercial AI companies is unsustainable in the long term; we are on the verge of a massive restructuring in which many corporations will go bankrupt or be forced to radically transform. This critical scenario is based on three key factors: false financial profitability, the physical limitations of the infrastructure, and the real redefinition of the labor market. Today, access to large commercial AI platforms (such as ChatGPT or Claude) is perceived as inexpensive or accessible. However, this scenario is artificial: the services are heavily subsidized by venture capital investors and tech giants that prioritize capturing market share over immediate profits.

Maintaining this infrastructure involves astronomical costs. Keeping servers running, processing billions of prompts daily, and cooling advanced data centers requires colossal budgets.

Frontier companies like OpenAI and Anthropic burn through billions of dollars more each year than they actually earn.

Data scientists and financial investors warn that the current model of unlimited consumption through a flat subscription (the classic "all you can do for $20 a month" scheme) is not economically viable when working with gigantic models of up to two trillion parameters. Eventually, the market will be forced to make a drastic decision: either subscription prices increase exponentially, or operating costs are cut aggressively to prevent the commercial bubble from bursting.

The crisis of commercial AI is not just a problem of financial balance sheets; it is a challenge of physics, natural resources, and material limits. The unchecked growth of cloud-based models is directly impacting the capacity of global power grids and the availability of water resources for cooling. The situation has reached such a point of saturation that, in key regions of the United States and Europe, fully completed and equipped data centers are sitting idle because local cities and industries lack the energy capacity to power them. Faced with this physical constraint, the market is being forced to pivot toward a more efficient alternative: small, local AI models (optimized structures of 10 billion parameters or less). These compact models represent the sustainable future of the technology. By running natively on the user's hardware (whether on a mobile phone or a desktop computer), they eliminate latency, guarantee data privacy, and smoothly handle more than 80% of everyday computing tasks such as summarizing texts, drafting documents, or assisting with code writing. Most importantly, they operate without consuming cloud energy or generating infrastructure costs for a third party.

On the other hand, alarmist narratives claiming that AI arrived with the sole purpose of massively destroying jobs have been greatly exaggerated by marketing strategies and sensationalism. Contemporary AI is not a conscious or autonomous entity; it is a highly advanced statistical tool.

Instead of an automated replacement of human personnel, the current corporate landscape is experiencing the phenomenon known as "worklop." This occurs when employees use generative AI tools without proper supervision or technical expertise, producing a massive volume of texts, reports, or code of mediocre quality or riddled with structural errors. Far from dispensing with professionals, companies are being forced to hire or reassign specialized humans with the sole function of auditing, hunting down, and correcting the "hallucinations" and inconsistencies of the machines. AI will not destroy jobs across the board, but rather redefine the nature of professional roles. Those under real threat of disappearing are those agencies or companies whose business model depends exclusively on charging for mechanical, repetitive, and low-value-added tasks that a language model can structure and solve in a matter of seconds. In the medium term, we will witness a thorough cleansing and purging of the technology ecosystem. Hundreds of applications, secondary tools, and startups that currently operate simply as a "cosmetic layer" or wrapper built on top of third-party APIs will go bankrupt when large infrastructure companies cut subsidies and adjust prices to the true cost of computing. The market will gravitate toward the permanence of two main trends: on the one hand, AI seamlessly and natively integrated into the software that is already part of everyday workflows (operating systems, development environments, and database engines); on the other hand, and with increasing force, open-source and local architecture models. These local solutions will allow users, professionals, and developers to maintain complete control over their data and run advanced processes on their own hardware, achieving true technological sovereignty without relying on a credit card or a monthly cloud subscription.

What do you think?