In the public debate on the future of technology, a thesis that inspires euphoria in some and existential fear in others is increasingly common. Its content is deceptively simple: since artificial intelligence can generate complete application code in a few seconds, the marginal cost of software development drops to zero. In view of the fact that any user equipped with a sophisticated language model can reproduce the architecture of a powerful system in a single afternoon, traditional companies based on the Software as a Service model would supposedly lose their raison d’être. This vision is based on a fundamental cognitive error. Confusing code syntax with business service is a trap that ignores the essence of the modern digital economy.
The real value of software has never been in the binary instruction record itself, but in the promise that this record realises. The current fascination with free code is akin to the delight in the fact that paper and ink are cheap, which would supposedly render notarial contracts or financial analyses worthless. Meanwhile, the role of the traditional SaaS model is being dramatically strengthened. It is becoming a shield separating the customer from the chaos and unpredictability of generative algorithms.
When considering the economic foundation of this thesis, it is worth looking at the financial structure of mature technology companies. The belief in the imminent death of the industry assumes that the programming process accounts for the lion’s share of a company’s expenditure. Operational reality, however, draws a very different picture. In mature business models, the R&D budget typically oscillates around a quarter of total revenue, and the physical process of writing code itself is only a fraction of the engineering work. Most of the resources are consumed by architectural decisions, domain modelling and interpretation of intricate user requirements. The mathematics here are inexorable: the impact of artificial intelligence on the total cost structure is a few to several per cent in real terms. This is an optimisation, not a budget revolution.
Moreover, the savings generated at the code development stage are rapidly consumed by rising operational costs. Intelligence-based software does not operate in a vacuum; it requires enormous computing power. Each query to an intelligent system generates a cost higher than a traditional database reference. As a result, the barrier to entry for new players wishing to compete solely on the price of ‘free code’ remains extremely high. It is not possible to permanently undercut the market when process costs rise along with the ambitions of the algorithms.
In B2B relationships, trust is a rarer currency than computing power. Corporations do not pay for a collection of functions, but for system availability more than ninety-nine per cent of the time, for compliance with strict security standards, and for the certainty that data is processed according to the letter of the law. A clone of an ERP or CRM system generated by artificial intelligence remains just a digital mock-up. It lacks the legal background, certification and business continuity guarantees that constitute the operational security of the client.
However, the problem of ‘probable rightness’ arises. In critical sectors such as banking, medicine or global logistics, an outcome that is ‘almost right’ is in fact completely wrong. These systems require a deterministic backbone – a structure that will deliver the same predictable outcome every time, regardless of the circumstances. The truly desirable software is not that which has been written entirely by artificial intelligence, but that which has been designed to be managed safely and predictably by it.
It is worth emphasising, therefore, that the uniqueness of a solution does not come from the fact that it has code, but from the ability to turn technology into sustainable use value. The fear of devaluing the IT industry stems from the erroneous assumption that software is the end product. Meanwhile, software is merely the carrier of a service. As technology becomes more complex and unpredictable, customers will be willing to pay more and more for someone who will tame this complexity and take full responsibility for it. SaaS is undergoing a mature transformation. It is ceasing to be a tool for editing data and is becoming a guarantor of stability in an uncertain digital environment.
