AI Redefines Tech Teams: An Inevitable Transformation

The Impact of AI on Software Production

Artificial intelligence is not just improving productivity in the tech sector; it is causing a profound upheaval in how software is designed and developed. Technical teams are now faced with the necessity of reorganizing their workflows to remain competitive and continue to generate value.

On February 5, Anthropic unveiled a new version of its tool Claude, often described as a more efficient co-pilot. However, this description does not do justice to the magnitude of the ongoing change. This is not merely an enhancement of an existing tool, but a radical transformation of software production, now partially supported by automated systems. This shift has deep economic implications.

A Major Economic Transformation

Studies conducted by AlixPartners reveal that AI can achieve productivity gains of 20 to 30% in software development. Meanwhile, Goldman Sachs predicts that these technologies could capture a significant share of the sector's value by 2030. IDC, an analyst firm, anticipates a reworking of pricing models for the majority of software publishers. Apollo Global Management, one of the largest global investment funds, mentions a drop in the marginal cost of production.

Taken together, these figures outline a clear trend: a continuous decrease in production costs. In any industry, such a reduction leads to a reconfiguration of the economic balance. Margins shrink, business models tighten, and traditional competitive advantages weaken. This phenomenon affects not only agencies and publishers but also scale-ups, large companies, and IT departments managing sizable teams.

The Inadequacy of Traditional Structures

Technical teams are often organized to handle a high volume of production. Agile practices come and go, performance indicators provide reassurance, and the machine keeps running. However, with the increasing automation of technical tasks, the question is no longer how much is produced, but how it is done.

Industry analyses predict that by 2026, 70 to 80% of routine technical tasks could be automated. This means that human contribution to task execution is diminishing, while the organization remains unchanged. Developers who merely execute tasks without understanding the product are already working on the most automatable parts of the chain. Project managers who do not take into account the new capabilities offered by AI are making decisions within an outdated framework. Even technical leads who spend too much time coding rather than designing dilute their added value.

Thus, the gap widens between those who adapt their production methods and those who merely accelerate the old model.

Value Beyond Volume

The real risk is not producing less, but producing more without qualitative improvement. With the acceleration of execution, the temptation to increase the number of features, deliveries, and parallel projects is strong. However, volume does not guarantee value creation and may even mask a dilution of product coherence.

Historically, the complexity of tech projects, dependence on expertise, and non-negotiable deadlines have allowed for a certain opacity. AI changes this dynamic by making production costs visible and compressible. Financial departments now demand more rigorous justifications regarding team sizes, project durations, and impacts on financial results. This dialogue will intensify, putting pressure on organizations that confuse activity volume with real value creation.

A Model to Reinvent

Today, tasks that once took weeks can be completed in a few days thanks to AI. Entire modules can be quickly reworked, tests generated automatically, and new features explored without mobilizing an entire team. This acceleration transforms the pace of product design and iteration.

We are entering an era where code becomes an abundant resource, losing its power of differentiation. What will remain valuable is the ability to understand complex problems, formulate relevant hypotheses, make informed decisions, and take strategic choices.

AI is not the main threat but rather a revealer of an existing gap. Companies that continue to focus on execution will see their margins shrink and their relevance diminish. Those that shift value towards thinking, architecture, and impact will gain a difficult-to-catch advantage. The question is not whether AI will transform your teams, but whether your organization is still suited to a world where execution costs almost nothing.