For decades, the decision to build software from scratch or to acquire a ready-made solution has guided technology strategies in companies across various sectors. The equation seemed simple: buying accelerated adoption and reduced costs, building offered customization and control. But the arrival of generative artificial intelligence, and especially AI-assisted development (AIAD), has changed all the variables of this equation. It's no longer about choosing between two classic approaches, and perhaps the traditional dilemma no longer exists.
With generative AI optimizing crucial stages of the development cycle, such as coding, automated testing, bug detection, and even architecture suggestions, custom software development is no longer an effort exclusive to large corporations with robust budgets. Pre-trained models, specialized libraries, and low-code or no-code platforms powered by AI have drastically reduced development costs and time.
Instead of months, many solutions are now delivered in weeks, and instead of large internal teams, lean and highly specialized teams can deliver customized and scalable applications with impressive efficiency. GitHub Copilot, launched in 2021, is a practical example of generative AI that assists developers by suggesting code and automatically completing snippets. A GitHub study indicated that developers using Copilot completed tasks 55% faster on average, while those who used it took an average of 1 hour and 11 minutes to complete the task; those who did not use GitHub Copilot took an average of 2 hours and 41 minutes.
Given this reality, the old argument that buying ready-made software was synonymous with savings loses strength. Generic solutions, although tempting, often do not adapt to the specifics of internal processes, do not scale with the same agility, and create a limiting dependence. In the short term, they may seem sufficient, but in the medium and long term, they become obstacles to innovation.
Moreover, the very notion that competitive advantage lies in the code itself begins to crumble. In a scenario where rewriting an entire application has become cheap and feasible, the idea of "protecting the code" as a strategic asset makes less and less sense. The true value lies in the architecture of the solution, in the fluidity of integration with business systems, in data governance, and, most importantly, in the ability to quickly adapt the software as the market or the company changes.
The use of artificial intelligence (AI) and automation reduces development time by up to 50%, according to 75% of executives surveyed in a report conducted by OutSystems and KPMG. But if "build" is the new normal, a second dilemma arises: build internally or with specialized external partners? Here, pragmatism speaks louder. Creating an in-house technology team requires continuous investment, talent management, infrastructure, and above all, time—the scarcest asset in the race for innovation. For companies whose corebusinessis notsoftwarethis choice can be counterproductive.
On the other hand, strategic partnerships with development companies offer advantages such as immediate access to advanced technical know-how, accelerated delivery, hiring flexibility, and reduction of operational overhead. Experienced outsourced teams act as an extension of the company, focused on results, and often come with ready-made scalable architecture models, integrated CI/CD pipelines, and tested frameworks—everything that would be costly and time-consuming to build from scratch. It is also worth mentioning a third element in this equation: the network effect of accumulated expertise.
While internal teams face a continuous learning curve, external specialists working on multiple projects accumulate technical and business expertise at a much faster pace. This collective intelligence, applied in a targeted way, often generates more effective and innovative solutions. The decision, therefore, is no longer between buying or building, but between sticking to rigid solutions or building something that truly meets the business's needs.Customization, once a luxury, has become an expectation; scalability, a requirement; and AI, a game-changer.
In the end, the true competitive advantage is not in ready-made software or in custom-written lines of code, but in the strategic agility with which companies integrate technological solutions into their growth. The era of AIAD invites us to abandon binary dilemmas and think of software as a continuous, living, and strategic process. And, for that, it's not enough to build; you must build with intelligence, the right partners, and a vision for the future.
