For decades, the decision between building software from scratch or purchasing an off-the-shelf solution has guided technology strategies in companies across various sectors. The equation seemed simple: buying accelerated adoption and reduced costs, while building offered customization and control. But the advent of generative artificial intelligence, and especially AI-assisted development (AIAD), has changed all the variables in this calculation. It’s no longer about choosing between two classic approaches, and perhaps the traditional dilemma no longer even exists.
With generative AI optimizing crucial stages of the development cycle—such as code writing, automated testing, bug detection, and even architectural suggestions—building custom software is no longer an endeavor exclusive to large corporations with robust budgets. Pre-trained models, specialized libraries, and AI-powered low-code or no-code platforms have drastically reduced development costs and time.
Instead of months, many solutions are now delivered in weeks, and instead of large in-house 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 found that developers using Copilot completed tasks 55% faster on average, while those who did not use it took an average of 2 hours and 41 minutes to complete the task, compared to 1 hour and 11 minutes for Copilot users.
Given this reality, the old argument that buying off-the-shelf software was synonymous with cost savings loses its strength. Generic solutions, though tempting, often do not adapt to internal processes, scale as quickly, or create limiting dependencies. 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 is beginning 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 real value lies in the solution’s architecture, the fluidity of integration with business systems, data governance, and, above all, the ability to rapidly 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%, as highlighted by 75% of executives surveyed in a report by OutSystems and KPMG. But if ‘build’ is the new normal, a second dilemma arises: build in-house or with specialized external partners? Here, pragmatism speaks louder. Building an internal technology team requires continuous investment, talent management, infrastructure, and, most importantly, time—the scarcest asset in the race for innovation. For companies whose core business is not software, this choice may be counterproductive.
On the other hand, strategic partnerships with development companies bring advantages such as immediate access to advanced technical know-how, accelerated delivery, hiring flexibility, and reduced operational overhead. Experienced outsourced teams act as an extension of the company, focusing on results, and often come with ready-made scalable architecture models, integrated CI/CD pipelines, and tested frameworks—all of which would be costly and time-consuming to build from scratch. It’s also worth mentioning a third element in this equation: the network effect of accumulated expertise.
While in-house teams face a continuous learning curve, external experts working on multiple projects accumulate technical and business knowledge at a much faster pace. This collective intelligence, applied in a targeted manner, often generates more effective and innovative solutions. The decision, therefore, is no longer between buying or building, but between being tied 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 lies not in off-the-shelf software or 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—it’s necessary to build with intelligence, the right partners, and a vision for the future.
