With AI, software development has become more agile and efficient

For decades, the decision between building a software from scratch or acquiring a ready solution guided technology strategies in companies from 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), modified all variables of this account. It is no longer a matter of deciding between two classic approaches, and perhaps the traditional dilemma no longer exists.

With generative AI optimizing crucial stages of the development cycle, such as code writing, automated testing, bug detection, and even architectural suggestions, building bespoke software is no longer a one-off effort for large corporations with robust budgets. Pre-trained models, specialized libraries, and AI-powered low-code or no-code platforms have dramatically reduced development costs and time.

Instead of months, many solutions today are delivered in weeks, and instead of numerous internal teams, lean, highly specialized teams can deliver custom and scalable applications with impressive efficiency. GitHub Copilot, released in 2021, is a practical example of generative AI that assists developers by suggesting code and completing snippets automatically. A GitHub study indicated that developers using Copilot completed 55% tasks faster on average, while those who used it took on average 1 hour and 11 minutes to complete the task, those who did not use GitHubilot took on average 1 hours and 2 minutes.

Given this reality, the old argument that buying ready-made software was synonymous with economics loses strength. Generic solutions, although tempting, often do not mold to the particularities 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, become barriers to innovation.

More than that, 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” as a strategic asset makes less and less sense. The real value lies in the solution architecture, the fluidity of integration with business systems, data governance, and especially the ability to quickly adapt software as the market, or company, changes.

The use of artificial intelligence (AI) and automation reduce up to 50% in development time, as pointed out by 75% of the executives interviewed in a report conducted by OutSystems and KPMG. But if “build” is the new normal, a second dilemma arises: to build internally or with specialized external partners? Here, pragmatism speaks louder.Creating a proprietary technology team requires continuous investment, talent management, infrastructure and, above all, the scarcest asset in the race for innovation. business it's not software, this choice can 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 reduction of 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 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 experts working on multiple projects accumulate technical and business repertoire 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 plastered solutions or building something that really meets what the business needs. Personalization, before a luxury, has become an expectation, scalability, a requirement, and AI, a game changer.

In the end, the real competitive advantage is not in the ready software, nor in the lines of code written to measure, but in the strategic agility with which companies integrate technological solutions to 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 this, it is not enough to build, it is necessary to build with intelligence, right partners and vision of the future.