Will AI turn Enterprise Software Development into a commodity? Not if it is customized

Software development is moving toward commoditization

A commodity is a standardized good or service that can easily be replaced by equivalent products and whose competitive value depends primarily on price. 

For decades, software development has been characterized by high barriers to entry: specialized skills, substantial investments, and significant development times. Today, Generative Artificial Intelligence, AI Coding Assistants, and Low-Code platforms are progressively changing this situation. 

According to Google’s 2025 DORA Report, 90% of the technology professionals surveyed use AI in their work, and more than 80% believe it improves their productivity.^[1].

As highlighted in an article published by Forbes Technology Council, AI is changing not only developer productivity but the entire economics of software engineering. When producing code requires fewer resources, the way the value of development is perceived also changes^[2].  

The risk of commoditization is therefore real, especially for repetitive and standardizable activities. 

But there is another perspective: if development costs decrease, why should companies settle for standard applications when they can afford software designed around their own needs? 

The more accessible development becomes, the more customized software can become

Traditionally, the relationship between standard software and customized software has been influenced above all by costs. 

Standard applications provide quick access to established features, spreading development costs across numerous customers. Custom software, on the other hand, makes it possible to create solutions designed around an organization’s specific processes and objectives, but generally requires greater investment. 

The reduction in software production costs could make it increasingly cost-effective to develop applications tailored to a company’s own workflows, rather than adapting to the features of standard products. 

This evolution meets a need already present in the Enterprise market: to differentiate through specific processes, data, and ways of operating. 

According to Gartner research on custom development services, the main reasons driving companies toward customized solutions include operational efficiency, improved customer experience, and competitiveness^[3].  

There are three main reasons: 

• Preserve distinctive processes. Custom software makes it possible to capitalize on the ways of operating that differentiate a company from its competitors. 

• Reduce organizational compromises. Instead of changing processes to adapt them to the features of a standard application, an organization can develop solutions that more closely match its needs. 

• Obtain greater value from IT investment. If development becomes more efficient, companies can demand greater customization, functionality, and quality for the same budget. 

This last point is also reflected in an analysis published by CIO.com, which examines how the economic benefits of AI are changing Enterprise customers’ expectations of software vendors, not only in terms of pricing but also quality, speed, and flexibility^[4].

The democratization of development could therefore encourage not only the spread of software, but also the spread of its customization. 

Code can become a commodity. Software engineering cannot.

Producing code quickly does not, however, automatically mean building a reliable Enterprise application. 

Business software development requires an understanding of processes, the definition of architectures, integration with existing systems, and the management of security, quality, and maintenance requirements. 

As Forbes points out, lower implementation costs progressively shift value toward activities such as architecture, integration, verification, and problem/requirements definition.^[2]  

Google, through its DORA program, also highlights how AI can amplify both the strengths and weaknesses of existing development processes. Accelerating code production therefore does not automatically guarantee greater quality and reliability^[5].

Our experience in Low-Code development has taught us that the value of custom software does not depend on the amount of code written manually, but on the ability to create solutions that meet specific business needs and remain sustainable over time. 

And this still requires software engineering. 

The future will not necessarily mean the same software for everyone

Artificial Intelligence is making code production increasingly accessible and some development activities progressively more standardizable. 

But the commoditization of code does not necessarily imply the commoditization of Enterprise software development. 

Organizations will continue to have different processes, objectives, and needs, which may require customized solutions. 

In Enterprise software, this dynamic could become even more relevant: AI and Low-Code can help make custom applications economically sustainable for a growing number of companies. Bringing the two technologies together creates a system that enables greater productivity not only in development but also in maintenance, while ensuring the security and quality of the result. 

Because the true outcome of the democratization of software development may not be enabling everyone to have the same application, but enabling every company to have the one it truly needs. 

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Sources

[1] Google DORA (2025) — State of AI-assisted Software Development 2025.

[2] Forbes Technology Council (2026) —  Luis Aburto, AI Is Changing The Economics Of Software Engineering, Not Just Developer Productivity, October 16, 2026.

[3] Gartner (2025) — Peer Lessons Learned for Custom Software Development Service Implementation, June 30, 2025.. 

[4] CIO (2026) — Grant Gross, AI is altering the economics of software development, but who gets a cut?, March 31, 2026.

[5] Google DORA (2026) — Balancing AI tensions: Moving from AI adoption to effective SDLC use, March 10, 2026.