AI Makes Software Cheaper. Quality Still Costs
This article discusses the limitations of using AI for software development, warning that while tools like LLMs speed up prototyping, they do not replace the need for professional expertise. The author cautions managers against the 'demo trap,' where simple AI-generated results mask the complexity of enterprise-grade software.
Why it matters
It challenges the prevailing narrative that AI has commoditized software engineering, highlighting the persistent value of human skill in complex business environments.
Leadership Strategies AI Makes Software Cheaper. Quality Still Costs By Esade Business & Law School ,
Forbes contributors publish independent expert analyses and insights. We set an example for a better future via education and research. Follow Author Jul 21, 2026, 08:30am EDT --:-- / --:-- This voice experience is generated by AI. Learn more . This voice experience is generated by AI. Learn more . Local and national artificial intelligence assistant is ready for duty Anadolu via Getty Images GETTY By Jose A. Rodríguez-Serrano is Professor at Department of Operations, Innovation and Data Sciences at Esade
A recent trend in the media and public debate is to portray the current state of AI as an era in which everyone can produce their own software.
Over the last two years, large language models (LLMs) for code generation have evolved into platforms or agent frameworks, behaving as increasingly capable software collaborators.
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