The global software industry is facing a fundamental shift as artificial intelligence makes it increasingly possible to develop applications that previously required large engineering teams, substantial financial investment and months of development.
Advances in AI-powered coding tools are challenging a business model that has supported software companies for decades. Businesses traditionally paid significant amounts to purchase applications or subscribe to software services because developing comparable solutions independently was expensive, technically demanding and time-consuming.
That calculation is beginning to change.
Modern AI systems can generate application code, design databases, build user interfaces, automate testing and assist with deploying software. As these capabilities improve, businesses are gaining more options for developing custom applications instead of purchasing existing products.
In an analysis published by InfoWorld, technology writer Andrew C. Oliver argues that the economic value of software is approaching zero as AI reduces the cost of creating functional alternatives to established commercial products.
The argument does not suggest that software has become worthless. Rather, it highlights the possibility that the code underlying many applications could become significantly cheaper and easier to reproduce.
For decades, software companies benefited from the complexity of development. Building a reliable application required skilled engineers, extensive testing, specialised infrastructure and ongoing maintenance. These requirements created barriers that protected established companies from smaller competitors.
Artificial intelligence is weakening some of those barriers by allowing developers and entrepreneurs to complete increasingly sophisticated engineering tasks with AI assistance.
A small development team can now use AI tools to accelerate the creation of business management platforms, customer relationship systems, administrative dashboards and other applications that previously required considerably more resources.
The implications are particularly significant for the Software-as-a-Service (SaaS) industry, where businesses typically pay recurring subscription fees to access applications hosted and maintained by external providers.
As AI-assisted development becomes more accessible, some organisations may begin questioning whether they should continue paying for software that can be recreated or customised at a lower cost.
However, the ability to generate application code is not equivalent to delivering a dependable commercial product.
Production software requires security controls, data protection, scalability, regulatory compliance, reliable infrastructure and continuous maintenance. Businesses must also consider the cost of integrating new applications with existing systems and supporting them over time.
These requirements mean that established software providers retain advantages beyond the code itself, including customer trust, operational expertise, support services and established business relationships.
Nevertheless, AI is changing how customers evaluate software purchases. Instead of paying primarily for access to standard features, organisations may increasingly demand measurable business outcomes, specialised capabilities and seamless integration with their operations.
This could place pressure on software companies whose products offer limited differentiation or depend heavily on functionality that AI tools can reproduce relatively easily.
At the same time, the transformation is creating opportunities for smaller technology companies and independent developers.
Entrepreneurs can increasingly build software products without immediately assembling large engineering departments, potentially reducing the financial barriers associated with launching technology businesses.
The shift could be particularly important in emerging markets such as Kenya, where development costs and limited access to capital have historically constrained some technology startups.
AI-assisted engineering may allow local companies to develop specialised solutions for schools, hospitals, retailers and other organisations at costs that were previously difficult to achieve.
However, successful businesses will still need to understand customer problems, maintain reliable systems and deliver consistent value. Artificial intelligence can accelerate development, but it does not automatically guarantee product quality or commercial success.
The industry may therefore be moving towards a future in which the ability to write code becomes less scarce while the ability to identify valuable problems and deliver trustworthy solutions becomes more important.
For software engineers, this transformation is also changing professional expectations. Developers increasingly need to understand how to supervise AI-generated code, evaluate technical decisions, identify security weaknesses and maintain complex systems.
Rather than eliminating the need for engineering expertise, AI is shifting more attention towards architecture, judgement, quality assurance and the management of automated development processes.
The value of software is not literally disappearing, but the economics of creating it are changing rapidly. As artificial intelligence makes development faster and more accessible, technology companies may increasingly compete on reliability, specialised knowledge, customer experience and the business outcomes their products deliver rather than the complexity of their code alone.
