AI Has Lowered the Cost of Building Software, but Enterprise Governance Hasn’t Caught Up

AI DRIVING DOWN SOFTWARE DEVELOPMENT COSTS

Artificial Intelligence (AI) has fundamentally transformed the landscape of software development, leading to a dramatic reduction in costs. Traditionally, the process of building software was seen as a resource-intensive endeavor, often reserved for organizations with extensive engineering capabilities and significant financial resources. However, recent advancements in AI-assisted development have made it possible for virtually anyone to create software at a fraction of the previous cost. The cost of coding has reportedly dropped to zero, enabling a broader range of individuals and organizations to engage in software development.

This shift in the cost structure has been highlighted in Retool’s 2026 Build vs. Buy Shift Report, which indicates that the time and financial investment required to develop custom software has significantly decreased. Where it once took weeks or even months for engineering teams to deliver a custom internal tool, it is now feasible for an operations lead to produce a working prototype in just a day or two. This capability is a direct result of AI innovations that streamline the development process, making it more accessible and efficient.

ENTERPRISE GOVERNANCE FAILING TO KEEP PACE WITH AI INNOVATIONS

Despite the rapid advancements in AI that have made software development more cost-effective, enterprise governance models have not evolved at the same pace. Organizations are still operating under traditional governance frameworks that were designed for a time when building software was a complex and costly endeavor. This disconnect presents significant challenges, as enterprises struggle to adapt their governance structures to accommodate the new realities of AI-driven development.

As companies increasingly turn to custom-built solutions, the lack of updated governance policies can lead to inconsistencies and potential risks. There is a pressing need for enterprises to reassess their governance models to ensure they align with the capabilities and implications of AI-assisted development. Failure to do so may result in missed opportunities for innovation and efficiency, as well as increased vulnerability to compliance and security issues.

THE IMPACT OF AI ON THE BUILD VS. BUY DECISION IN ENTERPRISES

The advent of AI has fundamentally altered the build vs. buy decision-making process for enterprises. Historically, purchasing software from vendors was perceived as the safer and more cost-effective option. However, with the significant reduction in the cost of building custom software, this paradigm is shifting. Retool’s report reveals that 35% of teams have already replaced at least one SaaS tool with a custom-built solution, and a staggering 78% plan to increase their custom tooling efforts by 2026.

This shift is particularly pronounced in sectors where specific needs cannot be met by generic software solutions. As the cost of building custom applications continues to decline, enterprises may increasingly favor building over buying, leading to a more tailored approach that better meets their operational requirements. This trend not only reflects a change in financial calculations but also a broader cultural shift towards valuing customized solutions that can adapt to unique business challenges.

HOW AI-ASSISTED DEVELOPMENT IS TRANSFORMING CUSTOM TOOL CREATION

AI-assisted development is revolutionizing the way organizations create custom tools, enabling faster and more efficient processes. The integration of AI technologies into development platforms allows users to leverage machine learning algorithms and automation to streamline workflows and enhance productivity. This transformation is particularly beneficial for operations leads and other non-technical stakeholders who may not have extensive programming backgrounds.

With AI tools, the barriers to entry for software development have been lowered, allowing more individuals within an organization to participate in the creation of custom applications. This democratization of software development means that teams can respond more rapidly to changing business needs, creating tools that are specifically designed to address their unique challenges. As a result, the reliance on generic SaaS solutions is expected to diminish, paving the way for a new era of customized software solutions driven by AI.

RETOOL'S REPORT: A SHIFT TOWARDS CUSTOM SOFTWARE SOLUTIONS

Retool's 2026 Build vs. Buy Shift Report provides critical insights into the ongoing transformation in software development. The report highlights that a significant number of organizations are already making the transition from off-the-shelf software to custom-built solutions. This trend is indicative of a broader recognition of the limitations of generic software in meeting specific operational needs.

The findings of the report underscore the urgency for enterprises to embrace custom software development as a viable alternative to traditional SaaS solutions. As the cost of building software continues to decrease, organizations are recognizing the potential benefits of developing tailored applications that can enhance efficiency and drive innovation. This shift not only reflects a change in financial considerations but also signifies a strategic pivot towards a more agile and responsive approach to software development.

ADDRESSING THE DISCONNECT BETWEEN AI COST REDUCTION AND SAAS PRICING

One of the most significant challenges arising from the shift towards AI-assisted development is the disconnect between the reduced costs of building software and the stagnant pricing of SaaS solutions. While the cost of developing custom software has plummeted, SaaS providers continue to charge per-seat fees for generic software that often requires additional customization and integration costs. This disparity creates a compelling case for organizations to reconsider their software procurement strategies.

As enterprises increasingly recognize the financial advantages of building custom solutions, they may begin to challenge the traditional pricing models of SaaS providers. The findings from Retool's report suggest that organizations are likely to continue moving towards custom-built tools, especially as they seek to optimize their operational efficiencies and reduce unnecessary expenditures associated with generic software. Addressing this disconnect will be crucial for SaaS providers as they navigate a landscape that is rapidly evolving due to the influence of AI.