Generative AI has democratised code generation. Tools such as Claude Code and Codex allow users to describe what they want in natural language and produce functional software within minutes. For any business leader, the question is inevitable: why pay for a SaaS solution if anyone can now build one?
This is the premise of the whitepaper launched by UVE Solutions, entitled “It’s not the code you are buying. It’s the accountability”. In it, the company argues that when code generation becomes cheaper and accessible to everyone, as it is today, experience and accountability become more valuable.
Code gets cheaper; accountability becomes more valuable.
Anyone can generate code in minutes. What AI does not generate is what comes afterwards: an application is a living system that needs to be maintained, verified, secured and continuously updated. That is why the cost was never in developing software, but in keeping it running.
The data is clear: 45% of AI-generated code contains security vulnerabilities, many of which fall within the OWASP Top 10, according to Veracode’s 2025 GenAI Code Security Report. Meanwhile, 95% of enterprise generative AI pilot projects fail to reach production or have an impact on the bottom line, according to The GenAI Divide. State of AI in Business, an analysis by the MIT NANDA project at the Massachusetts Institute of Technology (MIT).
At the end of that same year, 2025, an autonomous Amazon agent deleted and rebuilt a production environment by itself, causing a 13-hour outage. If one of the most highly engineered companies in the world needs to put controls around the code generated by its own AI, the question is not whether you can build it. It is whether you can take accountability for it. A poorly calculated internal report can be corrected on Monday. The platform your sales team depends on to operate at the point of sale, manage distributors and launch the Christmas promotion cannot.
If that system failed at the worst possible moment, there would be only two scenarios. With a SaaS solution, there is a commitment, there are penalties, and there is someone on the other end with clear incentives to resolve it today. But if you built it yourself, only you are accountable for it.
The importance of governing AI
Let’s look at a case study. Your Head of Trade Marketing builds an agent that recommends actions by point of sale. Your Head of Sales automates alerts by combining distribution data with the forecast. An analyst builds a dashboard that calculates share of shelf. All three tools work. None have any obvious security vulnerabilities. And yet, no one has validated that the three calculate sell-out in the same way, or that they understand “coverage” to mean the same thing.
The chaotic Excel files of the 2000s are back, but they are no longer files that someone opens and interprets. They are agents that act autonomously. The question every business leader should ask is not a technical one, but a matter of business governance: how many of these tools already exist in your organisation without your knowledge, making decisions based on criteria that no one has validated?
AI dramatically accelerates teams that already know what they are doing, while amplifying the mistakes of those that do not. There is a clear difference between getting an answer and getting the right answer in the context of your business. In this regard, an expert in your sector tells you which numbers matter, in what order to look at them, what they mean. And they stand behind that answer. A general-purpose model gives you figures and, for example, does not know which questions you have not asked yet.
What are you really buying when you purchase a SaaS solution?
When you purchase a vertical SaaS solution, you are buying five things that no artificial intelligence can generate on its own:
- Living, accumulated domainexpertise: years of understanding how the sector works from the inside, including its exceptions and specific cases, something that cannot be learned from scratch.
- Real contractual liability: an SLA, contractualpenalties and a point of contact with clear incentives to respond when something goes wrong.
- The sum of countless invisible decisions made well:Infrastructure as Code, continuous security scanning, dependency management, active monitoring. None of this appears in a demo, but it is the foundation that allows a system to withstand real-world demands.
- Support throughout adoption: what enables a tool to transform a business is how it is adopted.
- The accumulated knowledge of an entire sector: a vertical SaaS solution learns from hundreds of customers at the same time. Those who build their own solution learn from their own mistakes, while those who choose a mature vertical SaaS solution benefit from the mistakes of the entire sector.
And therein lies the reason why AI does not erode the value of a solid platform, but rather reinforces it. The history of technology teaches the same lesson repeatedly: when the cost of building software falls, demand does not decline, it multiplies. It is the Jevons paradox applied to code. There will be more agents, more automation and more tools than ever before and, precisely because of this, the value of the robust, governed and reliable platforms on which all of this is built will increase.
Lines of code have never been cheaper. Experience and accountability have never been so valuable.
Download the whitepaper
Download the white paper “It’s not the code you are buying. It’s the accountability” and discover why generative AI will not replace experts, but will replace those without expertise.
About UVE Solutions
UVE Solutions is the technology partner of leading manufacturing and distribution companies in Spain, thanks to its ability to connect the different stakeholders across the fragmented channel value chain, including HORECA (hotels, restaurants and cafés), impulse and traditional channels. UVE supports these companies through an integrated Data Intelligence Automation model that enables them to successfully manage their Route-to-Market commercial processes. The company is the Spanish market leader and operates in more than 70 countries across Europe, the Americas, Africa and the Middle East.
