Oracle NetSuite is adding AI capabilities to SuiteCloud to help developers customize its ERP platform faster using natural language prompts.

In a statement, the company said its NetSuite SuiteCloud Agent Skills “will make it easier for developers to create customized vertical and industry-specific applications by giving AI coding assistants a better understanding of the conventions, patterns, and best practices in SuiteCloud – NetSuite’s standards-based AI extensibility and customization platform.”

The new skills give AI coding assistants NetSuite-specific development guidance, including UI framework references, permission codes, SuiteScript fields, documentation practices, OWASP security guidance, and tools to help migrate older SuiteScript 1.0 code to SuiteScript 2.1.

This comes as developers increasingly use AI coding assistants in their daily work. Stack Overflow’s 2025 Developer Survey found that 84% of respondents were either using or planning to use AI tools in their development process, up from 76% a year earlier.

The tougher challenge for enterprise software vendors is making those tools understand how business applications actually work. For platforms like NetSuite, useful AI assistance requires knowledge of the platform’s own APIs, permission models, UI conventions, and business workflows. In ERP systems, even a small customization error can ripple into core business operations.

Impact and adoption challenges

NetSuite said it is “introducing SuiteCloud development guidance across more than 25 AI coding platforms.” Analysts said this could reduce friction for developers by making NetSuite-specific knowledge available across widely used AI coding tools, rather than limiting it to a single vendor-controlled environment.

“If you can package platform-specific knowledge in a format that drops into any of the major AI coding tools through an open framework, removing a lot of friction, that is great for enterprise developers,” said Neil Shah, VP for research at Counterpoint Research.

However, broader adoption across enterprise software platforms may depend on how ready vendors and customers are to switch from their long-established development practices.

“Enterprises have already invested in systems and personnel to build their applications using their own proprietary approaches,” Shah said. “We will have to see how soon vendors adopt this new approach and whether they are ready to let go of sunk costs and perhaps some personnel.”

In this sense, the technology may be more immediately useful for new applications or for modernization work around legacy systems, rather than for wholesale redevelopment of existing enterprise applications. Cost and governance are other important considerations.

“What the token economics will be as enterprises get up the learning curve remains to be seen, as the initial token burn rate is likely to be significantly higher,” Shah said. “Also, security and risk are big challenges here, as ERP apps are tightly coupled, and one small change in approach that does not work well with the proprietary stack could break downstream workflows and become a disaster.”

That means companies are likely to test such tools cautiously, especially for customizations that touch sensitive data. Shah said that enterprises will have to use this in a sandboxed environment to check for code hallucinations and to see what breaks in terms of business logic, security, or privacy.