In 2026, the landscape of database development is shifting with the increasing reliance on AI tools. Many developers are moving away from traditional coding to overseeing AI agents that generate and debug code. A key point raised is the stability of SQL as a language, which makes it easier for AI to handle database tasks compared to application development. However, the reality of many existing databases is chaotic, with poor documentation and inconsistent designs, complicating AI's ability to navigate them effectively. Certain types of database work require a high level of security and precision. While AI can manage simpler tasks, mission-critical applications—like those involving tax calculations or patient assignments—demand exacting accuracy. The article notes that database development tools remain subpar, lacking the integration of robust AI capabilities. Reporting tools, on the other hand, are more competitive and likely to adopt AI faster, potentially leading to significant changes in how data is handled. Looking ahead, data engineers and report developers are poised to be the primary users of AI in this space. They are likely to benefit from faster processes and improved efficiency. Meanwhile, established database developers dealing with complex, undocumented systems will still find themselves heavily involved in hands-on work. The complexity of new applications will grow over time, further necessitating human intervention in query writing as the original context of AI-generated schemas gets lost.