AI-Powered SQL: How LLMs are Changing the Way We Write Queries

Large language models (LLMs) like ChatGPT and GitHub Copilot are rapidly changing how developers write SQL by making query generation faster, more intuitive, and more accessible. These tools can translate natural language into working SQL statements, offering a solid starting point for queries that would otherwise take longer to build from scratch. They also assist with complex joins, filtering logic, and suggest performance improvements, without the developer needing to sift through documentation or rely solely on memory.

Beyond generating code, LLMs are proving especially useful for debugging and learning. Developers can use them to explain what a query does, identify logical issues, or help junior team members grasp SQL concepts like window functions or aggregations. While these tools aren’t perfect, they function well as accelerators, helping consulting teams deliver value faster while reinforcing the foundational role of well-written SQL in any data-driven solution.

LLMs bring real advantages to SQL development, especially in environments like Oracle where queries can quickly become complex. For developers working under tight deadlines or in unfamiliar databases, having an AI assistant that can draft code or explain logic in plain English is a powerful productivity boost. In consulting, where speed often enhances client satisfaction, this kind of support helps teams move faster without sacrificing quality.

However, these tools come with clear limitations. LLMs often lack awareness of the specific schema, business rules, or performance requirements of a given project, meaning their suggestions can be syntactically correct but contextually wrong. They may struggle with Oracle-specific features like hierarchical queries (CONNECT BY), PL/SQL nuances, or advanced performance tuning. Most importantly, LLMs don’t replace the judgment and domain knowledge of an experienced developer. In a consulting context, their best use is as a force multiplier, helpful for accelerating development, but always requiring a human in the loop to ensure reliability, performance, and alignment with business goals.

In a recent Oracle APEX project, I was working on a query to join two tables, applying a condition to the second table. Because of how the query was structured, that condition had to go in the WHERE clause, but doing so unexpectedly filtered out rows I needed. After reviewing the logic without success, I turned to ChatGPT for help.

By describing the issue and sharing the query, I was able to get suggestions on restructuring it, including using a subquery or adjusting the join type. Through a few iterations and clarifications, the model helped me pinpoint the issue and revise the query to return the correct results. It wasn’t about getting a perfect answer right away, but about speeding up the troubleshooting process, and that’s where LLMs really shine.

While LLMs are powerful tools for accelerating SQL development, they’re best seen as collaborators rather than replacements. In many ways, AI functions like a junior developer or pair programmer: handling repetitive tasks, suggesting ideas, and providing instant feedback. But just like a junior teammate, it requires guidance, context, and review from experienced developers to ensure quality and alignment with business needs.

For IT consultants, this means our role is shifting from purely writing code to overseeing and refining AI-generated outputs. Deep understanding of database schemas, performance considerations, and business logic remains essential. Looking ahead, the integration of AI into IDEs and platforms like Oracle APEX will only deepen this partnership, automating routine steps while freeing developers to focus on complex problem-solving and strategic insights.

AI-powered tools like large language models are already transforming how developers approach SQL. Yet, despite impressive advances, they remain assistants rather than substitutes. The value of deep domain expertise, critical thinking, and nuanced understanding of business rules continues to be the foundation of successful IT consulting.

By embracing AI as a collaborator, not a competitor, consulting teams can accelerate delivery, improve quality, and empower both developers and clients. As these tools evolve and integrate further into various environments, the future of SQL development will be shaped by a new partnership — one that blends human judgment with AI efficiency to unlock greater business value.

At Zirous, our custom development team combines the power of tools like large language models with deep expertise in Oracle, APEX, and modern application development. We help businesses solve complex challenges, improve performance, and accelerate results with thoughtful, efficient solutions.Learn more about how Zirous can help you meet your business needs here: https://www.zirous.com/solutions/development/