Not long ago, database tools mainly helped developers write and format SQL. Features like code completion, syntax highlighting, and query navigation made editing queries faster. But writing, fixing, and improving queries was still the developer’s job.
That is starting to change. AI coding assistants are now helping developers draft code, explain errors, and suggest improvements. Some studies show developers finishing tasks more than 50% faster when using AI assistants, while surveys report productivity gains of 20–40% in daily work. And this change is no longer limited to application code. SQL development is starting to see the same shift.
The change is also reaching the tools developers already use. The dbForge 2025.3 release, for example, adds AI query assistance to dbForge SQL Complete, bringing AI support directly into SQL Server Management Studio.
Recent improvements to SQL development tools
The dbForge 2025.3 release includes several updates for everyday database work. These updates add support for the latest development tools, expand SQL syntax support, and introduce editor features that make working with SQL more convenient.
For SQL Server developers, the update adds support for the latest version of SSMS 22. It also includes editor features such as navigation markers and automatic wrapping of selected text in quotes, brackets, or parentheses, small changes that make large SQL scripts easier to edit.
Another important addition is AI support in dbForge SQL Complete. The dbForge AI Assistant is now built into dbForge SQL Complete, allowing developers to generate queries, review SQL, and make quick fixes directly inside SQL Server Management Studio.
dbForge SQL Complete meets AI-assisted development
For a very long time, dbForge SQL Complete has been adding features to SSMS that make writing and using SQL easier. These capabilities included everything from intelligent code completion, formatting tools, and query navigation, except AI. However, with the release of dbForge 2025.3, the dbForge AI Assistant is now directly built into the SQL development workflow, which adds another level of support.
Writing and improving queries
Writing SQL often involves multiple iterations. Developers may start with a basic query and gradually add joins, filters, aggregations, or nested subqueries while verifying table structures and column relationships.
AI assistance helps speed up this process. The assistant can read simple prompts and generate a first draft of a query that developers can review and adjust. It can also suggest query parts or other ways to write the query based on the database structure and nearby code.
This allows developers to focus more on the logic of the query rather than spending time building repetitive SQL patterns.
Troubleshooting and learning support
Debugging and refining SQL queries is another area where AI assistance can be useful. Developers frequently deal with syntax errors, inefficient joins, or queries that return unexpected results after joining several tables.
Analysis with artificial intelligence can help review a query, identify potential issues, and suggest improvements. This can help developers move more quickly from debugging to optimization, especially when working under tight deadlines.
The assistant can also explain parts of SQL or how databases work that developers might not know. Developers can get an explanation right where they are working instead of having to leave the editor to look through documentation. This lets them keep coding without breaking their flow.
Why AI matters for SQL development
SQL work is not just about writing queries. Developers often spend time understanding the database structure, seeing how tables interconnect, and fixing queries that return the unexpected results. In large systems with many tables, this can take a lot of time.
Artificial intelligence helps reduce that effort. It can generate a query from a simple description, explain what an existing query is doing, and suggest fixes when something goes wrong. It can also point out joins or filters that may cause slow queries.
This matters because SQL work often involves a lot of back and forth. Developers write code, see results, adjust it, and run it again until it works. AI speeds up this process.
However, the goal is not to replace database developers. Artificial intelligence works more like a support technology. It handles some of the repetitive parts of query work so developers can spend more time focusing on query logic, performance, and database design.
Final word
As databases grow and writing code gets harder, developers need ways to work faster without making mistakes.
Artificial intelligence tools are starting to help with this. Tools like the dbForge AI Assistant in dbForge SQL Complete show how this support can work directly inside familiar environments such as SQL Server Management Studio. Instead of changing how developers work, this technology is beginning to support the tools and workflows they already use.
As AI continues to improve, it will likely play a bigger role in database development—from helping with individual queries to helping developers design, troubleshoot, and improve complex data workflows.
