AI is prompting dramatic evolution in every corner of business, from the way data is prepped and processed to the very architecture it resides. DBAs are equally at the whim of AI’s disruption, whereas database management strays farther from traditional maintenance, DBAs must acquire new skills to adapt.
DBTA’s webinar, The Impact of AI on the DBA, illustrated the new challenges and opportunities facing DBAs in the AI era, featuring expert perspectives on the skills, tools, and mindsets required for DBA success.
According to Amit Parikh, strategic solutions principal sales engineer, Quest, a growing anxiety for DBAs and database professionals is that AI can eliminate their roles in the enterprise. For more technical roles with structured, repeatable processes, these fears are certainly founded.
However, Parikh argued that with AI, the future of the DBA is augmented, not automated. Meaning, the DBA role is not replaceable; a DBA’s human judgment, inner business context, and the capacity for strategy is invaluable. The idea, according to Parikh, is that AI offers DBAs a chance to evolve into something greater: It’s a chance to “not just survive artificial intelligence but thrive with it.”
Parikh explained that the consensus regarding AI and the DBA is that AI is a tool, not a replacement. “It still takes a knowledgeable DBA to validate results and apply them correctly. As one DBA put it: AI won't replace DBAs, but DBAs who leverage AI might replace those who don't,” Parikh said.
Some ways the generative AI (GenAI) can be valuable for DBAs include:
- Explaining legacy SQL: Save hours of reverse-engineering by pasting cryptic SQL into tools such as ChatGPT or Toad's AI Explain feature to get step-by-step explanations.
- Tuning slow queries: Ask GenAI to identify issues with slow SQL and suggest improvements. Even if some suggestions are wrong, there is still significant time saved in triaging. Plans should still be validated manually.
- Writing routine scripts: Generate scripts for common tasks such as cleaning logs or creating portable templates across different database platforms. This handles more mundane processes so you can focus on critical thinking.
“Being a DBA isn’t what it used to be,” said JP Chen, senior director and global practice leader, SQL Server Services, Datavail. Echoing Parikh, AI’s main focus in DBA processes is overtaking tedious, manual tasks—such as index tuning, query optimization, and monitoring and alerting—so that DBAs can focus on more value-adding, critical tasks—such as those related to data architecture, cloud migration, and data governance and FinOps.
AI “cannot replace human judgement," Chen highlighted, listing the following as processes that are still human-critical for the DBA:
- Understanding business context
- Responding to unusual data patterns
- Designing scalable architectures
- Holistic workload optimization
With these processes in mind, new DBA skills are rising in importance, such as:
- Cloud platform fluency (Azure, AWS, GCP)
- Understanding AI/ML fundamentals
- Using AI-enhanced tools (Copilot, Query Store, Database Watcher)
- Various soft skills, including influencing, communicating insights, collaboration
Ultimately, “AI is powerful, there's no doubt about it…it’s a powerful assistant,” said Chen. However, “DBAs are still in the driver seat when it comes to context, strategy, and big picture thinking.”
Matt Shelvock, product advocate, Datavail Techboost, Datavail, then illustrated how Datavail’s DBAs are leveraging TechBoost—Datavail’s internal, AI-driven platform for database and application availability—to augment DBAs with AI. It reflects an important shift in the role, from technical to strategy—less firefighting and more forward thinking.
This is only a snippet of the full The Impact of AI on the DBA webinar. For the full webinar, featuring more detailed explanations, success stories, a Q&A, and more, you can view an archived version of the webinar here.