AI is revolutionizing corporate infrastructure, automating tasks across the software delivery lifecycle. As organizations increasingly adopt AI agents for coding, migrations, configurations, and deployment, they encounter significant risks due to the agents’ speed and autonomy. Key concerns include permission creep, where over-privileged identities rapidly spread; schema changes executed without proper context; and unintended metadata alterations that destabilize systems. Additionally, AI-driven configuration drift occurs at machine speed, complicating consistent environments and rollback procedures. To mitigate these risks, it’s crucial to treat databases as governed code, incorporating version control, automated policy validation, and continuous drift detection. Forward-thinking solutions, like Liquibase Secure, focus on maintaining transparency and accountability in database management. As AI’s role in operations expands, establishing robust governance is imperative. Organizations must prioritize safe, structured evolution over unchecked speed to protect their data foundation from potential automated incidents, transforming databases into living systems shaped by intelligent automation.
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