AI tools target cloud risks in government systems

As public sector organizations race to modernize, cloud adoption has become essential, but also fraught with risk, according to Forbes.

Misconfigurations, compliance lapses, and cyberattacks threaten critical infrastructure and citizen data, with 81% of organizations reporting cloud security incidents in 2022 alone. While many agencies turn to AI for help, generative AI presents its own challenges. Though useful for templating and documentation, generative models can produce code that violates policies or introduces vulnerabilities due to their probabilistic nature. In contrast, deterministic AI offers a safer alternative by using predefined rules to deliver consistent, auditable outputs aligned with organizational standards. Tools based on deterministic AI can scan infrastructure-as-code, detect misconfigurations, and automatically suggest compliant fixes. However, successful implementation requires clear policy definitions, integration with existing workflows, and an understanding of its scope limitations. As Gartner begins to recognize the strategic role of deterministic AI, public agencies must weigh both AI types carefully to mitigate risk, improve efficiency, and ensure secure digital transformation.