Editor's Note: A version of this article was originally published in the March 2025 Edition of Cyber Defense Magazine.
Government agencies face significant pressure to modernize, driven by both legislative demands and constituent expectations for a digital-first experience. Advances in autonomous AI agents, like Salesforce's Agentforce, offer new ways to leverage Software as a Service (SaaS) to improve the cost-effectiveness, efficiency, and quality of government operations and services. To fully benefit from the power of agentic Artificial Intelligence (AI), agencies must fulfill their part of the SaaS shared responsibility model to properly protect their data. SaaS security is crucial for defending against increasing threats and complying with government mandates. It also ensures that AI agents have the necessary data confidentiality, availability, and integrity.
For example, if relevant data is missing when developing or delivering AI agents, the results will be incomplete or error-prone. If an organization doesn’t detect corrupted data and includes it in the development or use of AI agents, it can lead to inaccurate outputs (garbage in, garbage out). If sensitive data isn’t properly restricted or anonymized, it could be exposed through AI agents, either inadvertently or intentionally, compromising confidentiality.
Enhancing Protection
While security products that use an outside-in API-based approach are helpful, they aren’t sufficient for securing SaaS data. Robust SaaS data security requires a data-centric, bottom-up approach that includes data classification, risk prioritization, and rapid remediation. However, agencies often struggle with these data security tasks due to increasing data volumes, limited resources, and a lack of SaaS security expertise.
Fortunately, these are challenges that agentic AI can help alleviate. AI agents use conversational AI to empower users and other AI agents with quick and easy access to relevant security information. This reduces the need for deep security expertise, making it easier for users to find answers. By proactively recommending remediation steps and automating certain workflows, AI agents can streamline security processes and enhance efficiency. Government agencies can benefit from such solutions to help label sensitive data, identify high-priority risks, detect configuration drift, and streamline remediation.
Detecting Threats
The frequency, scale, and sophistication of threats impacting SaaS data are escalating, leading to unauthorized access and data destruction. The risks and impacts of data loss and corruption due to human error are also growing. AI-enabled attacks amplify these threats, and the increasing complexity and data use in AI systems raise the stakes. To keep pace with these trends, AI-driven alerting is essential to detect issues that could compromise the confidentiality, availability, and integrity of SaaS data. Reliable, actionable alerts allow autonomous AI agents to handle dangerous actions, improving security and resilience, and reducing the disruption, cost, and impact of SaaS data security incidents.
Incident Response and Recovery
Effective incident response and data recovery readiness are crucial for resilient SaaS data. Successful response and recovery depend on well-defined processes, trained personnel, and the right technology. Restoring SaaS data from backups can be challenging due to the intricate relationships between objects and the need to restore data into a live environment without disrupting ongoing operations. The right technology can precisely target and restore only the lost or corrupted data, leaving the rest untouched. Periodic incident response and data recovery drills improve an organization's ability to quickly return to normal operations when a problem occurs, and are often required by regulations.
Leveraging AI Agents
Autonomous AI agents can help organizations with ongoing SaaS data protection, including risk management and threat detection, increasing trust and data resilience. The faster organizations can leverage AI agents to enhance SaaS data security, the more time and opportunity they have to develop new agentic applications. These SaaS data security practices, powered by automation and AI, can help agencies avoid cyber attacks and compliance violations, and gain operational benefits such as better use of developer resources and higher ROI.
We’ve seen firsthand how AI implementation within government agencies offers numerous advantages. While enhanced data protection is essential, integrating AI agents improves constituent services, empowers employees, and boosts operational efficiency. Moreover, automation through AI that provides on-the-job guidance helps personnel develop valuable skills, understand AI concepts, and manage large datasets. This prepares them for a digital-first workforce, ultimately improving the quality, efficiency, and usability of government services.
The Future of AI Agents
While SaaS providers offer a powerful, secure platform and autonomous AI agents, government agencies must understand their role in the shared responsibility model to implement and maintain necessary security controls. In an evolving threat landscape, failing to protect SaaS data can cause damage, disrupt operations, and slow AI innovation. Agencies need to prioritize SaaS data security in their digital transformation efforts to ensure successful AI usage and associated benefits.
Trusted and resilient data is essential for successful applications of AI, which require accessible, reliable, relevant, and error-free data. AI-driven SaaS data security plays a key role in fueling innovation, freeing up time so that cloud specialists can focus on development of high-value projects, including leveraging autonomous AI agents.
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