The enterprise AI landscape is entering a new phase and moving beyond generative content creation. Agentic AI introduces systems that can autonomously plan, decide, act, and interact with tools and data to carry out complex tasks—offering opportunities for operational efficiency and process automation. However, this shift also introduces new risks around data exposure, tool misuse, and agent behavior.
To support this evolution,
Securiti has integrated with the NVIDIA Enterprise AI Factory. This collaboration allows enterprises to rapidly deploy agentic AI systems with essential safeguards already in place.
Securiti’s AI TRiSM platform extends risk mitigation, governance, and security controls across the AI lifecycle—from data ingestion to agent execution.
Data Governance as a Cornerstone of Trust
Securing agentic AI starts with understanding the data. Securiti automates the discovery and mapping of enterprise data sources, classifying sensitive information and preserving access permissions as data moves into vector databases or training repositories. This helps prevent agents from being exposed to inappropriate data during training or deployment. Fine-grained controls ensure only authorized users and agents access the tools and datasets they need—nothing more.
Securing Agent Behavior and Tool Access
Agentic AI systems derive much of their value from their ability to use tools to complete complex tasks. But this same capability can become a vulnerability if not properly governed. Without the right controls in place, agents may trigger unintended actions, access restricted systems, or pass along injection attacks—intentionally or otherwise. This shifts the focus of security to the behavioral layer, where intent, context, and execution converge.
“The ability to use tools makes Agentic AI powerful and able to handle complex tasks,” said
Chris Joynt, Director of Product Marketing at Securiti. “But access to tools also comes with risks if the AI ecosystem is not carefully secured. Overpermissioned agents could easily become problematic—it can be as simple as a user asking an agent to query a database the user should not have access to. A malicious user could also pass along injection attacks or gain access to sensitive data through agents.”
As agents gain more autonomy, the risk of unintended or malicious actions grows. “Agents that have greater autonomy to take action risk being compromised and acting on behalf of a malicious user,” Joynt added. “For example, in supply chain or invoice processing, an agent integrated with an ERP system might make an improper payment.”
To manage this risk, a layered approach is required—one that goes beyond prompt-level guardrails to include real-time visibility, tight access controls, and continuous policy enforcement. Monitoring agent access and tool usage becomes critical to maintaining trust and control in dynamic, multi-agent environments.
Empowering Partners to Act as Policy Enforcement Hubs
As enterprise AI environments grow more complex, MSPs and MSSPs are increasingly expected to move beyond infrastructure support and play a more active role in securing AI operations. Securiti is enabling these partners to serve as real-time policy enforcement hubs across distributed data flows and toolchains—rather than just backend service operators.
Securiti’s platform gives partners full visibility into enterprise data and AI assets by automatically discovering and mapping them across environments. “Securiti connects to various data sources and automatically classifies sensitive data, redacts or masks if necessary, and builds contextual data intelligence, including data lineage, access permissions, and usage,” explained Joynt. With this intelligence, partners can apply granular controls, safely filter data before it enters the AI ecosystem, and preserve access entitlements as data moves into systems like vector databases.
This capability allows MSPs and MSSPs to act as active intermediaries in the AI trust chain. By applying policy in real time across pipelines, they ensure that only authorized agents and users can access specific data or tools—enabling secure, compliant operations in an increasingly autonomous environment.
Trusted AI at Enterprise Scale
As agentic systems scale, enterprises will need visibility across multiple agents, tools, and data flows. Securiti’s AI Data+AI Command Center supports centralized monitoring and automated testing to ensure system integrity. It enables security teams and partners to manage risks in real time—even as agentic AI ecosystems become more interconnected and complex.
Agentic AI will continue to reshape how enterprises operate, but its benefits hinge on trust, visibility, and control. By integrating with the NVIDIA Enterprise AI Factory and enabling partners to enforce policy across the AI lifecycle, Securiti is helping organizations secure the path forward. As the underlying data remains at the core of AI operations, securing its use will define the success of autonomous systems going forward.
