Agentic AI creates control, technology, and purchasing problems. Security leaders need to know which controls they must satisfy, which technologies can satisfy them, where existing tools already provide coverage, and where a new investment actually fills a gap. Far too often, we see clients conducting that process in reverse order…trying to buy a technology and then mapping it to controls.

Most of our AEGIS guidance sessions eventually reach the same set of questions: which technologies do we need, which controls do they satisfy, and which vendors should we examine first?

Our latest research, Navigate AEGIS Technologies To Secure Agentic AI maps AEGIS controls to technologies, functionality, and vendors. We did this to give clients a cleaner, more effective path to follow for securing agentic AI.

Map AEGIS Controls To The Tech That Secures Agentic AI 

Securing agentic AI doesn’t mean that security teams have to discard their existing tech stack and start over. Many of the capabilities needed to secure agentic AI already exist in existing security tools (especially if you work with the large, acquisitive security platform vendors).

The problem comes from determining where that existing coverage ends and what to prioritize. To help address this, the report sorts the list by Must Have Now, Should Have Next, and Specialized & High Assurance Use Cases.

Some familiar technologies now support AI-specific use cases. Others provide only part of the required control. New categories fill gaps created by autonomous agents, tool calls, delegated permissions, model dependencies, and near instantaneous decisions.

A useful technology map should answer seven questions for each category:

  1. What the technology does
  2. Where it runs
  3. What it protects
  4. Which existing security technologies share similar capabilities
  5. Which AEGIS controls it supports
  6. Which NIST AI Risk Management Framework controls it maps to
  7. Which vendors clients can consider

Our new Navigate research covers 23 technology domains across the agentic AI stack. These domains include immediate priorities such as AI runtime security, AI detection and response, DLP for AI, AI security posture management, AI identity and access management, and AI GRC.

Start With Control Gaps Then Work Towards Products 

Security technology research usually starts with a product category. Buyers read a definition, review a market, compare vendors, and then try to connect the category back to a real control gap. Our Navigate research allows teams to reverse that sequence.

This report gives you a practical decision path through its methodology:

  1. Identify the missing or weak AEGIS control.
  2. Find the technology categories that support it.
  3. Review the required functionality and deployment location.
  4. Check for overlap with products already in the environment.
  5. Determine whether the organization can absorb the requirement into an existing platform or needs a dedicated investment.
  6. Use the sample vendor list to begin market research and evaluation.

Here’s An Example: AI Runtime Security 

Assume an organization identifies gaps in AEGIS controls covering runtime monitoring, unsafe agent behavior, prompt injection, data exfiltration, or high-risk tool actions.

These use cases are satisfied by AI runtime security.

What The Technology Does and What It Protects: AI runtime security monitors AI applications and agents while they execute. It collects model and tool-call telemetry, detects activity such as prompt injection, jailbreaks, data exfiltration, and anomalous actions, then applies policies to block, contain, redact, limit, or escalate the activity.

Where it runs: It may run at an AI gateway, API proxy, application runtime, agent framework plug-in, sidecar, or another inline enforcement point.

Which existing security technologies share similar capabilities: the report shows where AI runtime security overlaps with technologies such as AI Detection & Response (AIDR), AI DLP, and AI security posture management. That gives security leaders an opportunity to inspect their existing security tools before opening a new procurement cycle.

AEGIS and NIST AI Risk Management Framework alignment: Control mapping helps security leaders understand those boundaries before they commit budget.

This control-first view answers six questions that typically sprawl across separate research notes, meetings, emails, spreadsheets, slide decks, RFIs, RFPs, and vendor demonstrations:

  1. What capability do we need?
  2. Where should it run?
  3. What assets and activity should it protect?
  4. Which control does it satisfy?
  5. Do we already own some of it?
  6. Which vendors should we examine?

Use AEGIS As An AI Security Investment Map 

Forrester’s AEGIS framework gives security leaders a way to define those guardrails across agent behavior, delegated authority, data exposure, tool use, model dependencies, and incident response.

The next job is converting those guardrails into architecture and investment decisions. That means linking each control to the technologies that can enforce, monitor, govern, or validate it.

Start with the control gap. Trace it to the relevant technology categories. Check where existing tools already cover the requirement. Then decide whether to configure, combine, buy, replace, or wait.

Read the full report for all the insights and a deep dive into the methodology, technologies, and vendors solutions.

Connect With Me

Forrester clients with questions related to this research can connect with me through an inquiry or guidance session.

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