Fitting AI controls next to the EDR, SSE and DLP you already run

What does EDR give you?

EDR watches processes, files and network activity for malware and intrusion. It is good at telling that something malicious is running. It is not built to judge whether a trusted coding agent, run by a real employee, should be allowed to install a package or read a file. AI endpoint controls work alongside it.

EDR is also a delivery path. Bay and Noma Security state that they deploy through your existing EDR or MDM without a new endpoint agent. Koi (Palo Alto Networks) is offered as a Cortex XDR module. Prompt Security is built into SentinelOne Singularity, with its own browser extension and AI endpoint agent. If you run one of those platforms, the finder adds four points to the product built into it, and shows it as built into a platform you already run.

What does device management give you?

Intune, JAMF, Kandji or Group Policy can install software, push browser extensions and enforce settings, including the managed settings some AI agents offer. Harmonic Security names those four for its rollout. Device management is also what makes a device managed in the first place, which every on-device control depends on.

What does an SSE give you?

If web traffic already passes through an SSE or secure web gateway, you can usually allow or block AI services there and, depending on the product, inspect what is sent. It does not see local agent actions. Two products here are network controls of this kind: Zscaler Generative AI Security, which shows the prompts employees send to GenAI apps and blocks sensitive data with DLP, and AI Access Security from Palo Alto Networks, linked from Prisma Access. Lasso Security describes proxy integrations for AI usage control, and the finder counts that as working with something you already run.

What does DLP give you?

DLP may already detect sensitive data in web uploads or on devices. Ask what it sees of AI chat tools in particular, and whether it understands prompts and uploads to them. The finder treats DLP as a reason to look at the browser position, where data leaves.

What is left for an AI endpoint control?

• Knowing which AI agents, MCP servers and extensions are on each device.
• Deciding on an individual agent action before it runs, with context about who started it.
• Asking the person, rather than blocking, when an action is unusual.
• Recording whether a person or an agent took each action.

What should you ask your current vendors first?

• What do you already see of AI tools, agents and MCP servers on our devices?
• Can you carry another vendor's AI control to our devices, and what does that involve?
• Is there an AI module or add-on on your roadmap, and what does it cover today?

Their answers tell you whether you are filling a real gap or paying twice. If your EDR or SSE vendor already sees most AI tools and can apply rules to them, a dedicated product needs to add something specific, such as decisions on individual agent actions or a person-versus-agent record. If they see little, the gap is wider and the finder's product list matters more. Either way, write the answers down before the first vendor demo, so each new product is judged against what you already have rather than against nothing.

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