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What Does SEN Think Of Agentic AI’s Ability In Security Applications?

What Does SEN Think Of Agentic AI’s Ability – We tend to think the security industry has been deploying agentic AI much longer than it realises.

Prior to the development of agentic AI, the electronic security industry sought ways to automate functionalities based on threshold breaches using networks of sensors, controllers, comms paths and control rooms.

When it comes to the latest speculations around what agentic AI might be able to do, something most security people discount is that electronic security solutions and the procedures and teams supporting them are life safety solutions.

This makes the reliability of agentic AI’s actions at key moments paramount for security professionals who are serious about their organisation’s security and safety stance.

It’s a fundamental that means agentic AI’s actioning of procedures must be carefully considered, especially now that the pace of AI development has accelerated to a dizzying degree.

It helps that the electronic security industry has been using early versions of agentic AI to parse data flows and handle intrusion detection and event classification and undertake automated responses far longer than most other industries have.

This means that AI development – including a level of agentic AI development – is integrated into many electronic security solutions as emergent properties of software management systems.

SEN frameworkSix levels of autonomy for security automationThe argument about agentic AI in security is really an argument about how much autonomy to hand over, and the industry has no shared vocabulary for that. Here is one. Move along the scale to see what changes — and where the life-safety line falls.
Life-safety line
The system does
The human does
If the agent is wrong
Autonomy
Assurance burden
This scale is SEN’s, not a standard. It is offered as a common vocabulary for a conversation the industry is already having without one. The observation that electronic security has been operating at the lower levels for years — parsing data flows, classifying events, actioning automated responses — is the argument made in this article. Where any given product sits is a question for the vendor.

We love the idea of huge security, safety and automation systems that have fingertip awareness right down to sensor states and zone voltages.

Agentic AI could use this sensor data to not only send reports or alerts on overall system states – many SMS and VMS systems do this already bear in mind – it could also trigger automation rules as thresholds are crossed.

Before you delegate
Six questions to answer per function
Not per product. Autonomy is granted function by function, and the answers change with each one.
01Is this function life safety?If a wrong action can hurt someone or block egress, the answer to everything below has to be stricter.
02Are the rules written down?Agentic behaviour built on procedures nobody has documented cannot be reviewed, tested or defended.
03What does a wrong decision cost?Irritating on a trivial project, potentially catastrophic in a life-safety system. Grade the function, not the product.
04Who is in the loop, and when?Before the action, during it, or only in the after-action review. That choice is the autonomy level.
05What happens on a remote update?If the underpinnings of an enterprise system change without a change-control gate, yesterday’s assurance is stale.
06Can you reconstruct a decision?An audit trail of what the agent saw, concluded and did is the difference between an incident review and a shrug.
Drawn from the cautions raised in this article. Editorial, not a compliance framework.

However, given experience with generative AI, we know AI makes mistakes – not just little mistakes, either, but epic misconceptions that are irritating during trivial projects but could be catastrophic in a life safety system.

That means the rules and procedures built into any agentic AI’s operations need to be carefully considered and demand a degree of oversight, especially if the underpinnings of an enterprise system were undergoing remote updates.

Regardless, the potential of agentic AI across a range of use cases can’t be ignored, especially when it comes to parsing rivers of data and bringing key events to the attention of well-trained humans.

You can geek out on the Coasean Singularity of AI agents here or read more SEN news here.  What Does SEN Think Of Agentic AI?

“What Does SEN Think Of Agentic AI’s Ability In Security Applications?”

Keep readingWhere this argument goes nextThe economics of AI agents — what happens to firms when the cost of coordination collapses — is the other half of this question, and it is being argued out in the economics literature rather than the security press.

What Does SEN Think Of Agentic AI - What Does SEN Think Of Agentic AI

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John Adams
John Adamshttps://sen.news
A professional writer and editor who has been covering the security industry since 1991, John is passionate about clever applications of technology and the fusion of sensing and networking. A capable photographer John enjoys undertaking practical reviews of the latest electronic security systems.

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