AI-powered cybersecurity is a broad category, not one kind of product. It includes using AI to detect, investigate and respond to threats, as well as protecting AI models, applications, workloads and agents. Buyers should start with the security problem and systems they need to cover—not the “AI-powered” label—and check how a product fits their existing environment and what evidence supports its claims.
What does AI-powered cybersecurity mean?
The term describes security products that apply AI to tasks such as analyzing telemetry, identifying threats, helping investigate incidents or automating responses. It also covers tools designed to secure AI systems themselves. Those are related but distinct goals: using AI to defend an organization does not, by itself, protect that organization’s AI applications or agents.
Examples reported by CRN span security operations and SIEM, cloud and AI application defense, email threat detection, exposure management, and controls over AI agents. The category is therefore best understood by the job a tool is meant to do, the assets it covers and the actions it can take.
Which security problems can these products address?
Security operations and threat response
Security operations products use AI as part of monitoring, investigation and response workflows. CRN describes Palo Alto Networks’ Cortex XSIAM as an AI-powered alternative to traditional SIEM. CrowdStrike, meanwhile, added support in Falcon Next-Gen SIEM for ingesting and correlating telemetry from Microsoft Defender for Endpoint, an example of why data integration matters alongside a product’s AI features.
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AI in this area may assist with analysis or automate parts of a workflow, but product descriptions alone do not establish how accurately a system detects threats or how much work it removes from a security team.
Cloud, application and AI-system protection
Cloud security products monitor and protect cloud environments and the applications running in them. A related need is protecting AI models, applications and workloads, which can involve assessing configurations and looking for security weaknesses throughout development and operation.
CRN reports that Google Cloud and Wiz are building a unified security platform combining Google threat intelligence and security operations with Wiz cloud and AI security. Google Cloud CEO Thomas Kurian said the intended platform would “detect, prevent, and respond to threats across all environments.” CRN also reports that Wiz products are intended to continue supporting major cloud providers. These are descriptions of the planned offering, not evidence that it has achieved particular security outcomes.
Rank #2
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CRN describes Palo Alto Networks’ Prisma AIRS as including model scanning, posture management, AI red teaming, runtime security and agent protection. Those capabilities address different parts of AI-system security; a buyer should establish which are available in the relevant product and deployment, rather than assume the name covers every AI asset or stage of use.
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AI-agent permissions and oversight
AI agents can take actions, not just generate recommendations. That makes it important to control what an agent is allowed to do and to monitor what it actually does. CRN reports that Cisco’s Zero Trust Access for AI agents ties permissions to tasks and monitors agent actions. Cisco senior vice president and general manager Tom Gillis described the shift this way: “we believe that has to evolve from access control to action control”.
Oversight is another design choice. CRN reports that Arctic Wolf’s Aurora Agentic SOC uses what the company describes as hundreds of agents for security tasks while retaining human experts for oversight and validation. The scale and claimed benefits are the company’s characterization, not an independent performance finding.
Rank #3
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Email, exposure and other emerging use cases
Email threat detection and exposure management are also part of the wider category. CRN’s interview with Palo Alto Networks asked about the significance of adding email security to Cortex XSIAM 3.0, illustrating how security platforms may expand across work areas. The interview alone does not establish the product’s effectiveness or the degree of coverage available to a particular customer.
CRN’s coverage of RSAC 2026 also reports announcements from Wiz, Dell, Rubrik, Dataminr and Snyk involving AI application protection, quantum-ready PC security features, governance for autonomous agents, threat intelligence, and AI security posture management for agentic development. These are varied offerings, not interchangeable solutions to one problem.
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| Example | Problem or capability described by CRN | What a buyer should verify |
|---|---|---|
| Google Cloud and Wiz | A planned unified platform combining Google threat intelligence and security operations with Wiz cloud and AI security; intended detection and response across environments. | Which environments and AI assets are covered, how the planned capabilities are delivered, and how they integrate with existing tools. |
| Cisco Zero Trust Access for AI agents | Task-based permissions and monitoring of agent actions. | How permissions are defined, enforced and changed, and what action records or review controls are available. |
| CrowdStrike Falcon Next-Gen SIEM | Ingestion and correlation of Microsoft Defender for Endpoint telemetry. | What telemetry is supported in the buyer’s deployment and how it contributes to investigation and response workflows. |
| Palo Alto Networks Prisma AIRS | Model scanning, posture management, AI red teaming, runtime security and agent protection. | Which functions apply to the organization’s models, applications and agents, and what each function reports or enforces. |
| Palo Alto Networks Cortex XSIAM | Described by CRN as an AI-powered alternative to traditional SIEM; the interview also discusses email security in XSIAM 3.0. | What data sources and email capabilities are included in the relevant offering, and how performance compares in the buyer’s own use case. |
| Arctic Wolf Aurora Agentic SOC | The company describes hundreds of agents carrying out security tasks, with human experts providing oversight and validation. | Which tasks are automated, what requires human review, and how escalation and validation work. |
The descriptions above are attributed to CRN’s reporting and, where indicated, to vendor statements. They do not constitute a controlled head-to-head evaluation, and the products do not all address the same security problem.
Rank #4
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How should buyers evaluate an AI security product?
Start with the assets and risk you need to cover
Define the specific gap first: for example, investigating security alerts, monitoring a cloud environment, protecting an AI application or restricting an agent’s actions. List the relevant systems, data sources, clouds, models and agents. Then ask vendors to identify what their product covers and what it does not.
Check integration and operational fit
Find out whether the product can use the telemetry and identity, endpoint, cloud or email controls already in place. Ask how data is ingested and correlated, which integrations are available in the edition being considered, and what additional work is needed to keep them functioning. CrowdStrike’s reported addition of Microsoft Defender for Endpoint telemetry illustrates the practical importance of integration, but does not establish coverage for every buyer’s setup.
Map automation to human responsibility
Ask which actions the product recommends, which it performs automatically and which require approval. For agent-based capabilities, establish whether permissions can be limited to a task, whether actions are logged, and how a person can validate, stop or escalate an action. A product’s use of agents does not tell you how much authority those agents receive.
Best Value
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Ask for outcome evidence, not just capability lists
Request evidence that matches your own use case: how the product was evaluated, which data and conditions were involved, what outcomes were measured, and whether the results can be independently checked. CRN’s product coverage largely reports vendor announcements and executive statements; it does not provide a controlled comparison establishing which named product reduces risk more effectively or lowers operational burden.
CRN also reported Palo Alto Networks Chief Product Officer Lee Klarich’s statement that the company had data showing a 300 percent year-over-year increase in new attacks per day. That is a vendor-reported statistic relayed in a 2025 interview, not an independently established industry-wide measure, so it should not be used as a general measure of how quickly attacks are increasing.
Measure risk reduction and reporting in your environment
Agree on the outcomes that would make the purchase worthwhile before comparing feature lists. CyFlare founder and CEO Joe Morin framed the test as: “It’s really about, when you have it, did it reduce my risk? And can you pull the data and make compliance reporting easier?” For a buyer, that means specifying what risk or workflow is being addressed and what data would demonstrate a useful change.
Quick Recap
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