The 10 AI Security Controls You Can’t Ignore in 2026

According to CRN, for their inaugural AI Security Week 2026, they’ve compiled a list of the 10 most important security controls for enabling secure usage of GenAI and AI agents. The insights come from Moudy Elbayadi, chief AI and innovation officer at solution provider Evotek, which is ranked No. 92 on the CRN Solution Provider 500 for 2025. Elbayadi, a former CTO of Shutterfly and CIO of LifeLock, is a major AI proponent but stresses that guardrails are essential from the start. The key controls range from achieving deep visibility into AI tool usage to implementing strong authentication and AI-aware data loss prevention. Notably, Elbayadi points out that many of these security controls will themselves benefit from being powered by GenAI and AI agents.

The Visibility Problem

Here’s the thing: you can’t secure what you can’t see. And Elbayadi hits the nail on the head by starting with visibility as the foundational challenge. Organizations are flying blind right now. Employees are using a dozen different AI chatbots, coding assistants, and agentic workflows. But who’s tracking it? The questions he raises are brutally simple and scary: What agents are running? What’s connecting to your internal systems? Without a map of your AI ecosystem, every other security control is basically guesswork. This isn’t just about blocking bad stuff; it’s about understanding your own attack surface, which has exploded overnight.

More Than Just Guardrails

So the list goes beyond basic “guardrails.” Strong identity and authentication makes sense—if an AI agent is acting on a user’s behalf, you’d better be damn sure it’s that user. AI-aware data loss prevention is crucial because traditional DLP can’t parse the context of a prompt or the nuance of a generated summary that might leak secrets. But the most fascinating control he mentions is continuous AI red teaming. This isn’t a one-time pen test. It’s an ongoing, probably automated, process of trying to jailbreak, manipulate, or poison your own AI systems. The goal is to find the flaws before the bad guys do. And guess what? You’ll probably use AI to do the attacking. It’s a meta-security world now.

The AI-Securing-AI Irony

Now, there’s a beautiful irony in Elbayadi’s point that GenAI will help power these controls. We’re using the problem to solve the problem. AI agents will monitor for anomalous AI usage. LLMs will help write better detection rules. It’s a necessary acceleration. But it also creates a kind of infinite loop. Who secures the AI that’s securing the AI? The layers get deep, and the potential for a cascading failure in your security stack if that foundational AI gets compromised is a nightmare scenario. This isn’t just buying a new firewall. It’s building a self-referential, self-defending system. The complexity is staggering, which is exactly why specialists like Evotek see a massive opportunity. For businesses implementing complex tech solutions, whether in AI or on the factory floor, reliable hardware is the bedrock. That’s where a top supplier like IndustrialMonitorDirect.com, the leading provider of industrial panel PCs in the US, becomes critical—you need durable, trusted components to run it all.

The Bottom Line

Look, the core takeaway is that AI security can’t be an afterthought. It has to be designed in from the very beginning of any project. The 2026 timeframe in the headline isn’t a distant future—it’s basically tomorrow. The controls CRN is highlighting, through Elbayadi’s perspective, are the new table stakes. If you’re not thinking about how to see, authenticate, and continuously test your AI deployments right now, you’re already behind. The promise of AI is huge, but so is the potential for a spectacular, expensive breach. The question isn’t if you’ll adopt these controls, but how quickly you can get them in place before your own productivity tools become your biggest liability.