Agentic AI Is Already Inside Your Business — Here's Why That Should Worry You

Let me give you a number that I think should stop every business leader in their tracks: 96%.

That's the share of senior security leaders who now say AI-enabled cyberattacks are a significant threat to their organization, according to a March 2026 EY Cybersecurity Roadmap Study of 500 security executives. Nearly half estimate that at least a quarter of the incidents they've dealt with in the past year were AI-enabled.

And the fastest-growing piece of that threat? Agentic AI.

If you've been thinking of AI as a chatbot that drafts emails or summarizes documents, you need to update your mental model — fast. Because the AI systems being deployed inside businesses today are fundamentally different. They don't just respond to prompts. They act. They make decisions, execute multi-step tasks, access databases, move files, send emails, and interact with third-party platforms — all with minimal human involvement. They're autonomous. And that's exactly what makes them dangerous.

What "Agentic" Actually Means

A traditional AI tool is passive. You ask it a question, it gives you an answer. You stay in control.

An AI agent is different. You give it a goal — "book a flight," "analyze this quarter's sales data," "process incoming vendor invoices" — and it figures out the steps, takes the actions, and gets it done. To do that, it needs real permissions. Access to your CRM. Your email system. Your financial software. Your file storage. It operates inside your environment, touching real data, making real decisions.

This is transformative for productivity. The EY study found that virtually every security leader surveyed — 99% — expects agentic AI to fundamentally transform their proactive and defensive security strategies within two years.

But here's the tension that keeps me up at night: the same capabilities that make these systems so powerful are what make them so attractive to attackers.

The Attack Surface Nobody Planned For

Every AI agent your organization deploys creates what security professionals call a "non-human identity" — a machine that needs credentials, API keys, and system access to function. Your legacy identity and access management systems were designed to handle people. They're not built for a world where machines authenticate to machines at scale.

Think about what that looks like in practice. Your marketing team adopts an AI agent to pull together campaign analytics. That agent needs access to your CRM, your email platform, your customer data, and your advertising APIs. Four different systems, each a potential point of compromise. Now multiply that by every department experimenting with similar tools — and you start to see how quickly your attack surface expands without anyone noticing.

Then there's the shadow AI problem. Employees don't wait for IT approval when they find a tool that makes their job easier. They just use it. Research shows more than a third of data breaches now involve "shadow data" — unmanaged systems that security teams don't even know exist. When you combine shadow data with unauthorized AI agents, the risk doesn't add up. It multiplies.

The OWASP Warning You Should Take Seriously

Earlier this year, OWASP — the organization that defines security standards for applications worldwide — released their first-ever Top 10 for Agentic Applications. This is significant. OWASP doesn't issue frameworks lightly. The fact that they dedicated an entire taxonomy to agentic AI risks tells you something about how seriously the security community views this problem.

The list highlights risks that probably sound unfamiliar to most business leaders: prompt injection attacks (where malicious content tricks an AI agent into taking unauthorized actions), excessive agency (agents that have been given too many permissions and can cause unintended harm), and supply chain vulnerabilities in the AI tools and components your developers are plugging into your systems.

These aren't theoretical. They're happening now, and the organizations that get hit first will be the ones that assumed their existing security controls were sufficient.

Three Things Business Leaders Should Do Right Now

I'm not going to tell you to stop deploying agentic AI. That would be like telling businesses in 2010 to stop moving to the cloud. The productivity gains are real, the competitive pressure is real, and the organizations that figure this out will pull ahead. What I am saying is: don't deploy blind.

First, get an inventory. You need to know what AI agents and tools are actually running in your environment — including the ones IT didn't approve. Shadow AI is not an IT problem. It's a board-level risk. Treat it like one.

Second, apply least-privilege to every AI agent. Just like you wouldn't give a new employee the keys to every system on day one, don't give AI agents broad permissions because it's convenient. Define exactly what each agent needs to access, constrain it to that, and review it regularly. The blast radius of a compromised agent with excessive access is enormous.

Third, govern before you scale. The EY study found that 80% of organizations have an AI governance framework that isn't fully embedded in practice. That gap is where breaches happen. If your AI security policy exists as a document but not as enforced controls, it isn't a policy — it's a liability.

The Window to Act Is Closing

Here's the uncomfortable reality: the EY study found that less than half of senior security leaders are strongly confident in their organization's ability to defend against a major AI-enabled breach. And AI defense spending is projected to quintuple in the next two years, jumping from 9% of security budgets to 48%.

That spending surge is coming because organizations are recognizing — some of them the hard way — that their existing security architecture wasn't built for autonomous AI. The perimeter model is dead. Identity-based, least-privilege, continuously-monitored security is what the agentic AI era requires.

I've spent 25 years watching organizations respond to security threats reactively rather than proactively. The ones that paid the price are the ones that waited for an incident to take the problem seriously. The agentic AI threat is not a future problem. It is a right now problem.

If you're not sure where your organization stands, that's the first thing we should talk about.