AI Is Finding Vulnerabilities Faster. Can Your Patch Management Keep Up?

AI is helping us find software vulnerabilities faster than ever. That’s great news for cybersecurity. But, there’s a consequence we don’t talk about nearly enough: More vulnerabilities discovered means more vulnerabilities to fix. More vulnerabilities to fix means more patches. And more patches mean more pressure on already-busy IT teams. Would you agree?

Microsoft, Google, and other major technology providers are increasingly using AI and advanced security technologies to uncover vulnerabilities that might previously have remained hidden much longer. I see this as an important step forward. Finding vulnerabilities earlier gives us a better opportunity to address them before attackers can exploit them. But, it also raises an important question for every IT and security organization: If AI dramatically increases the speed at which we discover vulnerabilities, can our patch management processes keep up? Think about it for a second and try to digest the impact of these changes on you and your teams.

For me, the answer isn’t simply to patch faster. It’s to patch smarter and the old approach to patch management won’t scale forever. Not a chance! Think about what happens when patch volumes increase. IT teams have more updates to evaluate, more vulnerabilities to prioritize, more endpoints to manage, more deployments to schedule, and more results to verify. Are you already visualizing the impact on your organization?

If every step requires manual intervention, eventually something has to give and simply telling IT teams to “patch everything faster” isn’t a sustainable cybersecurity strategy. Instead, I believe organizations need to rethink patch management around three principles: Prioritize. Automate. and Verify.

Get those three things right, and increasing patch volumes become far more manageable.

1. Prioritize: Not every vulnerability represents the same risk

When hundreds of updates are competing for attention, not every patch necessarily deserves the same priority and context matters. How severe is the vulnerability? Which systems are affected? How critical are those systems to the organization? What would happen if they were compromised? How quickly does the vulnerability need to be addressed? This is why I believe risk-based patch management is becoming increasingly important. Instead of treating patching as a race to deploy everything simultaneously, organizations can focus on getting the right patches to the right systems at the right time.

Combine that approach with phased deployments across test, pilot, and production environments, and organizations can better balance two objectives that sometimes compete with each other: security and operational stability.

2. Automate: Let policies handle the repetitive work

This is where automation can make an enormous difference. Imagine manually reviewing every new update, determining which endpoints need it, deciding when it should be deployed, building deployment groups, monitoring results, and then starting the entire process again when the next round of patches arrives. Now, imagine doing that as AI helps uncover vulnerabilities at an increasingly rapid pace. Doesn’t matter how you plan or think about it. It simply doesn’t scale!

With OpenText ZENworks Patch Management and OpenText Core Endpoint Management Express, organizations can use Patch Policies to automate many of these repetitive processes. Policies can help automatically select patches based on predefined criteria, schedule deployments according to risk, support phased rollouts, standardize deployment processes, and reduce manual administration. Instead of recreating patch plans month after month, IT teams can establish policies and approved workflows and allow new updates to move through those processes automatically. That’s an important shift because the goal isn’t to make IT teams work faster. It’s to reduce how much repetitive work they need to do in the first place.

3. Verify: Deployment doesn’t necessarily mean protection

This may be the most overlooked part of the patch management conversation as deploying a patch is not the same as successfully installing it. A device may have been offline. An installation may have failed. A system may have missed a deployment window. An endpoint may remain non-compliant without anyone realizing it. That’s why I believe patch compliance needs to be treated as seriously as patch deployment.

IT and security teams need visibility into questions such as: Which devices are still missing critical patches? Which deployments succeeded or failed? Which endpoints are currently non-compliant? Which systems require remediation? Are we meeting our patching policies and service-level objectives?

Without that visibility, an organization may believe its environment is protected when critical vulnerabilities remain unresolved. For me, there’s a simple principle here: Don’t just deploy it. Verify it! You don’t want to leave security to chances. Do you?

Now, let’s bring AI into the conversation as we all agree we are entering an interesting cycle. AI can help security researchers and software vendors find vulnerabilities faster. But attackers can also use increasingly sophisticated technologies to identify weaknesses, automate reconnaissance, and accelerate attacks as they are always at the forefront of technology and how to use it, unfortunately, for the bad. That makes the time between vulnerability discovery and effective remediation increasingly important. And that puts patch management right in the middle of the cybersecurity conversation and therefore, Patch management can no longer be viewed simply as routine IT maintenance but as an essential part of cyber resilience. Organizations need to know what vulnerabilities exist, understand which ones matter most, deploy the appropriate updates quickly, and verify that those updates actually reached the systems that needed them.

More patches shouldn’t mean more complexity

This is ultimately where I see the biggest opportunity (and hope you agree with me). If vulnerability discovery continues accelerating, organizations can’t respond simply by adding more manual processes or expecting IT teams to absorb an ever-growing workload. What we need to do is automate more of the routine work and that’s exactly the type of environment OpenText ZENworks Patch Management and OpenText Core Endpoint Management Express are designed to support.

Through automated Patch Policies, scheduled deployments, phased rollouts, centralized endpoint visibility, and compliance monitoring, organizations can build a more scalable approach to patch management and endpoint security. The objective is simple: Increase security without increasing operational complexity at the same rate.

AI is changing how quickly vulnerabilities can be discovered. Now our patch management strategies need to evolve with it. I don’t believe success will be measured by how many patches an organization can push out in the shortest possible time. The organizations that are better prepared will be those that can consistently: Prioritize what matters; Automate what can be automated;
Deploy in a controlled way; Monitor compliance and verify that vulnerabilities have actually been addressed.

Because as AI accelerates vulnerability discovery, one thing is becoming increasingly clear: Finding vulnerabilities faster only improves security if we can fix them just as intelligently. And that’s why the future of patch management, endpoint security, and cyber resilience isn’t simply about patching more. It’s about patching smarter.