Not long ago I was in a conversation with a few other security leaders about automation. It started the way these conversations often do, someone mentioned how much faster their team was able to respond to alerts since implementing automated workflows. Another person talked about automatically isolating compromised endpoints upon alerts and someone else described vulnerability remediation scripts they’re working on that could patch systems faster than any human team ever could.
At first the tone of the conversation felt like a victory lap, automation is the buzz of the leadership circles and they all seemed to be making progress. Automation was making everything faster, more efficient and less dependent on manual effort for their teams. It’s the security equivalent of replacing a bicycle with a sports car.
In many ways, that comparison is fair, automation has transformed modern security operations and security teams today are expected to monitor thousands of systems, millions of events, and an attack surface that seems to expand every time a new cloud service appears and without automation, the math simply does not math.
My thought added to the conversation is that speed does not always equal safety and like any powerful tool, automation works best when it is used carefully and well thought out, because sometimes, automation can amplify problems just as quickly as it solves them.
One of the things that came out of that conversation was an observation that stuck with me. Automation often removes friction (that sounds like a good thing), and most of the time that is great, but friction can also serve a purpose, it forces people to slow down, verify assumptions, and think about consequences and when automation removes too much friction, mistakes move faster (even during your busy times).
Consider a common scenario in security operations: An alert fires indicating suspicious activity from an endpoint, maybe a process looks malicious or a command execution pattern matches known attacker behavior. A well-designed automated workflow might isolate the endpoint from the network immediately and that logic is sound, we’ve contained the threat before it spreads and we all want that.
But what happens if the detection rule was wrong?
Instead of a single analyst reviewing the alert and making a decision, the system isolates the machine instantly (which we all would claim that we want). But…If that endpoint happens to belong to someone running a critical system or an executive preparing for a board meeting, the business impact becomes visible very quickly.
Let’s expand that thought a little bigger and imagine that same automation triggering across multiple systems because a detection rule was overly broad and not tuned or tested properly. Congratulations! Your security automation has just executed a denial-of-service attack against your own environment. This is not a hypothetical scenario (well this example is…but many organizations have experienced some version of it.)
Automation does not necessarily make mistakes less likely, it simply makes them faster and more consistent. The same risk appears in vulnerability management if you think about it. Automated patch deployment is often necessary to keep up with the volume of vulnerabilities discovered every week. Without it, security or information technology teams would never catch up, but if patch testing is incomplete or system dependencies are poorly understood, automated remediation can take down critical services just as quickly as it fixes them. Anyone who has ever watched a patch break an application understands this dynamic well.
Automation assumes the environment behaves predictably, but unfortunately, technology environments rarely do. Pop culture offers a good analogy for this. If you have ever watched a science fiction movie where an AI system starts making decisions faster than humans can intervene, you have seen the Hollywood dramatic version of the same principle. The system is not malicious (in some movies it is), but it is simply following its logic faster than anyone expected.
In cybersecurity, our automation is far less cinematic, there are no glowing robots or dramatic countdowns, but the principle is similar. Automated systems follow instructions precisely, and they do it without hesitation or context or situational awareness. That precision is powerful when done right, but is unforgiving when not thought through.
Another area where over-automation can introduce risk is identity and access management. Automated provisioning workflows are a cornerstone of modern identity systems. When someone joins the company, changes roles, or leaves, automation ensures accounts are created, updated, or disabled quickly. In theory, this is exactly what organizations want and every leader will tell you that. If the underlying role definitions are incorrect or outdated (or maliciously changed), automation spreads those mistakes across the entire environment. A flawed role assignment in a manual process affects one user at a time, where the same mistake in an automated process can affect hundreds. Automation does not question assumptions. It scales them.
This is why governance matters so much when automation enters the picture. The more authority you delegate to automated systems, the more important it becomes to understand the logic and the reality behind them. Workflows need guardrails, decisions need context and critical actions need escalation paths.
In many organizations, automation grows organically not part of a well thought out strategy, a script gets written to solve a problem, a few months later another script connects to it to deal with another process and eventually the collection becomes an unofficial workflow system that no single person fully understands and this is where security programs can run into trouble.
Automation that lacks clear ownership becomes difficult to audit, difficult to modify, and even more difficult to trust during incidents. From a leadership perspective, the real issue is not automation itself. Automation is essential and I’m for it wherever it makes sense and the scale of modern infrastructure demands it. Security teams cannot manually review every log entry, manually patch every vulnerability, or manually investigate every alert.
The question leaders should be asking is not whether automation exists but whether it is governed appropriately? Mature automation strategies include visibility into what the automation is doing and why. They incorporate testing (including edge cases) before deployment. They include rollback capabilities when something behaves unexpectedly and most importantly, they ensure humans remain in the loop for high-impact decisions. Automation should support human judgment, not replace it.
A subtle risk with over-automation is the gradual erosion of expertise of your environmental norms. When systems automatically respond to alerts, analysts may become less familiar with the underlying signals. Over time, teams can lose the ability to investigate events manually because the automated workflow has been doing it for them. This can create a dangerous dependency for some inexperienced teams.
If the automation fails or produces unexpected results, the team may struggle to reconstruct what actually happened. In the worst cases, organizations discover during a major incident that the only system that understood the response process was the automation platform itself and usually that realization tends to come at the worst possible moment.
Security leaders should think about automation the same way aviation treats autopilot systems. Autopilot is incredibly useful. It reduces workload and improves consistency. But pilots are still trained to fly the aircraft manually. They understand the underlying mechanics because automation is not infallible.
Security programs should approach automation with the same mindset, use it extensively, use it intelligently, but never assume it eliminates the need for human understanding.
Automation should follow the same governance principles applied to any critical system. It should have defined owners, documented logic, regular reviews, and monitoring to ensure it behaves as expected. It should be tested before major changes and perhaps most importantly, it should be designed with the assumption that something will eventually go wrong….Because something always does (and usually at the worse time).
The irony is that automation is often implemented to reduce operational risk, and most of the time, it succeeds… Security teams become faster, detection improves, response times shrink, but if automation is treated as a magic solution rather than a capability that requires oversight, the same systems designed to protect the organization can create unexpected exposure.
Speed is valuable. Control is essential.
The next time your team discusses a new automation initiative, ask a few simple questions. What decisions is the system allowed to make on its own? What safeguards exist if the logic is incorrect? Who owns the workflow? And if something goes wrong at machine speed, how quickly can you stop it?
Automation is one of the most powerful tools modern security teams have, but like any powerful tool, it deserves respect…the real risk of automation is not that it moves too slowly, but it is that sometimes, it moves exactly as instructed.