The Value of AI-Driven Automation at Your Security Operations Center

Executive summary

Today's threat environment is pushing the Security Operations Center (SOC) past its breaking point. Mass cloud adoption has expanded the attack surface, geopolitical risk is at an all-time high, and critical talent shortages are leaving SOCs exposed.

Once strategic advantages, SOC scale and speed have become serious liabilities. With large enterprises facing a deluge of up to 3,000 daily alerts, the traditional, manual investigation process is failing. Investigation times are now significantly slower than the time it takes an attacker to compromise a system. As the gap becomes untenable, teams have been forced to make difficult choices, accepting critical levels of risk.

The challenges are clear. That's why AI for security operations is now a top priority for security leaders.

And so, for security executives and practitioners ready to move past alert fatigue and operational struggle, this guide is for you. In it, we’ll lay out the key components of AI-driven automation, explore the key benefits, before finally listing the capabilities to consider in an AI-driven SOC solution that will deliver the speed, scale, and consistency enterprise organizations need to manage today’s threat environment.

Introduction: The evolution of the Security Operations Center (SOC)

The modern SOC has evolved significantly since its origins in the 1970s, where defense organizations focused primarily on low-impact, malicious code. As threats from viruses, DDOS attacks, and bot-net armies emerged over the next decades, the next generation of SOCs perfected intrusion detection and prevention.

Today’s threat environment, however, is unprecedented:

• New, complex threats routinely paralyze response teams, even those with clear incident action plans.
• Attack surfaces have expanded considerably with the mass adoption of the cloud and proliferation of third-party services.
• Geopolitical risk from cyber-sophisticated powers is at its highest.
• Acute supply-chain disruptions and critical talent shortages further complicate security operations.

Challenges to running an SOC

As a result, building and running a resilient SOC have never been harder. The key challenges facing modern SOCs confirm this crisis of volume and speed:

• Excessive triage time. The process of understanding and responding to an alert (once generated) is excessively time-consuming. This directly contributes to alert fatigue, leading teams to ignore a substantial volume of alerts.
• Lack of continuous monitoring. Gaps in off-hours coverage means alerts are frequently missed or timely responses are delayed.
• Analyst burnout and/or turnover. Overwhelmed by the volume and complexity of alerts, analysts are burning out. Then, they’re turning over. The resultant loss of institutional knowledge and increase in training costs severely limit operational vigilance and impair the ability to comply with SOPs.
• Managing multiple systems. Part of the strain comes from managing multiple systems with limited resources. Alerts are coming from everywhere. The average large company has almost 30 alert-generating systems. The average SMB has 17 alert-generating systems.
• Failure to measure KPIs accurately. Having these disparate systems creates another issue: teams find it difficult to extract and consolidate meaningful data for incident reporting, which is often done in another system altogether.

Security alerts run amok

But are the number of alerts really an issue? Emphatically, yes.

Companies of all sizes are experiencing a deluge of alerts, straining their security operations. Larger companies face around 3,000 alerts per day, according to the State of AI in Security Operations 2025 report. SMBs generate 500 alerts per day.

Given the volume, many of these alerts simply aren’t getting investigated. In fact, a staggering 40% of alerts are never investigated. And one-third of companies ignore more than half of their alerts.

Sure, many of these alerts turn out to be false. But many turn out to be consequential. Three in five security teams reported that an ignored alert proved to be critical.

Besides ignoring alerts, security teams are also suppressing detection rules to limit the number of alerts they receive in an effort to manage their current operational limitations. When surveyed by Prophet, almost 60% of companies acknowledged that they were actively suppressing detection rules, accepting unimaginable levels of risk in the process.

The limitations of traditional, manual security

The manual processes and fragmented tools security teams rely on are also proving inadequate. The Mean Time to Investigate (MTTI), i.e., the average time it takes a security team to thoroughly investigate an alert, stands at around 70 minutes. Meanwhile in its 2025 Global Threat Report, CrowdStrike found that the average phishing attack only took 48 minutes to compromise a system and extract sensitive information.

To simplify security operations, many SOCs have turned to AI solutions. In fact, AI for security now ranks among the top three priorities for security leaders, after data and cloud security.

The trendlines are clear: 55% of companies are now using AI for alert triage and investigation. Of the remaining 45% of non-users, nearly three-fifths plan to evaluate an AI SOC solution within the next year, while three-tenths are already evaluating AI SOC solutions.

What benefits do they stand to get from such solutions? This guide answers that very question, defining AI-driven automation for SOCs, articulating their core value proposition for enterprises, and spelling out the capabilities to look out for in a solution.

Definition and components of AI-driven automation

The influx of alerts and data volume has seriously hampered the effectiveness of traditional SOC capabilities, requiring enterprises to invest in new solutions. AI-driven automation addresses this very pain point, leveraging machine learning, powerful computing, and behavioral analysis to extend human capabilities and empower security teams to detect and respond to digital threats with unprecedented speed and accuracy.

What’s it all about, though? Well, AI-driven automation solutions are built on a framework of advanced technologies, be it machine learning, natural language processing, and/or deep learning. These elements work in sync to process, analyze, and contextualize huge volumes of security data in real-time, enabling the automation of routine tasks like triage, investigation, and response coordination.

Here are the high-value components of an AI-driven SOC automation platform:

1. Real-time anomaly and behavioral detection

Focusing primarily on known attack patterns, traditional, signature-based detection has proven increasingly ineffective against sophisticated, evolving threats. Instead of relying on predefined signatures, AI models identify behavioral anomalies that indicate potential security threats:

• Proactive threat identification. Machine learning algorithms continuously analyze large datasets (e.g., network traffic, user activity, system logs, etc.) to identify deviations from normal patterns.
• Reduced false positives. Instead of flagging every suspicious signature, AI models learn from historical data over time, redefining detection capabilities to reduce false positives significantly and improve accuracy.
• Minimized damage. This proactive approach allows security teams to identify emerging threats before they escalate, minimizing dwell time and potential damage.

2. Predictive analytics and advanced threat hunting

Triaging the overwhelming number of security alerts generated by traditional systems often leaves SOCs fighting the last war. However, AI-driven predictive analytics enables SOCs to proactively hunt emerging threats.

How so?

• Vulnerability forecasting. By analyzing historical attack data and threat intelligence, AI models predict potential vulnerabilities, assessing the likelihood of future attacks against infrastructure.
• Targeted defense. This intelligence-driven approach allows SOCs to preemptively strengthen defenses, apply targeted patches, and mitigate risks before adversaries can exploit them.
• Enhanced threat context. AI correlates data from global threat databases, dark web monitoring, and malware repositories. This comprehensive analysis helps classify threats by severity, enabling security teams to prioritize high-risk incidents and respond with greater precision. 

3. Automated triage and alert differentiation

The deluge of false positives leads directly to analyst burnout and delayed response times. AI-powered automation rectifies the situation with intelligent alert scoring and differentiation:

• Advanced algorithms. Machine learning models use advanced algorithms to quickly differentiate between legitimate threats and benign anomalies.
• Prioritization. Models continually refine their classification over time, filtering out low-risk alerts and ensuring security teams focus their attention and resources exclusively on high-priority, validated incidents.

4. Coordinated, automated threat mitigation

AI-powered automation excels during the incident response stage, transforming reliance on slow, manual interventions into real-time, automated mitigation.

How does it function?

• Instant response. When an anomaly or threat is detected, the AI platform immediately executes predefined security protocols.
• Rapid actions. Rapid actions include isolating compromised devices, blocking malicious IP addresses, and/or restricting unauthorized access.
• Impact reduction. This automated response minimizes the time attackers have to exploit vulnerabilities, drastically reducing the impact of security breaches. 

5. Security orchestration and tool integration

Modern SOCs are unduly burdened by the complexity of managing so many security tools (e.g., EDR, Firewalls, IDS, SIEM, etc.). AI-powered orchestration platforms help to unify this environment:

• Integrated workflow. Platforms analyze alerts from multiple tools, correlate the data, and trigger automated responses across the entire security ecosystem.
• Coordinated defense. This unified approach ensures a faster, more coordinated response to threats, eliminating security gaps and reducing the risk of misconfigurations caused by manual handoffs.

6. Real-time forensic data collection and reporting

Between investigating security incidents, identifying their root cause, then documenting findings for compliance reporting, SOC analysts have a time-consuming job. AI-driven SOC automation can accelerate incident analysis by collecting and analyzing forensic data in real time.

AI systems themselves can:

• Generate detailed incident reports
• Provide insights into attack vectors and affected systems
• Recommend remediation steps

Thanks to natural language processing, in particular, AI can also summarize security incidents in an easily understandable format, which, in turn, helps SOC teams and executives make better informed decisions before, during, and after security incidents.

Benefits of AI-powered SOCs

Integrating AI-driven automation into the Security Operations Center (SOC) is becoming increasingly important for enterprises seeking to achieve operational mastery and secure a competitive advantage. The strategic combination of human expertise and artificial intelligence dramatically improves an SOC's overall effectiveness, allowing analysts to transition from reactive firefighting to strategic, proactive defense.

Further benefits of AI-powered SOC automation include:

• Focuses analysts, reduces alert fatigue, and mitigates burnout. AI acts as a powerful intelligence layer, filtering out low-risk alerts and ensuring that security teams focus on high-priority incidents to ensure that time and energy are spent exclusively on high-priority, legitimate incidents.

By automating repetitive and low-level tasks, AI also frees up highly skilled analysts to concentrate on complex threat hunting, strategic defense planning, and critical decision-making.

• Ensures consistent, rapid incident response. By integrating AI-driven security automation, organizations can streamline their incident response workflows, ensuring that security measures are enforced consistently across the entire security infrastructure.

Thanks to automated threat mitigation capabilities, organizations can also enforce their security measures consistently across their entire infrastructure. This automated consistency ensures that response workflows adhere perfectly to SOPs every single time, minimizing human error.

What’s more, automation allows SOC teams to handle a far greater volume of incidents without becoming overwhelmed, driving a scalable defense posture.

• Eliminates security gaps. The proliferation of tools in the modern SOC often creates integration gaps and coordination weaknesses. AI-powered orchestration solves this fragmentation to enable:
• Seamless tool integration. AI enhances efficiency by orchestrating and unifying myriad security solutions, enabling tools to work together seamlessly with less manual intervention and ensuring a faster, more coordinated defense.
• Reduces risk. By creating a unified workflow, AI-powered solutions drastically reduce the risk of security gaps and configuration errors that arise from manual management of disparate systems.
• Accelerates compliance and audit readiness. AI tools simplify and automate the most complex, time-consuming compliance tasks, turning reporting into a competitive advantage and source of continuous learning.

Using natural language processing, AI-based reporting tools can instantly summarize security incidents in a digestible format. Crucially, they can also automatically map security incidents to major industry standards and regulatory frameworks (e.g., GDPR, HIPAA, NIST, etc.), which not only accelerates compliance but also ensures that organizations maintain the comprehensive, high-fidelity documentation required for audits.

• Drives security resilience and ensures operational continuity. By creating a faster, more accurate, and less error-prone security environment, AI fundamentally increases organizational resilience. The automation and analysis of results significantly improve the overall efficiency of security operations, allowing organizations to maintain a state of continuous improvement.

What’s more, the combined effect of improved triage and automated response drastically reduces key metrics like MTTD and MTTR, ensuring that organizations outpace modern threats and maintain operational continuity.

Integration challenges

Despite the clear value to enterprise organizations, integrating AI-driven automation into an existing SOC environment requires a clear plan of action to overcome any challenges that might arise, whether significant changes in processes or resistance from SOC personnel.

However, these challenges can be addressed by taking a strategic approach to applying AI-driven automation. For some organizations, a slow implementation through sample projects might be the way to go.

Cultivating a culture of trust and transparency is also important. Organizations can go a long way toward developing such cultures with effective communication about the role and benefits of AI in security automation as well as training and collaboration between human observers and AI systems.

What to look for in cloud-based software to simplify security operations

But what systems work best for your SOC’s needs? At the very least, your cloud-based security automation platform should use AI to verify and respond to threats in real time. Fast, consistent incident response will simplify your security operations and improve SOP compliance.

For best-practice, AI-driven SOC automation, we recommend seeking out the following capabilities:

• AI-powered triage. Your solution should be able to reduce risk and save analysts time by automatically verifying and combining signals, giving the SOC team a clear view of only the most serious threats. The solution – not the operator – should be correlating security events, consolidating duplicates, and auto-resolving false positives.
• Automated incident response. Your solution should leverage predefined playbooks to enable rapid, error-free containment and stakeholder action. That will help lower MTTR and minimize costs and impacts, by reducing human error, delays, and inconsistent processes.
• AI-driven response planning. The best solution for your needs will generate the dynamic, step-by-step response plans you need to stay ahead of new, complex threats. AI-driven, agent-based automation will empower your team to confidently handle any situation.

Not just any decision, either. Advanced security automation software serves up AI-driven insights. For instance, you can use AI to process images for context and generate new plans for novel challenges.

• Single, intuitive interface. To cut down the management burden of switching between security systems, your security automation solution should provide a single, intuitive interface for real-time event visibility across your video, access control, and radio assets.  

Indeed, the best solution for your needs will work natively with industry leading products, such as Avigilon Unity and Alta video and access control. They will also let you integrate with third-party security systems via an open API.

• No, on-premises hardware. These capabilities don’t mean much if you can’t get your solution up and running quickly. For this reason, the best software for your security automation needs is cloud-based, enabling rapid deployment across the SOC with smart defaults, factory settings, and a pre-built SOP library.

Conclusion: Securing the future of the SOC

The trend is clear: manual, traditional SOC can no longer withstand the glut of threats facing today’s enterprise. From the 3,000 daily alerts to analyst burnout and high turnover, the cost (and risk) of maintaining the status quo is becoming unacceptably high. Compliance is tenuous, and the organization's defensive posture is perpetually reactive.

Therefore, AI-driven SOC automation is necessary to secure the future of your security operations, as it directly tackles core challenges by:

• Cutting MTTR through automated threat mitigation
• Re-prioritizing analysts and operators toward strategic work by eliminating false alarms and automating SOPs
• Guaranteeing resilience by ensuring a consistent, scalable defense posture around-the-clock

The path forward: Choosing the right automation partner

But not all solutions are created equal, especially since your enterprise security needs demand a platform designed for speed and ease of deployment.

Platforms like Motorola Solutions’ Inform fit the bill – and then some. Leveraging AI-powered event triage, incident-specific intelligence, and AI-native incident responses, they help your security teams more effectively handle the increasing volume and sophistication of threats.

Our solution, by offering seamless integration with existing ecosystem technologies like Avigilon Unity and Alta, as well as your crucial third-party systems, creates a truly unified, proactive security system to safeguard your people, property, and continuity of business operations.

Ready to build a resilient SOC? Don’t wait for the next critical alert to expose the limitations of your current defense. Schedule a personalized demo to see exactly how Inform can transform your SOC operations while delivering demonstrable return on your security investment.