Accelerating Security Outcomes: 2025 State of AI-Driven Security Automation

BlinkOps recently announced our inaugural 2025 State of AI-Driven Security Automation report. We surveyed over 1,000 security professionals to understand how teams are using AI-driven automation, where they’re struggling, and how they plan to adapt to keep pace with fast-moving threats.

In this blog, we’ll walk through the top findings from our first-ever report, explaining what each one means for CISOs and security teams looking to respond faster and smarter to the risks ahead.

Survey Background and Methodology

Who We Talked To

The survey includes insights from 1,000 security leaders and practitioners in the United States, from industries like technology, finance, healthcare, manufacturing, and government. Participants included CISOs, heads of security operations, SOC managers, security engineers, and frontline analysts, each with a unique vantage point on the adoption of AI and automation.

How We Gathered Data

We focused on questions that reveal where and how security teams use AI-driven automation today, the speed of that adoption, the organizational barriers they face, and the future roadmap each sees for security operations. By exploring these areas, we aimed to provide a holistic view of what “AI-driven security automation” looks like in actual practice.

Key Findings from the Report

1. Time to Automation (TTA) Is Now the Most Important Security Metric

45% of organizations took nearly three months to implement their most recent security automation initiative.

This data point underscores what security professionals have known for years: attackers move in seconds, but it can often take security teams longer to respond. Nearly half of surveyed teams took nearly three months to bring automated workflows live. This mismatch highlights Time to Automation (TTA) as the crucial metric for the modern SOC. In an environment where seconds count, a three-month roll out can translate into massive exposure and risk.

But it’s not all doom and gloom. 

The survey shows that teams achieving shorter TTAs (often under a month) share a few traits:

• Dedicated automation ownership (a designated team or individual overseeing automation projects)
• Prioritized workflows focusing on the highest-frequency, highest-risk use cases first
• Low-code or no-code tooling that reduces deployment friction
• Clear escalation and rollback pathways to ensure safe, consistent automation
  
  

As we’ll see later, addressing these factors helps organizations dramatically decrease the lag between identifying a security incident and implementing an automated response.

2. AI-Driven Automation as a Strategic Imperative

81% of security leaders say automation is “very important” or “critically important” to their strategy over the next 3–5 years.

For most respondents, automation is a core component of strategic planning. Executives now see it as essential for handling the speed and complexity of incidents. And they’re making choices, from budget decisions to technology stack selection, to make sure AI-driven automation is baked into daily operations.

3. Appetite for Agentic AI Is Growing Rapidly

• 27% say they expect AI to operate autonomously in key security areas
• 52% plan for AI to make complex decisions under some human oversight
• Only 3% do not plan to use autonomous AI at all
  

We’re witnessing a jump from automated task execution to automated decision execution. This means AI agents recommend next steps but also act. This could be isolating devices, enforcing policy blocks, or triggering workflows based on risk thresholds. Security teams are no longer content with AI that only flag anomalies; they want AI that proactively contains incidents in real time.

That said, oversight and trust remain paramount. Many organizations focus on building guardrails. This includes pre-approved escalation paths, and robust audit trails, so that agentic AI can act quickly and transparently. 

As adoption grows, the challenge is balancing speed with safety, making sure that an AI agent doesn’t accidentally block legitimate operations or cause disruptions in a production environment.

4. Security Workforce Pressures

The “people” factor surfaced as another theme. Teams are stretched thin, and the demand for specialized automation or AI skills outstrips supply. Traditional security roles require a heavy dose of manual processes, such as alert triage, threat classification, and incident reporting, leaving little time to build or maintain complex automation workflows.

Moreover, 35% admit their teams lack the skills to manage automation beyond basic levels. This shortfall explains why many security leaders are exploring low-code or no-code automation platforms that remove the need for constant developer input. 

The same dynamic is driving a structural transformation within SOCs:

• 45% plan to create a centralized “automation team” focused on workflow design, governance, and cross-functional coordination.
• 46% expect more analysts to shift into oversight roles, managing automated responses and investigating exceptions.
  

These shifts signal that scaling automation is both a technology and organizational challenge.

5. Automation Maturity Remains Limited, But Focus Is Clear

Despite the enthusiasm, only 6% of organizations claim to have fully embedded automation into daily operations. The majority are either experimenting with isolated workflows or only beginning to build a cohesive strategy. This partial adoption often leads to fragmented coverage and longer response times when new threats arise.

Yet the commitment to expand is high. Half of the respondents have automation as a core part of their long-term roadmap, and another third are formulating a strategy now. This trajectory suggests a future where continuous, AI-driven automation underpins everything from threat detection to forensic investigation.

The Next Era of Security Operations

From Task Execution to Decision Execution

Traditional security automation typically follows a linear workflow, such as collecting logs, enriching data, alerting a human, and waiting for action. Today, AI is accelerating this sequence into real-time detection and containment, drastically cutting the window of attacker opportunity. Agentic workflows that automatically isolate a suspicious host or block specific types of network traffic are becoming more common, with the human in the loop primarily for oversight and exception handling.

Centralized Automation Teams and Role Evolutions

Many organizations now see automation as an infrastructure-level function, such as networking or DevOps, rather than a side project. As a result, centralized teams of specialists and architects are springing up to oversee:

• Workflow Design: Building, documenting, and updating playbooks
• Platform Integration: Connecting the SOC’s wide array of tools
• Governance: Ensuring auditability, control, and risk management
  

Simultaneously, SOC analysts are transitioning away from purely manual tasks. Instead, they focus on auditing automated actions, fine-tuning risk thresholds, and investigating the most sophisticated threats. This shift reduces burnout and creates a more strategic role for frontline practitioners.

Strategic Focus on Faster, Simpler Deployments

Finally, speed is everything in security. Successful organizations prioritize short TTA cycles, enabling them to adapt workflows rapidly as new threats emerge. This agility hinges on using automation platforms that are accessible to non-developers, establishing clear lines of ownership, and embedding iterative improvements into the daily SOC routine. By measuring how quickly they can turn detection needs into live automations, teams can stay on par with or ahead of evolving threats.

Recommendations for Security Leaders

1. Prioritize High-Impact Workflows
   Start small with common issues like alert triage, phishing detection, or identity-based policy enforcement. Demonstrating quick wins helps secure executive buy-in and justifies broader rollout.
   
   
2. Invest in Skills and Simpler Tools
   Address the talent shortage by training existing staff and selecting low-code/no-code platforms that expand who can build automations. This approach frees engineers for deeper projects and fosters a more engaged workforce.
   
   
3. Balance Autonomy with Governance
   Agentic AI can dramatically cut response times, but only if you have the right guardrails in place. Define where full autonomy makes sense versus when human oversight is mandatory, and keep detailed audit logs for every AI-driven action.
   
   
4. Measure and Optimize Time-to-Automation (TTA)
   Time to Automation serves as a practical, outcome-based metric. Track how long it takes to go from scoping a new workflow to seeing it in production. Strive to shrink that window with every iteration.

Looking Ahead

Continuous Innovation in AI-Driven Security

AI-driven security platforms are promising improvements in real-time anomaly detection, advanced correlation, and more refined automation triggers. We can expect an ever-growing market of vendor solutions and open-source tools that aim to make automation more accessible and powerful.

Evolving Threats Demand Constant Adaptation

Attackers continually adapt their tactics in the face of new defenses, making a static or overly rigid security posture insufficient. As AI-driven solutions become more common, so will adversarial techniques to evade or manipulate them. This evolving arms race underscores the importance of continuous improvement and iteration.

Dive Deeper into the Report

This blog only scratches the surface of the insights gleaned from our 1,000 survey respondents. The full 2025 State of AI-Driven Security Automation Report includes detailed metrics for deeper exploration. It also provides practical roadmaps for tackling skill gaps, building centralized automation teams, and driving trust in autonomous decision-making.

The Bottom Line

As the pressure on security teams intensifies, AI-driven automation stands out as the most viable path forward, offering the speed, consistency, and scale modern security demands. But technology alone isn’t enough. The report’s findings show that organizational alignment, a focus on Time to Automation, and careful governance are all crucial to bridging the gap between aspiration and reality.

Ready to take the next step?

• Download the full 2025 State of AI-Driven Security Automation Report to see all the data in one place.
• Begin evaluating your own TTA, skill needs, and strategic roadmap.
• Join the conversation. Let us know how AI-driven automation is transforming your security operations.
  

It's our hope that what we've learned together can make your security work feel less like an endless sprint and more like a manageable challenge.