Traditional security models can’t keep up
Most security operations centers (SOCs) still run on outdated workflows. These are linear, ticket-based systems. That made sense a decade ago. Not today. The scale and complexity of threats have exploded. Attackers are now using AI to improve speed, precision, and unpredictability. Security teams are stuck doing things manually, and that’s the real problem.
We’re seeing alert volumes rise so fast that no organization can hire their way out of it. Chris Drumgoole, President of Global Infrastructure Services at DXC Technology, explains it clearly: If you tried to process every alert manually, your SOC would need to be the size of your customer service department. That’s not sustainable. It also wastes time, expertise, and money.
This is about threats being smarter. AI is now being weaponized. Threats don’t come in neat, repeatable patterns anymore. Traditional SOCs weren’t built for this. They’re slow, reactive, and built for a different era.
If you’re still relying on legacy SOC workflows, you’re giving attackers an unfair advantage. It’s not a staffing problem. It’s a model problem. The math doesn’t work anymore. Staying with old models is like telling your team to run a 100-meter sprint with weights on each leg. You can try, but you won’t win.
Executives need to stop seeing this as a technical issue. It’s strategic. Cybersecurity isn’t just IT’s problem, it’s a business risk. If your SOC can’t operate at speed and scale, you’re exposed. And attackers won’t wait for you to catch up.
AI-powered agents change the game in cyber defense
If your security team still handles alerts one by one, you’re already behind. The new model is agentic security, AI-powered agents that autonomously review, triage, and respond to incidents. No scripts. No predefined paths. These systems learn, adapt, and evolve.
This isn’t basic automation. It’s advanced AI. And it’s working now, not sometime in the future. At DXC Technology, they implemented an agentic platform developed by 7AI. The impact was immediate: 80% less demand on tier-1 analysts. 95% fewer alerts that needed a human to look at them. They also cut response time across their SOC by 67%. That’s not gradual improvement. That’s system evolution.
Chris Drumgoole described it well. Your old automation tools respond the same way every time. AI agents don’t. They analyze context, recall prior incidents, and make decisions based on the nuances of the situation. That’s a step change in capability.
We’re not talking about removing people. We’re talking about getting the machine to take care of what it’s good at, volume, speed, repetitive decision-making, so your experts can work on strategic risks. Let the agents handle the noise.
This system is not static. The longer it runs, the smarter it gets. It continuously learns from every threat it sees. That’s useful if you’re serious about reducing false positives and speeding up real-time decisions.
If you’re leading a company today and you’re still using traditional noise-heavy tools, it’s time to move on. Not because it’s trendy, but because it works. This is not marginal gain. This is exponential security performance.
Agentic SOC systems deliver real efficiency and time gains
Speed matters in cybersecurity. Any delay can widen the window for damage. Traditional SOC processes introduce delay by relying on humans to review every alert. That doesn’t scale. Agentic SOCs change this by using AI agents to eliminate bottlenecks and reduce false positives, fast.
With the Agentic SOC deployed at DXC, investigation times dropped from 74 minutes to 24. That’s a 70% improvement. In just 40 days, the platform saved 165 days of human analyst time. This isn’t a minor improvement, it’s redefining how time and talent are used inside security operations.
When you reduce the time it takes to process each alert, you reduce the overall risk exposure. Your security team can shift focus from reacting to repetitive noise to dealing with real threats. Instead of constantly catching up, the team can plan, prioritize, and act strategically.
AI isn’t just saving seconds and minutes. It’s restructuring team workflows. This has the secondary effect of improving morale. Security professionals are no longer drowning in alerts. They have time to use their expertise where it has impact. That leads to better retention, less burnout, and higher-quality threat response.
For executives, the takeaway is simple: invest where measurable gains are proven. If a solution reduces workload, increases speed, and boosts accuracy, it’s not optional. It’s fundamental to operating securely at enterprise scale.
Resistance to AI in security is driven by habit, not capability
Many companies are slow to adopt AI in cybersecurity, not because the tools don’t work, but because change is uncomfortable. Teams rely on familiar processes. Introducing AI into a human-centered workflow forces adjustments, retraining, and a mindset shift across teams.
Chris Drumgoole from DXC Technology pointed this out directly. The resistance to AI isn’t technical. It’s emotional and procedural. People are wary of disrupting processes that “have always worked.” That mindset limits progress and leaves opportunities untapped.
This hesitation wastes time. Every day spent debating the value of AI security tools is a day lost managing threats less efficiently. The AI doesn’t need access to personal data. It works off the same protocols and controls a human analyst would use. Implementation is straightforward. It doesn’t require rebuilding your infrastructure. And yet, hesitation persists.
Executives need to confront this directly. Your teams might be comfortable, but that doesn’t mean they’re protected. Pushing through inertia is part of leadership. If a system performs faster, smarter, and with less human fatigue, it deserves support.
Adopting agentic AI doesn’t mean removing people. It means giving them tools that expand their effectiveness. In complex environments, these tools are not simply helpful, they’re foundational. Sit idle, and threats will keep evolving while internal processes lag behind. Move forward, and you’ll be ready before they arrive.
Executive leadership must drive AI security adoption or risk falling behind
AI isn’t a side project. It’s not something to hand off to middle management to explore “when there’s time.” Implementing agentic security tools requires top-level leadership. Without executive commitment, organizations will stall in outdated models while attackers keep advancing.
Chris Drumgoole, President of Global Infrastructure Services at DXC Technology, put it directly: If you don’t evolve now, you’re going to become a dinosaur, fast. That’s not hype. That’s a fact supported by results. DXC deployed agentic AI into its own SOC, saw faster response times, cut human investigation workload, and automated routine decisions at scale. They treated the rollout as a strategic initiative, not a technical experiment. That mindset made all the difference.
For executives, the expectation is clear. Leadership isn’t just about approving budgets. It’s about setting direction. Change management starts at the top. When leaders commit to operational AI and align the teams behind it, transformation happens quickly. AI agents don’t require a change in infrastructure or access to sensitive data. They don’t burden compliance. What they need is access equivalent to your human analysts, and the support to be trained and deployed at scale.
Treating AI agents as a direct extension of your security workforce is the simplest way to frame their value. They don’t replace humans, they multiply what your team can accomplish with the same budget and footprint. But that wider capability doesn’t happen passively. It only happens when executive teams back it and accelerate its rollout.
If you’re waiting for a clearer sign, you’re missing the point. 165 analyst days saved in 40 days. 70% faster incident investigations. 95% fewer false positives for humans to sort. The upside is already measured. The risk is in doing nothing.
Leaders who push AI forward today will build more resilient, scalable organizations. Those who delay will spend more time catching up, and more money fixing problems they could have prevented earlier.
Key highlights
- Traditional SOC models are no longer sustainable: Legacy ticket-based workflows can’t keep up with today’s AI-driven threat volume and complexity. Leaders should reassess security operations for scalability and speed.
- AI agents are redefining threat detection and response: Autonomous AI systems reduce human workload and improve accuracy by contextualizing and learning from each incident. Invest in adaptive AI tools to shift from reactive to dynamic threat defense.
- Agentic SOCs cut response time and boost efficiency: AI-driven SOCs cut investigation times by 70% and saved DXC 165 analyst days in 40 days. Prioritize deploying these systems to accelerate response and reduce operational drag.
- The real barrier to adoption is mindset: Resistance stems from comfort with outdated workflows, not from technical limitations. Executives must drive cultural change to unlock AI’s full impact on cybersecurity.
- Executive backing determines transformation success: AI adoption requires top-down support to overcome inertia and integrate agents at scale. Treat AI-powered security assets as core operational extensions, not side experiments.
