Alert fatigue? Manage alerts with AI and cybersecurity experts

In an environment where the volume of threats is growing and the pressure to protect critical assets is constant, oragnizations and managed service providers (MSPs) are inundated with notifications. Prioritizing critical vulnerabilities takes time, resources and careful analysis. However, false positives also slip into this constant flow of alerts. Far from being harmless, these false alarms can create an even bigger problem: alert fatigue.

On average, each false alert consumes 15 minutes to check out. This wastes time that could be better spent on responding to major incidents. Information overload not only exhausts security analysts mentally, but also creates blind spots that attackers can exploit. Genuinely critical alerts may get buried under the mass of irrelevant notifications, turning noise into yet another threat. 

The challenge is no longer to detect more, but to detect smarter. And that’s more important than ever because attackers are now using AI too. From automating phishing emails with near-perfect language, to deploying polymorphic malware that changes on the fly, adversaries are weaponizing AI to sclae their attacks and slip past traditional defenses. According to IBM, only  9% of organizations monitor 100% of their attack surface. This figure shows there is plenty of room for improvement, especially at a time when both businesses and MSPs face constant pressure to optimize resources, scale their operations and maintain continuous protection.

How to address this situation? AI-based triage and expert supervision

Despite the benefits it brings, only 28% of cybersecurity professionals use AI to reduce false positives. This figure is surprisingly low considering that combining artificial intelligence and machine learning (AI/ML) with human expertise delivers a perfect operational solution to today's challenges. Thanks to this synergy irrelevant alerts are filtered out, real threats are detected more accurately and alert fatigue is decreased drastically. For enterprises and MSPs, integrating AI/ML with expert analytics not only improves efficiency, but transforms the way they prioritize and respond to vulnerabilities.

At WatchGuard, we use AI across multiple dimensions:

• Behavior-based anomaly detection learns what’s normal in your environment and flags deviations. For example, our Sixth Sense detection looks at over thousands of behavioral signals across endpoints and Microsoft 365.
• Supervised learning models trained on suspicious logins help detect credential misuse with low noise.
• Automated response tools act in real time, isolating devices or containing malware before it spreads.

 Here are the key benefits:

1. Filtering out the noise and finding real threats: AI/ML-based platforms detect deviations in behavioral patterns accurately. By reducing false positives, prioritization is streamlined and distractions are avoided. This allows you to focus on what really matters: critical threats.
2. Timely response: Rapid response is vital. MSPs that offer continuous monitoring, combined with risk scoring algorithms, will be able to act in real time, contain incidents faster and minimize impact, even in resource-constrained environments.
3. Expert support: For SMEs or teams without large resources, working with specialized partners ensures that incidents are validated and contextualized by experts. This provides a strong response and removes the need to expand the internal team.
4. Gaining visibility and confidence: Centralizing security data on intelligent platforms allows you to see the big picture, identify hidden patterns and anticipate incidents. It also facilitates regulatory compliance and generates greater confidence in decision making.

This all positions MDR as a robust, aligned solution to reduce alert fatigue. By covering the entire IT environment, we find and stop more with our AI. As opposed to reactive or preventive models, managed detection and response services that integrate SOC models provide customers and MSPs with advanced detection technologies, artificial intelligence and 24/7 monitoring. This stops the team from suffering operation exhaustion and delivers proactive, enterprise-customized protection.

For businesses, this combination means access to expert security coverage without having to expand their internal teams. For MSPs, it is a way to scale their services without adding operational complexity or overloading analysts. By delegating part of the triage to AI-based solutions, both gain in agility, effectiveness and alert noise is reduced. AI and expert monitoring do not compete against one another, they enhance each other. Together, they deliver technical improvements and represent a strategic evolution towards a more efficient, scalable cybersecurity ready to meet today's challenges.