AI won't solve cybersecurity burnout. Better leadership might

Can AI reduce cybersecurity burnout? The answer depends on leadership

Key takeaways

• AI is changing cybersecurity roles, but it is not eliminating the need for skilled security professionals. Organizations still need people who can apply judgment, communicate risk and make decisions. 
• Burnout remains one of the biggest challenges facing cybersecurity teams, despite widespread AI adoption. 
• The cybersecurity workforce challenge is increasingly about skills, mentorship and career development rather than simply hiring more people. 
• Organizations that use AI to augment teams, reduce complexity and develop future talent will be in a stronger position than those focused solely on short-term efficiency gains. 
• Technology matters, but leadership ultimately determines whether security teams thrive or burn out. 

Cybersecurity has spent years talking about workforce shortages. More recently, AI has entered the conversation as a possible solution. It can help teams analyze alerts, identify threats, automate investigations, and complete routine tasks faster than ever.

That shift is already underway. According to SANS workforce research, 74% of cybersecurity teams are changing structures and role assignments because of AI, with entry-level SOC and security analyst roles among the most affected. 

Yet workloads, complexity and stress continue to rise. The latest ISSA workforce study found that 68% of professionals believe their jobs have become harder over the past two years, and nearly half have considered leaving their current role. 

Why are cybersecurity professionals still burning out despite AI?

AI is already reshaping security operations. New roles focused on AI security, governance and machine learning are emerging as organizations define policies and workforce strategies around these technologies. 

The ISSA research found that 75% of respondents say cybersecurity skills shortages affect their organizations. Those shortages continue to increase workloads, contribute to burnout and place additional pressure on existing staff. 

The SANS research paints a similar picture. Nearly half of organizations report moderate-to-extreme skills gaps, and many say those gaps are delaying projects, slowing incident response and increasing burnout. 

In other words, AI is helping organizations do more, but it is not automatically reducing the amount of work teams are expected to handle. Security professionals are still defending more users, devices, applications and AI systems than ever. In many cases, AI is another responsibility rather than a replacement for existing work. 

Is the cybersecurity talent shortage really a skills shortage?

One of the more interesting findings from the SANS workforce research is that the industry's hiring problem is increasingly shifting from a headcount issue to a skills issue.

Sixty percent of respondents cited skills gaps as a greater challenge than staffing shortages, and 48% described their skills gap as moderate to extreme. 

During the accompanying Microsoft leadership discussion, speakers described organizations receiving thousands of applications while still struggling to find people with the specific skills required for emerging roles such as AI security. Many now need to develop the talent they already have, not simply hire more people. 

Could AI make the cybersecurity skills gap worse?

Historically, cybersecurity professionals developed expertise through hands-on work. Junior analysts learned by investigating phishing emails, triaging alerts, reviewing suspicious activity, documenting findings, and presenting recommendations. Over time, those experiences built the judgment and communication skills required for senior roles. 

AI can now perform or assist with many of those activities. That creates obvious benefits, but also raises a concern: If organizations automate away the work that traditionally trained junior professionals, how will they develop future defenders, architects and CISOs? 

Several speakers argued that this is ultimately a leadership challenge. AI should accelerate learning and eliminate repetitive work, but organizations still need development paths that help future security professionals build experience, exercise judgment and communicate effectively. 

How can organizations reduce cybersecurity burnout?

Cybersecurity burnout is not simply the cost of doing business in a digital world. The research points to several practical steps:

• Use AI to reduce repetitive work rather than eliminate learning opportunities. 
• Invest in mentorship, training and career development. 
• Give junior team members ownership and responsibility rather than relying entirely on automated systems. 
• Involve security professionals earlier in technology decisions. 
• Simplify operations and reduce unnecessary complexity wherever possible. 

Perhaps most important, leaders need to view AI as a tool for supporting people rather than replacing them.

Technology can help reduce the burden

Leadership and workforce development are essential, but teams also need practical ways to reduce day-to-day pressure.

Many burnout factors stem from alert overload, staffing shortages and growing environmental complexity. Security teams must monitor more users, applications, devices and cloud services, often with limited resources and rising business expectations. 

This is where technology can help. Simplifying operations, automating repetitive tasks and reducing disconnected tools can give analysts more time for higher-value work. For organizations without resources for a fully staffed 24/7 security operation, services such as Barracuda Managed XDR can provide continuous monitoring, threat detection and expert support. The goal is not to replace your team, but to reduce operational burden, cut noise and help security professionals focus on protecting the business. 

Strong leadership remains the best defense against burnout

The organizations that succeed in the AI era will not necessarily be the ones with the most AI tools. They will combine intelligent automation with intentional workforce development. They will use AI to eliminate tedious work rather than learning opportunities, invest in mentorship alongside technology and give security teams the support they need to succeed. 

AI will continue to change cybersecurity work. It can make teams more efficient, and platforms and services can reduce complexity. But burnout, retention and workforce development remain leadership challenges. Long-term success depends on leaders who invest in people, develop future talent and create environments where security professionals can thrive.