• A recent survey finds cybersecurity teams still spend on average 44% of their time on manual or repetitive work.
  • Despite widespread AI and automation adoption, burnout and inefficiency remain major problems for security teams.
  • Key reasons include tool sprawl, poor integrations, limited automation strategy, and skills gaps.
  • Experts say targeted process redesign, clearer metrics and focused automation pilots are needed to actually reduce burnout.

What the survey found

A recent survey reported that cybersecurity teams spend roughly 44% of their working time on manual or repetitive tasks, even as organizations race to deploy AI and automation tools. The headline is clear: installing automation doesn’t automatically free staff from tedious work or stop burnout.

Why AI hasn’t cut manual work — yet

There are several reasons widespread automation hasn’t translated into less repetitive work for security teams:

  • Tool sprawl and overlapping capabilities. Organizations often layer new AI tools on top of legacy systems without removing or consolidating older workflows. That creates more interfaces and manual handoffs.
  • Integration gaps. Many automation features require clean data pipelines and integrations. When systems don’t talk to each other, responders still chase alerts and move information manually.
  • Human oversight and trust. Security teams frequently retain manual steps because they don’t fully trust automated decisions for high‑risk actions such as blocking traffic or disabling accounts.
  • Skills and change management. Teams may lack the training or time to build, tune and maintain automation playbooks. Automation can add work if it isn’t implemented with clear ownership.

Why this matters: cost, retention and risk

When nearly half of a team’s time is tied to repetitive work, organizations face real consequences: increased burnout and turnover, slower incident response, and reduced time for threat hunting, improvement projects or strategic work. The money spent on AI licenses and pilots risks being wasted if automation simply creates more overhead instead of removing it.

Practical steps leaders can take

There is no silver bullet, but a focused approach can make automation deliver on its promise:

  • Prioritize use cases. Start with the highest‑volume, lowest‑risk tasks where automation can immediately reclaim analyst time.
  • Consolidate and integrate. Reduce tool sprawl; invest in integrations so data flows between systems without manual intervention.
  • Measure what matters. Track time spent on repetitive tasks before and after automation to prove ROI and build trust.
  • Invest in people. Train staff to develop and maintain automation playbooks and give clear ownership for automation outcomes.
  • Pilot, iterate and scale. Small, measurable pilots reduce risk and build confidence before wide rollout.

The bottom line

AI and automation offer potential, but the survey’s central finding — 44% of time still spent on manual work — shows that technology alone doesn’t solve operational or organizational problems. To actually reduce burnout, leaders must align tools, processes and people, and treat automation as a change program rather than a plug‑and‑play product.

Image Referance: https://securityboulevard.com/2026/02/survey-widespread-adoption-of-ai-hasnt-yet-reduced-cybersecurity-burnout/