The Evolution of Cybersecurity Automation and AI Adoption
Market Research
The Evolution of Cybersecurity Automation and AI Adoption
By Leon Ward, Chief Transformation Officer
Based on new research from ThreatQuotient, a Securonix company
Automation has become the foundation of modern cybersecurity operations. What was once a tool for efficiency is now critical. In parallel, artificial intelligence is no longer just a buzzword; it is reshaping how organizations detect, analyze, and respond to threats.
The new Cybersecurity Automation and AI Adoption Report explores how global security leaders are approaching these technologies, what’s driving adoption, and where organizations still face challenges.
Automation Is Now Business-Critical
According to the research, 97% of respondents say automation is now business-critical. Security teams are under increasing pressure to respond to alerts faster, reduce mean time to detect (MTTD) and mean time to respond (MTTR), and deliver measurable outcomes to leadership.
Nearly 49% of organizations report receiving new budget for automation initiatives, confirming that investment in this area continues to grow even as other technology budgets remain tight.
The takeaway is clear: automation is no longer a nice-to-have efficiency upgrade. It is an essential enabler for operational resilience and threat visibility.
AI Is Moving from Hype to High Impact
The report shows that AI is rapidly finding practical footing in the SOC. The most common use case today is human-in-loop alert triage, where AI assists analysts in prioritizing and assessing alerts while final decisions remain human-led.
Organizations are adopting AI primarily to improve productivity and enhance decision-making, with efficiency gains emerging as a secondary benefit. As AI tools become more explainable and transparent, trust and confidence are expected to grow.
However, the journey is not without challenges. Ethical risks, security implications, and geopolitical concerns remain major obstacles to wider adoption.
The Leadership Paradox: Driving Innovation While Demanding Control
A central theme of the report is the Leadership Paradox. While executive leaders are the strongest advocates for adopting AI and automation, they are also the primary source of restraint. CISOs and senior leaders are pushing hard for modernization, yet they simultaneously insist on governance, transparency, and measurable ROI before scaling initiatives.
This paradox reflects a healthy tension within security leadership: a desire to innovate responsibly. On one hand, leaders recognize AI’s potential to reduce operational load, close skill gaps, and improve speed. On the other hand, they remain cautious about ethical risk, data integrity, and accountability.
Organizations that successfully navigate this paradox are the ones pairing innovation with explainability, empowering their teams to experiment within controlled frameworks.
Financial Services Leads the Way
Among industries, the financial sector stands out for its comfort with autonomous triage and data-driven security operations. Regulatory scrutiny and the need for real-time risk mitigation have accelerated AI experimentation in banking and financial services.
While some sectors are still testing pilot programs, financial institutions are already focusing on measurable outcomes — linking automation and AI initiatives directly to improved MTTD and MTTR metrics.
Regional Differences Are Emerging
Geographic analysis reveals distinct patterns:
- United States: Faster adoption of autonomous triage and analytics
- United Kingdom: Preference for human oversight and explainable AI
- Australia: Highest levels of new automation funding, though also more reports of system integration challenges
These variations highlight how culture, regulation, and risk appetite shape adoption strategies around the world.
From Automation to Intelligent Autonomy
The report emphasizes a clear path forward: automation is no longer about replacing manual tasks but about enabling intelligent, adaptive systems that augment human expertise.
Organizations that succeed will be those that:
- Make automation part of their core security strategy
- Measure ROI through operational outcomes, not just efficiency metrics
- Address leadership and trust challenges early
- Evolve incrementally toward explainable, autonomous operations
Recommendations for Security Leaders
Based on the findings, the report identifies several actionable steps for teams seeking to advance their automation and AI maturity:
- Start with measurable impact. Focus early AI and automation projects on areas with quantifiable outcomes such as alert triage, detection, or incident response time reduction.
- Build explainability into design. Ensure AI-driven systems can clearly justify their recommendations to build confidence among analysts and executives.
- Align leadership expectations. Bridge the leadership paradox by pairing bold innovation goals with transparent reporting and accountability measures.
- Invest in human expertise. Automation is most effective when it amplifies human skills, not replaces them. Ongoing training and upskilling remain critical.
- Plan for interoperability. Integrate automation and AI into existing workflows rather than bolting them on, minimizing disruption and improving adoption rates.
Research Methodology
The Cybersecurity Automation and AI Adoption Report is based on a global survey conducted by ThreatQuotient, a Securonix Company.
Scope and Participants:
- Over 750 cybersecurity professionals from the United States, the United Kingdom, and Australia participated
- Respondents included CISOs, Heads of SOC, Incident Response leaders, and Security Architect leaders
- Industries represented included Central Government, Defense, Critical National Infrastructure (Energy and Utilities), Retail, and Financial Services
Objective:
The goal of the research was to understand how organizations are moving from traditional rule-based security workflows to more adaptive, AI-powered operations — and to identify what separates early adopters from cautious observers.
Explore the Full Report
Read the complete research to see how perspectives on AI and automation differ by role, industry, and region, and discover where your organization stands on the path from automation to intelligent autonomy.
Download The Cybersecurity Automation and AI Adoption Report
