AI in Cybersecurity: How Artificial Intelligence Transforms Security Defense
| 6 Min Read
The widespread adoption of artificial intelligence (AI) tools is driving innovation across industries, and cybersecurity is no exception. In recent years, AI has had a significant impact on job responsibilities and competency requirements for cybersecurity roles.
In a recent survey, 96 percent of decision-makers agreed that AI technology “will be critical for the future of organizational cybersecurity.”1 In addition, 68 percent said they were currently using cybersecurity tools that include AI. With the global AI market size reaching $279.22 billion in 2024,2 it’s clear that AI integration will continue to be a key component of organizational operations.
Benefits of AI in cybersecurity defense include increasing detection speed, reducing errors, and leveraging impressive predictive capabilities.1 It can also streamline workloads, empowering teams to focus their efforts on higher-value tasks.
How Can Generative AI Be Used in Cybersecurity?
While AI has been used in some form for cybersecurity since the 1980s, recent advancements have revolutionized the technology and its applications. Specifically, generative AI, which uses natural language processing to create new content by learning from existing data, is a powerful tool for investigation, analysis, and response.
- Threat detection: Generative AI can identify potential threats, conduct real-time analysis, and simulate attacks to help teams enhance their response capabilities.3
- Incident analysis: Teams can use generative AI to streamline the process of extracting insights from complex cyber threat intelligence.3
- Response automation: With automated workflows, AI can respond as soon as threats are detected. Faster response times are critical for mitigating the damage caused by cyberattacks.4
Machine Learning Applications in Cybersecurity
Advances in machine learning (ML) began to accelerate in the early 2000s. A subset of the larger category of AI, ML uses algorithms trained on large data sets to “learn” without being programmed.5 Cybersecurity teams can train models to identify patterns, solve problems, and make predictions.3 The following are some of the ways ML can be used in cybersecurity defense:
- Automated incident classification and triage: ML systems categorize and prioritize security alerts based on severity and threat type. Integrating ML with security orchestration, automation, and response (SOAR) tools allows organizations to automate workflows so that cybersecurity teams can focus on more complex investigations.
- Behavior analysis and anomaly detection: ML algorithms can learn normal user and network behaviors to identify irregularities and potential threats, such as insider attacks and zero-day malware. For example, they can detect unusual logins, abnormal file access, and suspicious network traffic that traditional signature-based systems would miss.
- Predictive threat intelligence: The ability to forecast potential threats and vulnerabilities based on historical data makes ML a powerful security tool. ML can analyze data to predict attack campaigns, identify emerging threat trends, and more.4,6
Cybersecurity AI Tools
From faster threat detection to simplified reporting, the advantages of AI-powered security are significant. When asked which aspects of cybersecurity will benefit the most from AI technology integration, surveyed decision-makers ranked network security and identity and access management (IAM) the highest, followed by behavioral analytics, automated response, and endpoint detection and response.1 But which cybersecurity tools already utilize AI? Explore the following examples to learn more:
- Cloud security solutions: Many organizations today rely on cloud storage for large amounts of data, making it challenging to track threats on multiple fronts. AI can analyze data across all of an organization’s cloud environments to identify threats.3
- Endpoint security solutions: Cybersecurity teams use AI to find vulnerabilities in endpoints like laptops and mobile phones. AI can also be used to scan these devices for suspicious activity.6
- Internet of Things (IoT) security: AI can detect threats to IoT devices and monitor patterns of suspicious activity across multiple devices.3
- Next-generation firewalls: Traditionally, firewalls have relied on administrators to create rules that determine what traffic is allowed or blocked. Next-gen firewalls offer advanced detection and prevention thanks to AI, improving network security.3
- Security information and event management (SIEM): SIEM solutions that utilize AI can easily analyze information from multiple sources and synthesize patterns and findings into clear, actionable insights.3
Will AI Replace Cybersecurity Jobs?
The future of human-AI collaboration in cybersecurity is promising. New AI technologies have been transformative for the industry, with skill sets and job categories emerging to keep pace with advancements. Cybersecurity professionals are uniquely positioned to leverage the high-impact benefits of AI tools within their organizations as subject matter experts.
Today’s cybersecurity leaders need a comprehensive skill set, including traditional security training, data science knowledge, machine learning expertise, and more. Demand for these professionals is high: A 2023 jobs survey found that there were 750,000 unfilled cybersecurity positions in the U.S. alone.7
Emerging Roles in AI-Powered Security
The following roles8 combine human cybersecurity expertise with AI technology, addressing the need for leaders who can harness the power of AI for organizational success:
- AI cybersecurity analysts utilize AI and ML tools to identify potential vulnerabilities and implement response strategies that protect systems from attack.
- AI/ML security engineers develop and deploy secure AI and ML systems while monitoring for cyberattacks that specifically target AI.
- AI security operations consultants are strategic advisors who work with organizations that don’t have strong AI resources internally to identify ways AI can streamline operations and improve security.
- GenAI security development managers lead teams of analysts and developers who build controls and strategies tailored to the organization’s unique generative AI needs.
Prepare for an AI-Enhanced Cybersecurity Career
Humans play an essential role in making the most of AI and applying it in ways that drive sustainable growth. For forward-thinking organizations, AI’s value lies in its use as an enhancement tool rather than a technology to replace workers.
In our evolving tech landscape, tech leaders need a deep understanding of AI capabilities and applications. You can stay on the cutting edge of cybersecurity developments with the online Master of Science in Cybersecurity degree from the Middlebury Institute of International Studies.
Online Cybersecurity Education from the Middlebury Institute
As a CompTIA Authorized Academy partner, the Middlebury Institute provides M.S. in Cybersecurity students with specialized exam preparation. You will graduate qualified to sit for the CompTIA Security+ and CompTIA Cybersecurity Analyst (CySA+) exams.
Middlebury has also partnered with cybersecurity company Recorded Future, giving students access to an industry-leading threat intelligence platform utilizing AI. In addition, our curriculum aligns with the National Institute of Standards and Technology (NIST) NICE Cybersecurity Workforce Framework.
Whether you want to enter the dynamic world of cybersecurity or are ready to advance in your current role, we can help you achieve your goals. Explore online cybersecurity education from the Middlebury Institute today.
Sources
- Gartner. “AI Adoption in Cybersecurity Tools.” Retrieved September 2025, from https://www.gartner.com/peer-community/oneminuteinsights/omi-ai-cybersecurity-qrl.
- Grand View Research. Artificial Intelligence Market (2025-2033). Retrieved September 2025, from https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market.
- Microsoft. “What Is AI for Cybersecurity?” Retrieved September 2025, from https://www.microsoft.com/en-us/security/business/security-101/what-is-ai-for-cybersecurity.
- IBM. “What Is AI Security?” Retrieved September 2025, from https://www.ibm.com/think/topics/ai-security.
- Google Cloud. “What Is Machine Learning (ML)?” Retrieved September 2025, from https://cloud.google.com/learn/what-is-machine-learning.
- Fortinet. “AI in Cybersecurity: Key Benefits, Defense Strategies, & Future Trends.” Retrieved September 2025, from https://www.fortinet.com/resources/cyberglossary/artificial-intelligence-in-cybersecurity.
- Cybersecurity Ventures. Cybersecurity Magazine. “Cybersecurity Jobs Report: 3.5 million Unfilled Positions In 2025.” Retrieved September 2025, from https://cybersecurityventures.com/jobs/.
- TechTarget. 4 AI cybersecurity jobs to consider now and in the future. Retrieved September 2025, from https://www.techtarget.com/searchsecurity/tip/AI-cybersecurity-jobs-to-consider-now-and-in-the-future.
