The global cybersecurity skills gap is a growing crisis, especially in light of the increasing prevalence and sophistication of cyber threats. Stakeholders are interested in whether artificial intelligence will help address or exacerbate the significant shortage of cybersecurity professionals.
Understanding the global cybersecurity skills gap
Reliance on technology has outpaced the growth of the global cybersecurity workforce. According to a World Economic Forum report, only 14 percent of organizations believe they have the necessary workforce and skills to meet their cybersecurity objectives. Many individuals are discouraged from pursuing careers in cybersecurity due to outdated training, expensive certifications, a lack of clear career paths, and job stress.
Workforce shortages create concerns for innovation, businesses, and the nation. The average cost of a malicious data breach reached $4.88 million in 2024, marking the most significant increase since the pandemic. The health care and finance industries face the highest breach costs. Along with financial concerns, these breaches can result in data theft and fraud, operational and supply chain disruptions, reputational damage, and regulatory penalties.
Limitations of traditional solutions
While conventional methods exist to combat cybersecurity threats and mitigate incidents, they often fall short. Firewalls, antivirus software, intrusion detection or prevention systems, patch management, and other common solutions rely on signature-based rules. They are reactive and sometimes fail to detect advanced threats that don’t match static, known signatures.
The available supply of cybersecurity workers is struggling to meet the high demands of employers. Job seekers may not already possess the advanced security and incident response skills necessary, so they require extensive training and upskilling up front. These limitations also fuel fierce talent competition in the industry, making it more challenging to recruit new employees and retain existing ones who other companies are pursuing.
4 ways AI is being used to fill the gap
AI is becoming a critical asset across industries, including cybersecurity. Here are key ways that developers and stakeholders believe it can help combat the global cybersecurity skills gap.
1. Accelerating threat detection and response
By identifying and containing threats at a faster pace, AI has helped decrease the cost of a data breach by 9 percent in 2025. It can analyze large amounts of data faster than human analysts to predict future attacks or identify vulnerabilities.
2. Automating routine cybersecurity tasks
AI and machine learning models are often trained on alert triage, log analysis, and vulnerability scanning. When this technology can efficiently handle repetitive and time-consuming tasks, human professionals can focus more on complex and strategic work.
3. Supporting security operations centers
In-house, outsourced, or hybrid security operations centers (SOCs) continuously monitor cybersecurity threats targeting an organization. SOCs are essential for centralized control and improving response capabilities. However, this dedicated staff isn’t infallible, with human error responsible for over 80 percent of cyber incidents. AI can aid SOCs by identifying potential threats that human analysts might miss. It can analyze data and provide actionable insights to improve decision-making.
4. Aiding cybersecurity training and upskilling
AI tools can serve as virtual assistants, enabling human cybersecurity professionals to tackle complex tasks and refine their skills through additional training. When implemented in training programs and learning paths, AI can tailor the content to address the employee’s weak points and provide instant, personalized feedback.
Potential pitfalls of AI in cybersecurity
While cybersecurity professionals can use autonomous AI bots for routine tasks and to assist with training, cybercriminals can also use autonomous AI to carry out attacks. These bots are trained to infect software and steal sensitive data, even without human intervention. AI-powered threats can become more adaptive and adversarial. Weaponized AI and machine learning capabilities heighten the following risks:
- Data pools contaminated with misleading information
- Malware that can evade detection
- More convincing phishing attempts
- Deepfake-based social engineering attacks
Additionally, the use of AI in an organization carries the risk of overreliance and erosion of existing skills. When people delegate too many tasks to AI, human professionals lack practice in analysis, problem-solving, and other cognitive skills. This reduction in critical thinking can lead employees to trust AI results without a second thought. If the AI tool makes an error, there can be significant consequences.
Balancing opportunity and risk
AI is a powerful tool for cybersecurity when used wisely. Decision-makers should adopt a holistic approach that combines technical safeguards and employee education. Establish robust oversight to prevent overreliance on the technology, which includes routine inspections and corrections to ensure accurate data and eliminate biases. There should be a balance between human judgment and AI outputs. Namely, AI can recommend actions and solutions, while humans in the loop make final decisions.
Organizations must train employees in both cybersecurity operations and AI best practices. AI-powered threats are becoming more prevalent, and the misuse of AI tools can lead to new security risks. Continuous workforce development often involves basic security awareness training for all employees, secure data handling practices, recognizing cyber threats, and understanding incident response plans. Workers should also understand new AI-enabled cybersecurity attack patterns and how to adhere to regulations regarding data collection and processing.
Businesses and organizations implementing AI technology in their cybersecurity operations must stay current with the latest AI-driven threats to ensure their cybersecurity measures evolve in tandem.
Will AI close the gap?
Innovations in AI and machine learning can support the global cybersecurity workforce by providing advanced insights and automating security tasks. However, they also have the potential to lower human critical thinking and aid cybercriminals in developing more sophisticated attack methods. Tech innovators and business owners must consider both the potential and challenges of AI when implementing it in cybersecurity.
Zac Amos is the Features Editor at ReHack Magazine, where he covers business tech, HR, and cybersecurity. He is also a regular contributor at AllBusiness, TalentCulture, and VentureBeat. For more of his work, follow him on X (Twitter) or LinkedIn.
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