AI in Cybersecurity Statistics By Benefits, Cost, Threat, Prevention Tools and Innovations

Introduction

AI in Cybersecurity Statistics: Artificial intelligence quickly changes cybersecurity by offering smart tools that help stop, find and respond to complex online threats. Since huge amounts of data are created daily, older security methods often can’t keep up. That’s why AI-powered systems are now important for quickly checking data in real-time and spotting dangers.

Reports show a big increase in the use of AI in cybersecurity, with many companies using machine learning, behavior tracking, and automatic response tools to improve their protection. This growing use of AI highlights how important it has become in strengthening security and reducing the damage caused by cyberattacks. This article will shed more light on AI in Cybersecurity Statistics.

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• Almost 61% of companies’ security analysts said they can’t detect breach attempts today without AI technologies. AI can decrease the time it takes to find threats by up to 90%.
• AI in Cybersecurity Statistics stated that around 75% of cybersecurity teams have adopted AI to mitigate cybersecurity risks.
• Organisations with no security AI and automation averaged $7 million for each breach, although a company with a fully developed system stated a cost averaging almost $3 million.
• Global security and risk management revenue is predicted to reach above $150 billion by 2027.
• 80% of security professionals think AI helps improve protection, while 20% are more concerned about its possible dangers in cybersecurity.
• 85% of IT leaders believe using AI-based security systems is the only real way to stop AI-driven threats.
• According to an IBM survey, 67% of businesses already use AI in their security plans, and 31% depend on it heavily.
• IBM’s AI-powered Threat Detection and Response team monitors over 150 billion security events daily.
• AI tools are expected to make the biggest difference in cloud protection, data safety, and computer network security.
• Cybercrime damages are forecasted to surpass $10 trillion in 2025, a 300% jump compared to a decade ago.

Benefits of AI in Cybersecurity

Artificial intelligence (AI) is having a major impact on many industries, including cybersecurity. A recent study found that the global market for AI-powered cybersecurity tools was worth about $15 billion in 2021. This number is expected to grow to nearly $135 billion by 2030.

Cybersecurity teams now use AI and older tools like antivirus software, fraud prevention, data protection, identity verification, access control, threat detection, and risk assessment. Since AI can go through massive amounts of data and find patterns, it’s especially useful for:

• Spotting real cyberattacks more accurately than people, with fewer false alarms, and ranking threats by how dangerous they are
• Catching suspicious emails and messages used in phishing scams
• Running test attacks (like social engineering) to find weak spots before hackers can use them
• Quickly reviewing tons of security data so teams can respond faster to stop the threat

AI can also play a key role in penetration testing, where systems are purposely tested for flaws. If businesses use AI to test their own systems, they can discover and fix problems before cybercriminals find them.

This smart technology gives cybersecurity teams a better chance to stop attacks early. Preventing security breaches protects personal and business data and can help companies save money on IT costs.

Cost of Frequency of AI cyberattacks

(Reference: statista.com)

• Cybersecurity experts say the biggest AI-related dangers include spreading malware, taking advantage of system flaws, leaks of private data through generative AI, tricking people through social engineering, unknown threats like zero-day attacks, and scanning systems to prepare for future hacks.
• 74% of IT security workers say their companies are dealing with major problems caused by AI-powered cyber threats.
• 75% of cybersecurity experts had to adjust their security plans last year to handle incidents caused by AI (Deep Instinct).
• 97% are concerned that their companies will soon face security issues caused by AI.
• AI in Cybersecurity Statistics stated that 93% of businesses expect to be hit with AI-based attacks daily in the coming year.
• 87% of IT pros believe AI threats will continue affecting their organizations for years.
• Over the past year, the average global cost of a data breach reached $4.88 million, a 10% increase and the highest ever recorded.
• The most common types of attacks reported by IT professionals are:

1. 1. Social engineering and phishing – 56%
   2. Online/web-based threats – 50%
   3. Stolen usernames and passwords (credential theft) – 49%

AI-Powered Cybersecurity Prevention Tools Statistics

• Just 15% of key decision-makers think traditional (non-AI) cybersecurity tools are good enough to detect and stop AI-created threats.
• AI in Cybersecurity Statistics stated that almost 44% of companies say that they understand how AI could help them improve their cybersecurity.
• Around 62% of the companies recognize the advantages of using machine learning to boost their security defences.
• Nearly 67% of cybersecurity experts use AI to build rules based on known threat patterns and warning signs.

(Reference: secureframe.com)

• 50% of the companies state that they are using AI tools to fill the gap caused by a shortage of skilled cybersecurity workers.
• Around 70% of the employees in the field say that AI does a great job spotting things that would normally go unnoticed.
• 73% of the cybersecurity teams want to move towards a more practical and AI-driven defence strategy.
• Around 53% of security departments say that their company is still in the early phase of using AI-driven cybersecurity tools.
• 65% of the security professionals stated that connecting AI tools with older systems is tough.
• Just 18% of the organizations have fully implemented and are actively using AI cybersecurity tools
• 63% of employees depend on AI to design rules that match familiar threat signs and behaviour patterns.
• 50% of companies are using AI to help overcome the shortage of cybersecurity experts.

AI as Cyber Threat Statistics

• Although AI helps protect against cyber threats, it can also be a dangerous tool when used by criminals.
• AI in Cybersecurity Statistics stated that 53% of IT workers are most worried about hackers using Chatgpt to create phishing emails that sound more real and believable.
• 71% of IT experts think nation-states might already use ChatGPT for cyberattacks, like hacking and phishing.

(Reference: darktrace.com)

• Right now, 40% of phishing emails sent to companies are written by AI.
• 93% of ethical hackers say that businesses may open new ways for cyber attackers to break in when they use AI tools.
• Only 53% of ethical hackers believe that today’s cybersecurity tools are strong enough to handle AI risks.
• AI in Cybersecurity Statistics stated that 82% of ethical hackers say the AI threat is growing too quickly for current defences.
• 72% of ethical hackers think the dangers of AI are greater than its benefits.

(Reference: darkreading.com)

• According to ethical hackers, the top 5 ways AI can be misused to weaken a company’s security or risk control systems include:

1. 1. Making fake data and identities that are hard to spot
   2. Getting systems to do harmful actions
   3. Building tools for big cyberattacks
   4. Feeding bad data into AI models to change how they work
   5. Taking advantage of mistakes and bias in security decisions

• In a recent study, 60% of people were fooled by phishing emails created by AI, which is about the same success rate as phishing emails made by skilled humans.
• New studies show that AI tools like large language models (LLMs) can fully automate the phishing process, cutting costs by more than 95% while being just as effective—or even better—than phishing messages written by humans.

Adoption and Regulation of AI in Cybersecurity

• Organizations are at different stages of adopting Generative AI, especially larger language models (LLMS).
• Almost 42% of the companies are already using LLMs in different parts of their business, showing a strong push to use AI for innovation and growth.
• AI in Cybersecurity Statistics stated that the other 45% are looking into possible ways to use and integrate LLMs that show high interest and awareness of GenAI’s potential.
• Just 9% have not started planning for LLM adoption, which shows that most businesses are moving towards using this technology and that those who don’t may fall behind.

(Source: lakera.ai)

• The European Union(EU) is leading the way in creating solid rules for AI.The new EU AI Act shows a serious focus on developing AI that is both safe and ethical.
• A Blackberry survey found that almost 95% of IT leaders think the government should set rules for advanced technologies like ChatGPT.
• ChatGPT use is booming; it has grown by almost 63%. Still, it is also the most blocked AI tool by companies.
• Despite AI’s rapid growth, 85% of organizations think that their data protection strategies are strong enough to keep up with its evolution.
• Almost 35% of businesses are using AI for various tasks. The study also found that younger employees tend to pick up and use AI tools in their jobs more easily and quickly than the older generations.

(Source: lakera.ai)

• AI is expected to change security significantly in 2024. Almost 55% of companies are planning to roll out GenAI solutions.
• The number of laws and regulations related to AI has grown significantly
• AI in Cybersecurity Statistics stated that 55% of companies used AI, including GenAI, in at least one part of the business.
• A CompTIA survey shows that 36% of companies are not using AI or machine learning for cybersecurity yet but are considering GenAI tools now.
• Immuta stated that 37% of data leaders say their companies have a strong plan to keep up with new AI rules and security needs.

(Source: website-files.com)

• AI in Cybersecurity Statistics stated that 71% of the companies have already started working to reduce ties to using AI.
• 65% of people stated that their companies now use GenAI regularly, almost double the number than before.

New innovations in Ai Cybersecurity

#1. AI That Helps Fix Security Problems Faster

#1. New AI tools make it easier and quicker for security teams to respond to threats.

#2. Some AI systems can look at security alerts and give users step-by-step instructions based on the situation.

(Source: mdpi.com)

#3. This helps them fix issues faster and in a way that fits their environment.

#4. For example, Secureframe Comply AI can automatically give clear solutions when cloud tests fail. It uses infrastructure as code (IaC) to suggest personalized fixes, helping teams solve problems quickly, pass audits, and improve security.

#2. Using Generative AI to Understand Threats Better

#1. Generative AI is helping security experts analyze threats faster.

#2. Instead of spending time writing complex search commands or studying large amounts of data, AI tools can scan code and traffic automatically and give helpful insights.

(Source: aiprm.com)

#3. Google’s Cloud Security AI Workbench, powered by an AI model called Sec-PaLM, helps security analysts find and understand threats.

#4. One tool, VirusTotal Code Insight, even provides plain-language summaries of code to help users more easily identify harmful scripts.

#3. AI That Answers Security Questionnaires

#1. Companies often use questionnaires to check if vendors meet cybersecurity standards, but filling them out takes time.

#2. AI can help by suggesting answers based on past responses and security policies.

#3. Secureframe’s AI tool uses past data, test results, and policies to answer questions faster and more accurately.

#4. It can also reword responses to better fit the questions, saving organizations time and effort.

#4. AI That Improves Password Safety

#1. A study by Home Security Heroes showed that AI can crack 51% of common passwords in under 1 minute.

#2. While this can be dangerous if used by hackers, it also means AI can help people create stronger passwords and check how secure their passwords are.

#3. AI models trained on large sets of stolen passwords — like PassGPT — can suggest harder-to-guess passwords and make password-checking tools more accurate.

#5. Deceiving Hackers with AI Defences

#1. While cybercriminals use AI for scams like deepfakes, security teams also use AI to trick attackers.

(Reference: secureops.com)

#2. AI can now create fake system flaws and decoys that confuse hackers.

#3. Acalvio’s ShadowPlex uses AI to set up realistic traps across company networks, helping stop advanced attacks by leading hackers away from real systems.

#6. AI That Speeds Up Vendor Reviews

#1. Checking vendors for security risks is important but can take time. AI can quickly read and process large amounts of data, making the process much faster.

#2. With Comply AI for VRM, users can send security questionnaires and get replies directly on the platform.

#3. The AI can even pull answers from vendor files like SOC 2 reports, reducing vendors’ work and making reviews quicker and more accurate.

#7. AI That Helps Developers Build Secure Software

#1. In 2023, the U.S. cybersecurity agency CISA released guidelines to help developers create safer software.

#2. While these rules may increase development costs, many teams use AI to reduce time and effort.

#3. For example, developers using GitHub Copilot completed coding tasks 55% faster than those who didn’t. This AI tool helps write code and improve software security while saving time.

#8. AI for Smarter Patch Management

#1. Fixing software vulnerabilities by hand takes time, and hackers exploit that.

#2. A report showed that unpatched flaws caused 47% of data breaches, and 56% of companies still patch manually.

#3. AI-driven patch systems can detect, rank, and fix security holes faster and with less manual work.

#4. GitLab now uses AI to explain software flaws to developers, and it plans to let the AI fix them automatically in the future.

#9. AI-Powered Penetration Testing

#1. Pen testing — where experts try to break into their own systems to find weaknesses — can be slow and complex.

#2. AI can speed up the process by quickly scanning systems, finding flaws, and suggesting ways to test them.

#3. Tools like DeepExploit (open source) and NodeZero (commercial) use machine learning to automate key parts of the process.

#4. DeepExploit is still in beta but already helps with data collection, vulnerability scans, and simulated attacks.

#10. AI for Automated Risk Reviews

#1. AI can now make risk assessments faster and more accurately. It can review company data, analyze risks, and create detailed reports without human help.

#2. Secureframe Comply AI for Risk can give insights based on a risk description and company info.

#3. It shows how likely a risk is, how big its impact could be, and what to do about it — helping teams better understand and reduce risks.

Conclusion

In summary, using AI in cybersecurity has made it much easier to spot and quickly respond to online threats. Recent numbers show that more companies are using AI tools and seeing fewer losses from cyberattacks and faster reaction times. As cybercrime grows more advanced and common, AI will play a bigger role in keeping systems safe.

Still, depending on AI brings problems, like unfair decision-making or hackers trying to trick the system. That’s why it’s important to keep improving these tools and ensure they’re used responsibly. We have shed enough light on AI in Cybersecurity Statistics through this article.