Artificial intelligence (AI) is one of the most powerful tools security teams can use to strengthen their defenses. But it’s also supercharging the risks. According to a 2025 cybersecurity survey by Gartner, 62% of organizations experienced deepfake social engineering attacks between 2024 and 2025.
Cybercriminals are weaponizing AI to launch advanced, at-scale attacks. Unfortunately, traditional systems and monitoring approaches can no longer keep up. To protect your organization, you need a security posture designed for AI-driven threats.
This guide looks at how AI is making life easier for cybercriminals, why traditional cybersecurity measures no longer cut it and how businesses are adapting to the new reality.
Key Takeaways
- AI boosts cybercriminal capabilities by enabling sophisticated attacks like deepfakes and automated phishing campaigns.
- Traditional cybersecurity measures struggle to counter AI-powered threats due to their adaptability and speed.
- Organizations need to adopt strategies like zero-trust models and employee training to combat AI-driven risks effectively.
- Using AI tools against AI threats can enhance monitoring and response times for security teams.
- A proactive defense posture is essential; continuously monitor systems and train employees to identify AI-based attacks.
Table of Contents
How Threat Actors Are Using AI
Cybercriminals are using AI to launch faster, more sophisticated attacks against organizations. The attacks are harder to detect and more convincing than traditional attacks, so they often go unnoticed until it’s too late. Here are some common ways cybercriminals employ generative AI.
Deepfakes
Criminals create AI-generated replicas of individuals to make their scams more believable. These deepfakes can closely mimic a target’s appearance and voice, making them highly convincing. For example, criminals can create AI-generated impersonations of key business decision-makers to trick employees into sharing confidential information or transferring money.
Such was the case for Arup, a global design and engineering firm. In 2024, Arup lost over $25 million after a finance worker was tricked into believing he was on a video call with the company’s chief financial officer (CFO). Following the video call with the AI-generated impersonator, the employee was so convinced that he transferred $25.6 million to scammers.
These face- and voice-cloning scams are not isolated incidents. A multinational firm in Singapore fell victim to a $499,000 deepfake phishing scam in 2025. The company’s finance director authorized the money transfer after a WhatsApp interaction and a Zoom call with a scammer who used AI to impersonate the CFO.
Social Engineering Attacks
Threat actors are using AI to make phishing attacks more sophisticated and scalable. They can generate highly personalized phishing campaigns at scale in minutes with little indication that the messages are fraudulent.
The criminals use AI models to analyze organizations’ communication patterns, writing styles, tones and vocabulary. They then craft tailored phishing emails and send them to their targets.
Some go a step further by automating real-time communication with AI-powered chatbots. The chatbots adapt to organizations’ language and respond dynamically in conversations, making it harder for targets to tell them apart from legitimate interactions.
Credential Stuffing
Cybercriminals can use machine learning to analyze employees’ password patterns. They then automate username-password combination testing at scale with AI tools.
AI can identify patterns that humans might miss, so the risk of data breaches at target companies is quite high. It can also run tests much faster than criminals can on their own.
AI-Generated Malware
Some cybercriminals no longer rely on static malware. Instead, they use AI to generate software that frequently changes its malicious code. This malware can be difficult to detect because each variation appears new to traditional security systems.
AI-powered malware can even adapt to its environment in real time, modifying its behavior to bypass your detection system and exploit potential weaknesses.
Why Traditional Security Approaches Fail
While security measures such as passwords, antivirus software and firewalls work against traditional cyber threats, they might not be enough to protect against AI-powered attacks. There are several reasons why threats are growing and why data privacy is breaking in the age of AI.
Legacy Tools Rely on Known Patterns
Traditional solutions, such as antivirus tools, identify threats by comparing suspicious activity to known signatures. The problem is that AI-powered malware is polymorphic. It can vary its code with each deployment, making it almost impossible for security systems to detect threats early.
AI Can Figure Out Static Rules
Traditional security solutions operate on preset rules. AI tools can analyze these rules, identify weaknesses and make real-time adjustments to maneuver around them. For example, if you have a rule-based defense “If an activity originates from this IP address, block it,” the AI-powered attacker can route traffic through proxies instead.
Traditional Models Are Primarily Human-Driven
Some legacy systems still rely on human-led reviews and incident responses. Done manually, these processes can take hours or days.
AI-powered attacks, on the other hand, occur more quickly than humans can keep up. For example, an AI-driven phishing campaign can send thousands of personalized emails to employees within minutes. Even when such an occurrence raises flags, security teams might not confirm the threat and implement security measures for hours—during which attackers might have access to your system.
This isn’t to say that you should remove human intervention from the equation. A good strategy relies on both AI and human oversight to assess and respond to threats.
Standard Systems Focus on Technical Anomalies
Traditional security tools are built to identify technical risks such as malware. However, modern cybercriminals don’t always rely on malware. In fact, according to CrowdStrike’s 2025 Global Threat Report, 79% of detected threats in 2024 were malware-free.
Cybercriminals are increasingly focusing on “non-technical threats” such as deepfake phishing, password cracking and social engineering. These threats are harder to detect.
How Organizations Are Adapting to AI-Powered Threats
Leading organizations are adjusting their cybersecurity approaches to better protect themselves from the new generation of AI-powered attacks—and you should too. Consider these strategies:
- Use AI against AI: Traditional tools can only do so much against AI-powered attacks. To boost your security, use AI tools to monitor system activity, analyze behavior patterns and flag suspicious activity. For example, you can use facial and voice recognition algorithms to detect synthetic media.
- Adopt a zero-trust security model: Verify every access request to your system, grant users only as much access as they need, implement multi-factor authentication (MFA) and continuously monitor your network for threats. This reduces the risk of threats spreading across your entire system if one point falls victim to AI-powered password hacking.
- Train employees on AI-generated threats: Offer regular security training that covers emerging threats, such as voice cloning and AI-generated impersonation. Also, run AI-powered cyberattack simulations to test employees’ awareness of potential threats.
- Regularly patch and update software: Cybercriminals can use AI to identify and exploit security vulnerabilities. Regularly conduct AI-powered penetration testing and close all identified security gaps before external threat actors exploit them.
- Automate incident response: AI-driven attacks work at machine speed. So should your response. Automate processes such as threat detection, alert triage and threat containment.
Implementing automation doesn’t mean getting rid of human input. Use AI to speed up responses, but lean on human judgment for decision-making. For example, you could configure your system to terminate sessions that exhibit unusual behavior (such as logging in from multiple locations), but leave it to your security team to determine whether to lock the affected user out of your system.
Keep Pace With AI Threats
With AI technology comes greater possibilities for enhancing your processes, but also more security risks. Modern cybercriminals use AI tools to impersonate individuals, craft personalized phishing emails, run at-scale username-password tests and bypass traditional security tools.
To protect your organization, develop a proactive defense posture. Continually monitor your systems and network for anomalies that might indicate security threats, train employees to be on the lookout for AI-powered attacks and always verify users’ or devices’ identities before granting access to your systems. Use AI as well to detect risks, automate alerts, investigate suspicious incidents and contain potential threats.
Now that you know how AI is making life easier for cybercriminals, you can develop and implement well-informed strategies to safeguard your organization against cutting-edge threats. Download Onspring’s ebook The 2026 GRC Report to understand today’s threat landscape and how to strengthen your organization’s defenses.
