As cyber threats keep evolving, it's becoming harder for organizations to keep up. Threat actors are using AI to create smarter malware, automate attacks and target people with more precision. At the same time, companies must manage complex data across different platforms and comply with new regulations. Traditional security methods are no longer enough to stay ahead of these evolving threats.
This is where AI can help. Cybersecurity tools that use AI can strengthen an organization’s defenses. AI can identify and prevent attacks by analyzing large amounts of data for unusual patterns. It can even predict and stop attacks before they happen. Let’s take a closer look at how AI is reshaping cybersecurity.
The role of AI in cybersecurity
As cyber threats grow in sophistication and scale, AI has emerged as an ally. It uses technologies like machine learning (ML), predictive analytics and natural language processing to help systems detect and respond to threats faster.
- Machine learning. Traditionally, algorithms provide step-by-step instructions for dealing with threats. But with ML, you don’t explicitly program a system to do specific tasks. Rather, you feed it examples and provide programming so that it can learn from those examples. This enables it to figure out behaviors that all the examples have in common. It can then use these generalizations to make predictions and take actions in the future when it sees something new, but similar, to what it has seen before.
- Predictive analytics. AI tools can analyze large datasets and connect the dots between seemingly unrelated phenomena. As a result, they can uncover behavior patterns and flag suspicious activities that might otherwise be missed.
- Natural language processing (NLP). This technology enables machines to interpret and generate human language in both written and spoken forms. By understanding and processing human language data such as emails, social media posts and code comments, NLP can identify potential threats like phishing threats, malicious code and social engineering attacks. It can also assist in log parsing, incident response automation and analyzing threat intelligence feeds.
Enhancing your team’s capabilities
AI in cybersecurity makes teams more efficient and enables faster and more effective responses. Here are a few ways that AI improves team capabilities:
- Automate repetitive tasks. AI takes care of repetitive tasks like monitoring traffic, scanning for malware and checking logs. AI in cybersecurity can take over many tedious, but essential, security tasks. This frees up the security team to work on more pressing challenges.
- Prioritize risk. Teams are often inundated with security alerts, which can lead to threats being overlooked. AI can sift through the barrage of notifications and single out the ones that need immediate human review.
- Scaling team capacity. Teams must deal with increasingly large volumes of data. AI cybersecurity tools can automate many tasks. This helps teams do more without hiring additional staff.
- Improve response times. Speed is critical in cybersecurity as delays give criminals time to escalate. AI detects threats in real-time and instantly alerts security teams, helping them act fast to minimize damage.
Case studies: AI-in action
AI is transforming how businesses defend against cybersecurity threats. Here are some key examples of its impact:
1) AI-driven protection stops a phishing attack
Recently, bad actors exploited a supplier’s email through vendor email compromise. This occurs when an attacker gains access to and weaponizes an email account of a smaller business partner instead of going directly after a bigger, more secure organization.
During the attack, bad actors gained access to the account of a professor at a public university. They then used this access to send a phishing link to a government employee whom the professor had previously emailed. Because the employee was a known contact in the professor’s inbox, the attacker was able to bypass many layers of security.
Proofpoint identified this email during an evaluation using Proofpoint Nexus, our end-to-end AI-driven detection stack. Because we identified it early, we were able to notify the security team at the receiving government organization. They were able to remove and remediate the threat.
2) Behavioral AI prevents data theft at a global law firm
Sending sensitive data to unauthorized accounts, such as personal accounts, pose a major security risk. Frequently, this happens when an employee is leaving a company. During this transition period, there’s often a sudden spike in data transfers, making it a critical time for monitoring.
At a large law firm, Proofpoint Adaptive Email DLP flagged an employee doing just that—attempting to email confidential data to outside accounts. By analyzing and learning normal email sending behaviors, trusted relationships and how users handle sensitive data, Adaptive Email DLP can detect when anomalous email behavior is occurring.
We worked closely with the customer to review key incidents of potential data loss. As part of this process, we provided:
- A list of all unauthorized accounts where the data was being sent
- All emails sent to those accounts, including details such as:
- Sender
- Recipient
- Subject
- Attachments
This case reinforces the importance of closely monitoring data access and movement during employee transitions. By using AI-driven solutions like Adaptive Email DLP—which is powered by Proofpoint Nexus AI—to identify users’ normal email sending behaviors and relationships, companies can detect unusual activity in real-time and proactively protect sensitive data.
Challenges and ethical considerations in adopting AI
While AI improves cybersecurity in many ways, it also comes with unique challenges and ethical concerns.
- Adversarial attacks. Adversarial attacks happen when threat actors manipulate AI systems to change their outputs or steal sensitive information. By changing inputs, they can trick AI into making mistakes or interpreting data. For instance, altering an image to trick a facial recognition system into misidentifying a person, allowing them to have unauthorized access. Similarly, a speech recognition system could be manipulated to misinterpret a command. To defend against them, AI systems need regular testing and better detection methods.
- AI bias. AI systems learn from data. Unfortunately, if data is incomplete or biased, then threats may be misidentified or missed. To combat this, it’s important to continuously review and assess data to ensure any biases are identified and corrected.
- Privacy issues. AI systems must prioritize security and privacy, particularly when handling sensitive data. Finding the right balance between using AI for threat detection and protecting user privacy is a complex challenge. While strong security measures protect against threats, they should not compromise individual privacy. Achieving this balance is key to maintaining user trust and ensuring compliance with regulations.
- Transparency. AI decisions must be transparent and explainable. Systems that function as "black boxes"—where even experts can't understand how conclusions are drawn—undermine trust in AI. Transparency ensures accountability, helps identify bias and allows users to make informed decisions based on AI-generated insights.
- Alert fatigue: AI systems may also generate false positives, leading to alert fatigue. This can overwhelm security teams, causing them to overlook real threats.
Building stronger defenses with AI
It’s clear that AI is making cybersecurity faster and more effective. It can quickly analyze data, spot threats and respond in real-time. AI also helps automate routine tasks, allowing security teams to focus on more pressing issues. This helps businesses stay one step ahead of cybercriminals.
Adopting AI is not just about reacting to threats—it’s about building a stronger, more proactive security system. Now is the time to embrace AI and take control of your cybersecurity strategy for the future.
How Proofpoint can help
Proofpoint Nexus AI is a comprehensive threat intelligence platform powered by AI, ML and real-time threat intelligence. With Proofpoint Nexus, security teams can rely on adaptive, threat-focused solutions that stay ahead of evolving cybercriminal tactics.
Whether it’s protecting users from phishing, detecting insider threats or preventing mistakes, Nexus AI provides the critical protection needed to secure an organization's most vulnerable entry points—its people.
Contact Proofpoint to learn how Nexus AI can transform your defenses and safeguard your organization today.
Learn more about how Proofpoint uses AI. To get deeper insights into AI in cybersecurity, download our e-book: Cybersecurity’s AI Tidal Wave.
