AI and Cybersecurity: Oil and Vinegar, or the Perfect Match?
In our digital-first and increasingly cloud-based world, AI and cybersecurity go hand in hand. AI tools enable IT and security teams to tackle the challenges of maintaining security posture at scale in organizations’ ever-evolving digital ecosystems. However, even as AI improves cybersecurity operations, threat actors are also using it to develop and carry out attacks.
In this article, we’ll discuss the potential for enhancing cybersecurity with AI tools and talk about some of the AI and cybersecurity risks posed by both threat actors, and the technology itself. We’ll also highlight how combining human skills with AI capabilities can help mitigate some of those risks for stronger cybersecurity.
How AI Can Improve Cybersecurity
As today’s businesses grow, they increase the number of devices, endpoints, and users in their network. They also use a host of different software solutions and apps that contain sensitive data and proprietary information. Even smaller organizations have a widening digital footprint that’s vulnerable to cyber threats. As the attack surface expands, IT and security teams are faced with the challenge of monitoring and managing it.
AI enables teams to maintain a high level of security and reduce manual tasks, even as the business expands. It can also improve the way teams detect and handle sophisticated attacks coming from threat actors that are also using cutting edge technology—including AI—to their advantage.
AI can support cybersecurity initiatives through:
Automation
Teams can use AI tools to support manual tasks like log analysis, vulnerability scanning, patch management, and network traffic monitoring and policy maintenance. It can also automate responses to known threats and play a role in coordinating human response efforts.Threat detection
Extended detection and response (XDR) and security information and event management (SIEM) tools can detect anomalies or issues at scale across an organization’s attack surface. AI solutions can also be used to detect phishing attempts by identifying anomalies within emails.Identity and access management
AI can identify voices, faces, fingerprints, and typing patterns to enhance authentication processes. This can reduce the risk of threat actors stealing digital credentials. Organizations can also use AI solutions to automatically identify and flag sensitive data so that teams have better visibility into who is accessing what.Adaptive security
AI-driven systems can learn and evolve as models ingest new data. This means that AI can quickly adapt to detect and respond to novel threats. As cybersecurity becomes more complex and threat actors more adept, AI can help organizations stay agile.Behavioural analytics
Teams can protect against insider threats by monitoring user behaviour with AI. This enables them to detect changes in user behaviour and assess network traffic for unusual activity that could indicate an issue in real time.Predictive security
AI can also be used to proactively identify potential risks, not just flag malicious activity when it happens. Teams can leverage AI to assess vulnerabilities within their own infrastructure, but they can also incorporate data from public repositories of cybersecurity vulnerabilities to create a more complete picture of the risks they might face.
Teams can use AI to detect and respond to cyber threats faster. It also empowers them to better understand the strengths and weaknesses of their security architecture so that they can make more strategic decisions about reducing vulnerabilities, rather than reacting to incidents. AI streamlines reporting and analytics, making it easier to monitor security posture and measure success.
AI is also highly flexible and can be tailored to individual organizations to provide solutions that address unique circumstances—like organizations that are growing quickly, those that have hybrid cloud infrastructure, and those with a remote workforce.
Emerging AI and Cybersecurity Risks
Unfortunately, the AI impact on cybersecurity benefits threat actors, too. AI lowers the barrier to entry for cybercriminals. The technology enables threat actors to automate vulnerability scanning and carry out increasingly sophisticated attacks at a larger scale. Threat actors are using genAI to learn how to build malware and improve their own skills in response to cybersecurity innovation. They’re leveraging AI to power phishing, impersonation, and evasion tactics—and adapt their attack strategy using AI capabilities.
Cybercriminals are also using genAI to create large-scale social engineering campaigns, such as email spam campaigns, deepfake videos, and decoy websites linked to malicious ads. As genAI becomes a part of more cloud-native platforms, threat actors are looking for ways to exploit these services. Risks include data theft, unauthorized access, model manipulation, and prompt injection geared towards extracting sensitive data.
Organizations need to be aware of the current limitations of AI-driven cybersecurity. AI cybersecurity solutions depend on a large volume of data which itself is vulnerable to threat actors. AI malware can potentially learn from an organization’s defence systems to find vulnerabilities. If there are issues with the quality or quantity of training data, AI solutions may return false positives and negatives or miss real threats. Training data may also impart biases to the model, leaving gaps in the system’s ability to accurately identify certain types of threats—especially novel threats.
Human Intelligence Drives AI Performance in Cybersecurity
The future of AI and cybersecurity still requires human expertise and skill. Human team members bring a variety of real-world experiences and innovative ideas to cybersecurity initiatives. They can develop new ways to mitigate risks and respond to threats, creating unique cybersecurity frameworks and strategies that threat actors have never encountered before, ultimately enhancing their security posture.
AI isn’t a silver bullet for protecting against increasingly complex cyber attacks. It can’t totally eliminate vulnerabilities. It’s critical that teams avoid overreliance on AI-driven cybersecurity solutions. Human interventions like good password hygiene, actively deploying patches, and monitoring the system for performance are still critical for maintaining strong security.
If teams are using AI tools like ChatGPT they must be trained to use them properly to avoid unintentional data leaks. If your organization uses an internal tool like Microsoft Copilot, you need to ensure that your data is structured for security to prevent unauthorized users from viewing information they shouldn’t have access to.
AI supports and augments human decision-making and streamlines cybersecurity tasks. In the real world, this could look like an IT team using AI-driven tools to monitor network activity and flag anomalies in real time. While AI handles data analysis, provides alerts, and proactively suggests potential response strategies, human team members execute responses based on their skillsets.
For example, security analysts investigate and triage AI-generated alerts and incident responders address threats that have been verified using the protocols and tactics that fit the situation and work best for the organization. Humans assess the efficacy of the decisions they made alongside the information provided by the AI solution to optimize their mitigation, detection, and response processes going forward.
Looking Ahead at the AI and Cybersecurity Landscape
Splunk’s recent 2025 Predictions report revealed that business leaders’ top priorities include recovering from cyber attacks faster and ensuring that AI initiatives deliver results. Companies that can leverage AI for vulnerability detection and rapid threat response will be better equipped to minimize expensive downtime and maintain the trust of their customers or users.
As our interconnected digital ecosystems expand, Splunk also notes that it’s more important than ever for every business to prioritize air-tight security. As Gretchen O’Hara, VP of worldwide channels and alliances at Splunk, says in the report, “If one piece topples—even at the very end—the whole chain can come crashing down.”
AI will evolve as teams improve security measures and threat actors develop strategies in response. GenAI will be able to create realistic threat simulations so that security teams can test their defense strategies. The accuracy and reliability of predictive security models will also improve, surfacing the threats that are most likely to impact an organization rather than just providing a list of all possible threats.
However, as organizations adopt more AI-driven security processes, they need to be mindful of the ethical issues around surveillance and privacy. Businesses need clear AI policies to ensure that the tools are used appropriately within the organization.
Optimize Your Security Posture with AI-Driven Cybersecurity Solutions
Is your organization ready to adopt AI solutions to enhance your IT team’s operations and improve your security posture? Our team can help you define your path forward with an AI readiness assessment. IX Solutions offers cyber security solutions including endpoint protection, data backup, and disaster recovery to ensure your organization stays ready and resilient in an evolving cybersecurity landscape.