By Ashley Leonard, CEO and Founder, Syxsense

Endpoints are one of the easiest and most frequently abused access vectors for threat actors. In fact, according to IDC, 70 percent of successful cybersecurity breaches originate on endpoint devices. As the threat landscape becomes more complicated, many organizations are beginning to think about the impact of AI on cybersecurity - both from an offensive and defensive standpoint. However, despite numerous reports of threat actors abusing AI to reinforce and scale phishing attacks, spread ransomware, and rapidly exploit vulnerabilities, most organizations are unaware of how to maximize the benefits of AI for endpoint security. 

To bridge this gap, here are the most impactful applications of AI to help enhance your endpoint security and a look at how the landscape might evolve over the next 12 to 24 months.

THE RISE OF AI COPILOTS

AI copilots leverage the power of large language models (LLMs) to create a user-friendly interface that optimizes functionality and the user experience. Simply pose a request to the copilot in natural language, and it will produce information to help complete tasks in kind. AI copilots have quickly become popular across industries. Companies like Microsoft have integrated them across their entire business, introducing copilots for its Microsoft 365, Microsoft Security, Viva, Dynamics, and GitHub product lines.

Since copilots make it easier to understand, analyze, and process vast amounts of data, they are well-suited to simplifying and accelerating the automation of endpoint management and security workflows. This includes processes like patching, vulnerability scanning, remediation, and more. As threat actors increase the speed and accuracy of their attacks, IT and security teams can now counter by automating defensive workflows using simple commands. This powerful innovation will help level the playing field as it becomes more widely available.

AI APPLICATIONS FOR PROTECTING ENDPOINTS

Traditional endpoint security solutions have primarily relied on signature-based detection (identifying known threats and blocking them), but this approach is not as effective as it used to be. Adding AI-powered endpoint security solutions to your stack will make it easier to identify anomalous behavior and detect previously unknown threats. Machine learning algorithms allow users to easily identify threats that would otherwise remain unnoticed. Let's look at the top AI-enabled use cases for your endpoint security.

• Automated Threat Detection & Response: As mentioned earlier, copilots have introduced the power of automation to many industries. For endpoint management, those capabilities are well suited to automating critical security functions like patch management, anomaly detection, and secure authentication mechanisms. Imagine being able to analyze the characteristics of an attack and remediate them in record time. Typically, it can take security teams from days to months to identify a vulnerability, and when it's discovered, time-intensive, complex, and poorly configured environments prevent many teams from taking action. But with AI, you can quickly and effectively analyze breach characteristics and datasets to distinguish normal activity from anomalies. This reduces the time to action and remediation. In short, AI might lead to a world with fewer successful cybersecurity infiltrations.
• Remediation with Predictive Analytics: In addition to automating threat detection and response, AI also lends itself to predictive analytics. Organizations can use the technology to analyze and forecast the threat landscape based on historical data and other diverse datasets to establish patterns. Overall, organizations will benefit from having better visibility and insights into security postures, allowing them to proactively mitigate risks.
• Knowledge Consolidation: Your ability to protect your endpoint is only as good as the information you can collect and analyze. Often, threat actors access businesses through endpoints due to oversights like fragmentation and blind spots. As unified security and endpoint management (USEM) practices become more common and more information is pulled in from a connective web of endpoints, it's crucial to have a central engine that can synthesize information and share the most helpful insights. Organizations can use AI to consolidate this data and take extra steps to transform unstructured material into structured data that can then be analyzed and included as part of the bigger-picture analysis. Additionally, organizations can collect more information from endpoint users without infringing on their privacy. This means IT and security teams can analyze every action (or inaction). With no stone left unturned, cybercriminals might compromise fewer endpoints.

THE FUTURE OF AI FOR ENDPOINT SECURITY

The era of AI is upon us. As we look to the next 12 to 24 months, we can expect AI integration across almost every aspect of the digital world. When it comes to endpoint security, those organizations that don't leverage AI will be significantly disadvantaged and left open to an onslaught of potentially crippling cyberattacks. Copilots and AI-managed endpoints will also become widely available and included in every vendor or MSP/MSSP offering. Organizations that embrace AI will greatly reduce blind spots and flatten steep onboarding curves.

While businesses will increase their productivity and efficiency, and workforces will become more specialized as AI literacy takes hold, we should also expect an evolution in cybercrime. Attackers are always looking for the latest edge. AI, like deepfakes, increases the surface area for organizations and individuals to manage. One potential consequence is an increase in identity-based attacks.

With all of the AI hype, it's easy to get overwhelmed and sidetracked by seemingly endless possibilities. Hopefully, these recommendations can bring some focus to your AI-enabled endpoint security strategy. As we brace for the future, now is the time to opt into AI to keep your endpoints defensible.

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ABOUT THE AUTHOR

Ashley Leonard is a technology entrepreneur with over 25 years of experience in enterprise software, sales, marketing, and operations, providing critical leadership during the high-growth stages of well-known technology organizations. Ashley manages U.S., European, and Australian operations in his current role, defines corporate strategies, oversees sales and marketing, and guides product development. Ashley has worked tirelessly to build a robust, innovation-driven culture within Syxsense while delivering returns to investors. Ashley serves on several boards and mentors up-and-coming technology CEOs through his membership in the Young Presidents Organizations (YPO). He served as Orange County chair for two years. Ashley also served as Area Chair for the YPO Pacific Region and was host city partnership chair for the 2020 YPO Global EDGE conference in San Diego, CA, welcoming over 3,000 of the world's top CEOs.