AI security: the future of cybersecurity

| By:
Jason Short

If you hadn’t already noticed, artificial intelligence is making inroads across all business functions. According to Forbes, an impressive 64% of businesses believe that using it will help increase productivity, while almost half already use it to create internal communications. Clearly, most organizations are quickly taking steps to leverage the power and efficiency of this evolving technology.

AI has proven to be especially attractive for its potential to power higher levels of cybersecurity. The threats out there are certainly ramping up: one security report found that cyberattacks surged by 31% in 2021 compared to the year before, while another estimates that the number of distributed denial-of-service (DDoS) attacks will reach 15.4 million by this year—more than double just five years ago. 

AI can enhance cybersecurity strategies to defend against these growing threats—and you should definitely take advantage of it, if you aren’t already. By consuming billions of data artifacts, AI quickly learns about emerging risks and can quickly identify malicious files and suspicious activity much faster and more accurately than a human ever could. 

Another important facet of AI is predictive scenarios. AI has the ability to pull from large data sets from companies similar to your clients in terms of tech stack, industry, IT infrastructure, and size. These scenarios can provide likely probabilities and situations related to threat events, as well as expected breaches to happen. With this information, your team can know ahead of time the most likely threats to try and focus on and mitigate.

As cybersecurity attacks become more sophisticated, using AI security to repel and mitigate them is rapidly becoming a must to ensure your clients’ systems stay safe at all times.

Common AI applications in cybersecurity

AI has the potential to supercharge your ability to provide clients with strong cybersecurity strategies to address the spectrum of risks and threats. A few current and potential artificial intelligence security applications include:

  • Threat detection and prioritization.  Artificial intelligence in security applications learns by analyzing data for examples of malicious activities, such as malware or phishing attempts. It then applies its findings to predict such actions, identify them as they occur, and assign them a severity level for remediation.
  • Predictive scenarios. By analyzing big data sets for similar clients, AI can help you determine likely threats and scenarios that may impact your clients. This helps you allocate your resources in the ways most likely to be effective. 
  • Breach risk detection. AI security tools have the capacity to sift through large numbers of IT assets to assess them for potential vulnerabilities that hackers could leverage. It can then calculate not just the likelihood of a breach, but even the techniques the hackers are likely to use. In addition, AI can help your teams prioritize actual breach risks, as opposed to false positives.
  • Data privacy. AI can encrypt sensitive data so that it’s much harder for cybercriminals to decipher it. It can also monitor unauthorized users and identify attempts to break into systems and files.
  • Task automation. This technology can handle routine tasks such as informing users that their credentials may have been compromised, resetting passwords, and patching vulnerabilities in systems and software. This can ease the burden on you and your staff, giving you more time to focus on more demanding security tasks and strategies.
  • Incident response and remediation. One of the most valuable features of AI in security is its ability to respond to threats and mitigate them quickly. Speed is critical to defend against threats, lessen their impact, and repair any damage. AI can analyze reams of data for behaviors and other signs of anomalous or malicious activity within seconds or minutes. It can then immediately take steps to protect systems and applications, and alert you so you can evaluate and fix the problem. This can reduce the typical timeline of responding to and acting on threats by 14 weeks.

Real-life examples of AI in cybersecurity

Many organizations have been using AI for security issues for a few years now, highlighting its impact and benefits. After a major security incident a few years ago, commodities trading firm ED&F Man Holdings revamped its cybersecurity strategy to incorporate AI, adding a platform to detect threats. The AI tool detected and blocked multiple attacks and even discovered a crypto-mining scheme happening in the background. 

In 2017, the WannaCry ransomware, in particular, became a global threat, affecting some 230,000 devices in more than 150 countries at its peak. That spurred Microsoft to develop AI enhancements focused on ransomware threats for its endpoint detection solution. The platform analyzes files, processes, user accounts, and devices to calculate the risk of an attack. 

Recently Google Cloud announced it is partnering with other cybersecurity vendors to launch a new AI-powered threat intelligence platform. Security Workbench uses an AI called a Large Language Model (LLM) to provide customized and up-to-date details about an organization’s threat landscape and environment based on external and internal information, including vulnerabilities and malware.  

As security with artificial intelligence becomes more common, you can expect to see more organizations of all sizes taking advantage of it.

Benefits of AI in security

Cybersecurity strategies need to be constantly upgraded to keep pace with new developments. AI security offers plenty of advantages to help shore up your cybersecurity efforts and threats evolve.

  • Bridge the IT talent gap. The Bureau of Labor Statistics estimates that demand for information security analysts (a category that includes cybersecurity specialists) will grow by an astonishing 35% from 2021 to 2031—a level of demand that will be hard to meet. Security with AI can help fill gaps in the workforce with automation, freeing up workers to focus on other tasks. In addition, by supporting 24/7 monitoring, AI will allow MSPs to provide effective client coverage while lowering staffing costs.
  • Scalability. AI cybersecurity tools can analyze a huge volume of data and processes. This means they can keep up as organizations grow and their technology infrastructure becomes more complex.
  • Continuous learning. Artificial intelligence security systems are always learning from new data and patterns, which helps them quickly adapt to threats as they emerge. They can also learn the difference between behaviors that indicate a threat and those that are innocuous, helping to reduce the number of false positives.
  • Greater resilience. Overall, the enhanced speed, scalability, and capabilities of artificial intelligence in security platforms help MSPs defend clients more effectively and recover faster from threats and attacks. This limits the time needed to focus on threats and recovery, supporting normal operations and levels of productivity.

Considerations for AI in security

However, in some ways, AI security is a double-edged sword. Along with the opportunities come concerns about its use. Some considerations to keep in mind include:

  • Data privacy and compliance issues. Ensure that the use of AI doesn’t contradict or interfere with privacy policies and regulations regarding data collection, storage, and processing.
  • Ethics. AI in security is a powerful tool, and you should be mindful of its potential impact on your clients, their employees, their customers, and even society at large.  
  • Potential for malicious use. Just as AI can defend against emerging threats, it can also be exploited by cybercriminals to create new ones that are more difficult to detect and repel.
  • Resource requirements. AI security solutions generally require significant computational power and capacity. Make sure your clients have sufficient infrastructure to support optimal performance with minimal impact on their normal operations.
  • Need for regular updates and maintenance. Just like other software, AI solutions must be regularly updated so they can recognize new threats. 
  • Oversight requirements. As smart as AI is, human experts are still needed to provide context for individual and collective threats and drive short- and long-term planning and decisions. It is an important element of an overall strategy guided by cybersecurity professionals.

Is AI security absolutely essential?

Traditional cybersecurity tools and techniques still offer a lot of protection. But as artificial intelligence in security continues to advance, so will the threats, and so will the demands on you. Ignoring AI means that your clients will be left more vulnerable to attacks in the months and years to come, and that you and your team will struggle to keep up with their speed and scale. 

At the same time, you don’t want to dump your current cybersecurity framework and completely replace it with AI. A multi-layered approach offers the most benefits and protection. One staple you should consider along with AI is security information and event management (SIEM). This software helps your team identify potential security issues and vulnerabilities, which works well with AI support. You should carefully evaluate how AI is most appropriately integrated into your clients’ cybersecurity tech stack by considering:

  • Each client’s risk profile
  • Their level of technological complexity
  • Computational capacity
  • Their size and the nature of their industry and operations 

Smaller organizations may need AI for security only to automate basic monitoring and management. Larger organizations that handle sensitive data, such as healthcare companies and financial institutions, will need more robust solutions. 

No matter what kind of organization it is, staying on top of current threats is critical to defending your client systems more effectively. The ConnectWise Cyber Research Unit (CRU) compiled a report on cyberattack trends, top ransomware tactics, and more to help provide MSPs with an eye-opening look at the ever changing threat landscape. Download the 2023 MSP Threat Report to stay informed and help get ahead of threats.

AI and cybersecurity solutions

AI can do a lot, especially in concert with traditional cybersecurity solutions and security policies, such as group policy management. But AI in security is only as good as the information it uses to learn. That means you may need supplemental solutions in certain areas to ensure it is working with high-quality and current data. 

For example, behavioral analysis features can help AIs learn to differentiate normal user and system behavior from anomalous or malicious actions. This can reduce the incidence of false positives, so you can focus on actual threats.

Threat intelligence platforms gather and analyze data in real time from multiple sources to identify and predict threats. Incorporating their findings or connecting them to AI cybersecurity tools can help the solution proactively take a defensive posture.

When you’re considering artificial intelligence security products and vendors, it’s helpful to be aware of those needs. Other things to consider include:

  • Capabilities: Ask about the algorithms the AI uses and how the vendor trains the models to keep up with threats. Make sure the vendor is continually updating it with current intelligence.
  • Accuracy: Explore the solution’s rate of false positives and negatives, successful detections, and other performance issues. 
  • Transparency: AI cybersecurity shouldn’t be a “black box.” Make sure you are able to understand the reasoning behind its actions.  
  • Compliance: It’s critical that your chosen solution meets strong standards for data privacy and security, especially for highly regulated industries. 
  • Customer training and support: As with any solution, robust educational and support resources will help users make the most of it and assist with troubleshooting.
  • Vendor reputation and stability: The vendor should have an established track record and be able to show proof of the effectiveness of its concept, such as with case studies and testimonials. Make sure the company has sufficient resources to put toward optimizing and enhancing the AI over time.

Building a comprehensive cybersecurity strategy with AI requires a multifaceted approach that incorporates several tools. Antivirus software, identity management solutions and security information & event management (SIEM) technology are critical to effectively build a proactive posture. 

ConnectWise offers a comprehensive suite of cybersecurity software solutions to help MSPs keep their clients’ critical assets safe from attacks, hacking, and breaches. For example, ConnectWise SOC combines 24/7 support from a security operations center along with AI to help your clients at all times. Visit our Cybersecurity Center for more information on the programs, solutions, and services that can help you build a successful security practice.


AI can be applied to enhance cybersecurity strategies with advanced threat detection, the ability to assess the likelihood of breaches and attacks, automated monitoring and incident response, and other features.  

With the ability to analyze billions of data assets, identify patterns quickly, and continually learn about behaviors and risks, AI provides enhanced defenses against cyberattacks as well as swift detection, response, and remediation of intrusions.

The National Security Commission on Artificial Intelligence (NSCAI) was established by Congress in 2019. As an independent commission, it is responsible for evaluating the impact and implications of AI on national security. Commission members study research and development, potential applications for defense and security purposes, the need for education and training, concerns about ethics and accountability, and other issues relevant to the development of AI in this context.

AI is making security overall more efficient and scalable with the ability to collect and analyze billions of pieces of data within seconds, as well as analyze behaviors and patterns to assess and predict risks. By helping cybersecurity professionals both proactively and reactively strengthen defenses, it enables organizations to be more agile in responding to a growing number and range of cyberthreats.

However, AI also presents ethical dilemmas over privacy issues. For instance, there are concerns about the misuse of sensitive information in large datasets being used by AIs for training and analysis. Other objections have been raised about features like biometrics for user authentication, such as facial recognition or retinal scans. .AI may also be used to generate attacks that could be hard to defend against.

AI is revolutionizing security practices, but human oversight is critical to ensuring it is deployed in a safe, responsible, and ethical manner.