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December 20, 2022

How to Select the Right Cybersecurity AI

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20
Dec 2022
Choosing the right cybersecurity AI is crucial. Darktrace's guide provides insights and tips to help you make an informed decision.

AI has long been a buzzword – we started seeing it utilized in consumer space; in social media, e-commerce, and even in our music preference! In the past few years it has started to make its way through the enterprise space, especially in cyber security.

Increasingly, we see threat actors utilizing AI in their attack techniques. This is inevitable with the advancements in AI technology, the lower barrier to entry to the cyber security industry, and the continued profitability of being a threat actor. Surveying security decision makers across different industries like financial services and manufacturing, 77% of the respondents expect weaponized AI to lead to an increase in the scale and speed of attacks. 

Defenders are also ramping up their use of AI in cyber security – with more than 80% of the respondents agreeing that organizations require advanced defenses to combat offensive AI – resulted in a ‘cyber arms race’ with adversaries and security teams in constant pursuit of the latest technological advancements.  

The rules and signature approach is no longer sufficient in this evolving threat landscape. Because of this collective need, we will continue to see the push of AI innovations in this space as well. By 2025, cyber security technologies will account for 25% of the AI software market.

Despite the intrigue surrounding AI, many people have a limited understanding of how it truly works. The mystery of AI technology is what piques the interest of many cyber security practitioners. As an industry we also know that AI is necessary for advancement, but there is so much noise around AI and machine learning that some teams struggle to understand it. The paradox of choice leaves security teams more frustrated and confused by all the options presented to them.

Identifying True AI

You first need to define what you want the AI technology to solve. This might seem trivial, but many security teams often forget to come back to the fundamentals: what problem are you addressing? What are you trying to improve? 

Not every process needs AI; some processes will simply need automation – these are the more straightforward parts of your business. More complex and bigger systems require AI. The crux is identifying these parts of your business, applying AI and being clear of what you are going to achieve with these AI technologies. 

For example, when it comes to factory floor operations or tracking leave days of employees, businesses employ automation technologies, but when it comes to business decisions like PR strategies or new business exploration, AI is used to predict trends and help business owners make these decisions. 

Similarly, in cyber security, when dealing with known threats such as known malicious malware and hosting sites, automation is great at keeping track of them; workflows and playbooks are also best assessed with automation tools. However, when it comes to unknown unknowns like zero-day attacks, insider threats, IoT threats and supply chain attacks, AI is needed to detect and respond these threats as they emerge.

Automation is often communicated as AI, and it becomes difficult for security teams to differentiate. Automation helps you to quickly make a decision you already know you will make, whereas true AI helps you make a better decision.

Key ways to differentiate true AI from automation:

  • The Data Set: In automation, what you are looking for is very well-scoped. You already know what you are looking for – you are just accelerating the process with rules and signatures. True AI is dynamic. You no longer need to define activities that deserve your attention, the AI highlights and prioritizes this for you.
  • Bias: When you define what you are looking for, as humans inherently we impose our biases on these decisions. We are also limited by our knowledge at that point in time – this leaves out the crucial unknown unknowns.
  • Real-time: Every organization is always changing and it is important that AI takes all that data into consideration. True AI that is real time and also changes with your organization’s growth is hard to find. 

Our AI Research Centre has produced numerous papers on the applications of true AI in cyber security. The Centre comprises of more than 150 members and has more than 100 patents and patents pending. Some of the featured white papers include research on Attack Path Modeling and using AI as a preventative approach in your organization. 

Integrating AI Outputs with People, Process, and Technology


Integrating AI with People

We are living in the time of trust deficit, and that applies to AI as well. As humans we can be skeptical with AI, so how do we build trust for AI such that it works for us? This applies not only to the users of the technology, but the wider organization as well. Since this is the People pillar, the key factors to achieving trust in AI is through education, culture, and exposure. In a culture where people are open to learn and try new AI technologies, we will naturally build trust towards AI over time.

Integrating AI with Process

Then we should consider the integration of AI and its outputs into your workflow and playbooks. To make decisions around that, security managers need to be clear what their security priorities are, or which security gaps a particular technology is meant to fill. Regardless of whether you have an outsourced MSSP/SOC team, 50-strong in-house SOC team, or even just a 2-man team, it is about understanding your priorities and assigning the proper resources to them.

Integrating AI with Technology 

Finally, there is the integration of AI with your existing technology stack. Most security teams deploy different tools and services to help them achieve different goals – whether it is a tool like SIEM, a firewall, an endpoint, or services like pentesting, or vulnerability assessment exercises. One of the biggest challenges is putting all of this information together and pulling actionable insights out of them. Integration on multiple levels is always challenging with complex technologies because they technologies can rate or interpret threats differently.

Security teams often find themselves spending the most time making sense of the output of different tools and services. For example, taking the outcomes from a pentesting report and trying to enhance SOAR configurations, or looking at SOC alerts to advise firewall configurations, or taking vulnerability assessment reports to scope third-party Incident Response teams.

These tools can have a strong mastery of large volumes of data, but eventually ownership of the knowledge should still lie with the human teams – and the way to do that is with continuous feedback and integration. It is no longer efficient to use human teams to carry out this at scale and at speed. 

The Cyber AI Loop is Darktrace’s approach to cyber security. The four product families make up a key aspect of an organization’s cyber security posture. Darktrace PREVENT, DETECT, RESPOND and HEAL each feed back into a continuous, virtuous cycle, constantly strengthening each other’s abilities. 

This cycle augments humans at every stage of an incident lifecycle. For example, PREVENT may alert you to a vulnerability which holds a particularly high risk potential for your organization. It provides clear mitigation advice, and while you are on this, PREVENT will feed into DETECT and RESPOND, which are immediately poised to kick in should an attack occur in the interim. Conversely, once an attack has been contained by RESPOND, it will feed information back into PREVENT which will anticipate an attacker’s likely next move. Cyber AI Loop helps you harden security a holistic way so that month on month, year on year, the organization continuously improves its defensive posture. 

Explainable AI

Despite its complexity, AI needs to produce outputs that are clear and easy to understand in order to be useful. In the heat of the moment during a cyber incident, human teams need to quickly comprehend: What happened here? When did it happen? What devices are affected? What does it mean for my business? What should I deal with first?

To this end, Darktrace applies another level of AI on top of its initial findings that autonomously investigates in the background, reducing a mass of individual security events to just a few overall cyber incidents worthy of human review. It generates natural-language incident reports with all the relevant information for your team to make judgements in an instant. 

Figure 1: An example of how Darktrace filters individual model breaches into incidents and then critical incidents for the human to review 

Cyber AI Analyst does not only take into consideration network detection but also in your endpoints, your cloud space, IoT devices and OT devices. Cyber AI Analyst also looks at your attack surface and the risks associated to triage and show you the most prioritized alerts that if unexpected would cause maximum damage to your organization. These insights are not only delivered in real time but also unique to your environment.

This also helps address another topic that frequently comes up in conversations around AI: false positives. This is of course a valid concern: what is the point of harvesting the value of AI if it means that a small team now must look at thousands of alerts? But we have to remember that while AI allows us to make more connections over the vastness of logs, its goal is not to create more work for security teams, but to augment them instead.

To ensure that your business can continue to own these AI outputs and more importantly the knowledge, Explainable AI such as that used in Darktrace’s Cyber AI Analyst is needed to interpret the findings of AI, to ensure human teams know what happened, what action (if any) the AI took, and why. 

Conclusion

Every organization is different, and its security should reflect that. However, some fundamental common challenges of AI in cyber security are shared amongst all security teams, regardless of size, resources, industry vertical, and culture. Their cyber strategy and maturity levels are what sets them apart. Maturity is not defined by how many professional certifications or how many years of experience the team has. A mature team works together to solve problems. They understand that while AI is not the silver bullet, it is a powerful bullet that if used right, will autonomously harden the security of the complete digital ecosystem, while augmenting the humans tasked with defending it. 

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Author
Germaine Tan
VP, Security & AI Strategy, Field CISO

Germaine is VP, Security & AI Strategy, Field CISO at Darktrace. Based in Singapore, she works with CISOs, managers and security teams all over APAC on model optimization and operationalization of Darktrace in their digital environments. She also manages the team of 17 analysts in the APAC region that threat hunts and monitors networks from all over the world. Germaine holds a Bachelor of Science in Engineering and a Masters of Science in Technology Management from Nanyang Technological University. She is CISSP, CRISC and CEH certified.

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March 28, 2025

Darktrace Recognized as the Only Visionary in the 2025 Gartner® Magic Quadrant™ for CPS Protection Platforms

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We are thrilled to announce that Darktrace has been named the only Visionary in the inaugural Gartner® Magic Quadrant™ for Cyber-Physical Systems (CPS) Protection Platforms. We feel This recognition highlights Darktrace’s AI-driven approach to securing industrial environments, where conventional security solutions struggle to keep pace with increasing cyber threats.

A milestone for CPS security

It's our opinion that the first-ever Gartner Magic Quadrant for CPS Protection Platforms reflects a growing industry shift toward purpose-built security solutions for critical infrastructure. As organizations integrate IT, OT, and cloud-connected systems, the cyber risk landscape continues to expand. Gartner evaluated 17 vendors based on their Ability to Execute and Completeness of Vision, establishing a benchmark for security leaders looking to enhance cyber resilience in industrial environments.

We believe the Gartner recognition of Darktrace as the only Visionary reaffirms the platform’s ability to proactively defend against cyber risks through AI-driven anomaly detection, autonomous response, and risk-based security strategies. With increasingly sophisticated attacks targeting industrial control systems, organizations need a solution that continuously evolves to defend against both known and unknown threats.

AI-driven security for CPS environments

Securing CPS environments requires an approach that adapts to the dynamic nature of industrial operations. Traditional security tools rely on static signatures and predefined rules, leaving gaps in protection against novel and sophisticated threats. Darktrace / OT takes a different approach, leveraging Self-Learning AI to detect and neutralize threats in real time, even in air-gapped or highly regulated environments.

Darktrace / OT continuously analyzes network behaviors to establish a deep understanding of what is “normal” for each industrial environment. This enables it to autonomously identify deviations that signal potential cyber threats, providing early warning and proactive defense before attacks can disrupt operations. Unlike rule-based security models that require constant manual updates, Darktrace / OT improves with the environment, ensuring long-term resilience against emerging cyber risks.

Bridging the IT-OT security gap

A major challenge for organizations protecting CPS environments is the disconnect between IT and OT security. While IT security has traditionally focused on data

protection and compliance, OT security is driven by operational uptime and safety, leading to siloed security programs that leave critical gaps in visibility and response.

Darktrace / OT eliminates these silos by providing unified visibility across IT, OT, and IoT assets, ensuring that security teams have a complete picture of their attack surface. Its AI-driven approach enables cross-domain threat detection, recognizing risks that move laterally between IT and OT environments. By seamlessly integrating with existing security architectures, Darktrace / OT helps organizations close security gaps without disrupting industrial processes.

Proactive OT risk management and resilience

Beyond detection and response, Darktrace / OT strengthens organizations’ ability to manage cyber risk proactively. By mapping vulnerabilities to real-world attack paths, it prioritizes remediation actions based on actual exploitability and business impact, rather than relying on isolated CVE scores. This risk-based approach enables security teams to focus resources where they matter most, reducing overall exposure to cyber threats.

With autonomous threat response capabilities, Darktrace / OT not only identifies risks but also contains them in real time, preventing attackers from escalating intrusions. Whether mitigating ransomware, insider threats, or sophisticated nation-state attacks, Darktrace / OT ensures that industrial environments remain secure, operational, and resilient, no matter how threats evolve.

AI-powered incident response and SOC automation

Security teams are facing an overwhelming volume of alerts, making it difficult to prioritize threats and respond effectively. Darktrace / OT’s Cyber AI Analyst acts as a force multiplier for security teams by automating threat investigation, alert triage, and response actions. By mimicking the workflow of a human SOC analyst, Cyber AI Analyst provides contextual insights that accelerate incident response and reduce the manual workload on security teams.

With 24/7 autonomous monitoring, Darktrace / OT ensures that threats are continuously detected and investigated in real time. Whether facing ransomware, insider threats, or sophisticated nation-state attacks, organizations can rely on AI-driven security to contain threats before they disrupt operations.

Trusted by customers: Darktrace / OT recognized in Gartner Peer Insights

Source: Gartner Peer Insights (Oct 28th)

Beyond our recognition in the Gartner Magic Quadrant, we feel Darktrace / OT is one of the highest-rated CPS security solutions on Gartner Peer Insights, reflecting strong customer trust and validation. With a 4.9/5 overall rating and the highest "Willingness to Recommend" score among CPS vendors, organizations across critical infrastructure and industrial sectors recognize the impact of our AI-driven security approach. Source: Gartner Peer Insights (Oct 28th)

This strong customer endorsement underscores why leading enterprises trust Darktrace / OT to secure their CPS environments today and in the future.

Redefining the future of CPS security

It's our view that Darktrace’s recognition as the only Visionary in the Gartner Magic Quadrant for CPS Protection Platforms validates its leadership in next-generation industrial security. As cyber threats targeting critical infrastructure continue to rise, organizations must adopt AI-driven security solutions that can adapt, respond, and mitigate risks in real time.

We believe this recognition reinforces our commitment to innovation and our mission to secure the world’s most essential systems. This recognition reinforces our commitment to innovation and our mission to secure the world’s most essential systems.

® Download the full Gartner Magic Quadrant for CPS Protection Platforms

® Request a demo to see Darktrace OT in action.

Gartner, Magic Quadrant for CPS Protection Platforms , Katell Thielemann, Wam Voster, Ruggero Contu 12 February 2025

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant and Peer Insights are a registered trademark, of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences with the vendors listed on the platform, should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

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Pallavi Singh
Product Marketing Manager, OT Security & Compliance

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March 28, 2025

Survey Findings: AI Cybersecurity Priorities and Objectives in 2025

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AI is changing the cybersecurity field, both on the offensive and defensive sides. We surveyed over 1,500 cybersecurity professionals from around the world to uncover their attitudes, understanding, and priorities when it comes to AI cybersecurity in 2025. Our full report, unearthing some telling trends, is available now.  

Download the full report to explore these findings in depth

It is clear that security professionals know their field is changing fast, and that AI will continue to influence those changes. Our survey results show that they are aware that the rise of AI will require them to adopt new tools and learn to use them effectively. Still, they aren’t always certain about how to plan for the future, or what to invest in.

The top priorities of security stakeholders for improving their defenses against AI-powered threats include augmenting their existing tool stacks with AI-powered solutions and improving integration among their security tools.

Figure 1: Year-over-year changes to the priorities of securitystakeholders.

Increasing cybersecurity staff

As was also the case last year, security stakeholders are less interested in hiring additional staff than in adding new AI-powered tools onto their existing security stacks, with only with 11% (and only 8% of executives) planning to increase cybersecurity staff in 2025.

This suggests that leaders are looking for new methods to overcome talent resource shortages.

Adding AI-powered security tools to supplement existing solutions

Executives are particularly enthusiastic about adopting AI-driven tools. Within that goal, there is consensus about the qualities cyber professionals are looking for when purchasing new security capabilities or replacing existing products.

  • 87% of survey respondents prefer solutions that are part of a broader platform over individual point products

These results are similar to last year’s, where again, almost nine out of ten agreed that a platform-oriented security solution was more effective at stopping cyber threats than a collection of individual products.

  • 88% of survey respondents agree that the use of AI within the security stack is critical to freeing up time for security teams to become more proactive, compared to reactive

AI itself can contribute to this shift from reactive to proactive security, improving risk prioritization and automating preventative strategies like Attack Surface Management (ASM) and proactive exposure management.

  • 84% of survey respondents prefer defensive AI solutions that do not require the organization’s data to be shared externally

This preference may reflect increasing attention to the data privacy and security risks posed by generative AI (gen AI) adoption. It may also reflect growing awareness of data residency requirements and other restrictions that regulators are imposing.

Improving cybersecurity awareness training for end users

Based on the survey results, practitioners in SecOps are more interested in improving security awareness training.

This goal is not necessarily mutually exclusive from the addition of AI tools. For example, teams can leverage AI to build more effective security awareness training programs, and as gen AI tools are adopted, users will need to be taught about data privacy and associated security risks.

Looking towards the future

One conclusion we can draw from the attitudinal shifts from last year’s survey to this year’s: while hiring more security staff might be a nice-to-have, implementing AI-powered tools so that existing employees can work smarter is increasingly viewed as a must-have.

However, trending goals are not just about managing resources, whether headcount or AI investments, to keep up with workloads. Existing end users must also be trained to follow safe practices while using established and newly adopted tools.

Security professionals, including executives, SecOps, and every role in between, continue to shift their identified challenges and priorities as they gear up for the coming year in the Era of AI.

State of AI report

Download the full report to explore these findings in depth

The full report for Darktrace’s State of AI Cybersecurity is out now. Download the paper to dig deeper into these trends, and see how results differ by industry, region, organization size, and job title.  

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