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Security
AI is helping attackers make phishing, social engineering, and cyberattacks faster and more convincing. This guide explains the AI-related threats MSPs should monitor and how endpoint visibility and automation help security teams keep up.
Level
Monday, February 9, 2026
AI-powered cyberattacks are becoming more common because artificial intelligence is helping attackers improve phishing, social engineering, reconnaissance, impersonation, and attack automation. The biggest shift is not that AI has introduced entirely new categories of cybercrime. Instead, AI is making familiar attacks faster, more scalable, and often more convincing. Recent cybersecurity reporting through 2026 has highlighted growing concerns around AI-assisted phishing, impersonation, and attack automation. For MSPs, this means security teams need stronger visibility, faster response capabilities, better endpoint monitoring, and more automation to keep pace with evolving threats.
AI-powered cyberattacks are cyberattacks that use artificial intelligence to improve some part of the attack lifecycle.
This can include:
The National Cyber Security Centre assesses that AI will almost certainly increase both the volume and impact of cyberattacks by making existing attack techniques more effective. Rather than replacing attackers, AI helps them work faster and at greater scale.
For example, attackers can use AI to improve phishing messages, summarize public information about targets, translate scams into multiple languages, generate realistic content, or automate repetitive tasks that previously required manual effort.
The result is a lower barrier to entry for less experienced threat actors and improved efficiency for more sophisticated attackers.
Artificial intelligence is increasingly being integrated into cybercriminal operations because it reduces the time, cost, and effort required to conduct attacks.
The Canadian Centre for Cyber Security states that cybercriminals and state-sponsored actors are almost certainly leveraging generative AI to improve social engineering campaigns and create more convincing impersonation content. The report also notes that AI-generated audio and visual content can make fraudulent communications appear more legitimate.
The growing availability of AI tools means attackers no longer need extensive technical expertise to produce polished phishing emails, realistic impersonation attempts, or highly tailored messages.
At the same time, defenders face a growing challenge. Security teams must detect threats that can be generated faster, customized more easily, and delivered at greater scale than traditional attacks.
This dynamic is driving increased investment in security automation, monitoring, and response capabilities across organizations of all sizes.
Phishing remains one of the most common entry points for cyberattacks, and AI is making phishing campaigns more effective.
Traditional phishing emails often contained spelling errors, awkward phrasing, or obvious signs of fraud. Generative AI can eliminate many of these indicators by producing professional-looking content in seconds.
Attackers can now use AI to:
The scale of the threat remains significant. According to Microsoft, approximately 8.3 billion email-based phishing threats were detected during the first quarter of 2026. Microsoft also highlighted the continued growth of QR code phishing and CAPTCHA-gated phishing campaigns.
For MSPs, this means phishing prevention requires more than user awareness alone. Organizations need layered defenses that combine email security, identity protection, endpoint monitoring, user training, and incident response capabilities.
Social engineering attacks rely on manipulating people rather than exploiting technical vulnerabilities.
AI is helping attackers improve these tactics by generating realistic conversations, impersonating trusted individuals, and creating believable supporting content.
The Canadian Centre for Cyber Security warns that generative AI can create highly realistic audio and visual content that may be used to impersonate executives, colleagues, vendors, or trusted organizations.
Common AI-assisted social engineering attacks include:
For MSPs, this creates challenges around identity verification and support workflows.
Password resets, MFA changes, privileged access requests, and financial approvals should be backed by verification procedures rather than relying solely on email requests or voice communications.
Organizations that implement strong verification processes are generally better positioned to resist impersonation attempts, regardless of whether AI is involved.
Discussions around AI-generated malware often generate headlines, but the practical reality is more nuanced.
Current evidence suggests that AI is more commonly being used to assist with malware-related activities rather than autonomously creating advanced malware from scratch. AI can help attackers write scripts, explain code, troubleshoot development issues, summarize technical documentation, and accelerate parts of the attack process.
According to the National Cyber Security Centre, AI is expected to improve attacker capabilities in areas such as reconnaissance, vulnerability research, social engineering, and operational planning.
Attack automation is another area of concern.
AI can help threat actors:
For MSPs, the key concern is speed. As attackers become more efficient, defenders need stronger visibility and faster response processes to keep pace.
Even when AI is involved, most successful cyberattacks still interact with endpoints at some stage.
A phishing email may lead to malicious activity on a workstation. Stolen credentials may be used to access a managed device. Social engineering may convince a user to install unauthorized software.
This makes endpoint monitoring a critical security function.
MSPs should monitor for:
The National Cyber Security Centre emphasizes that traditional cybersecurity controls remain important even as AI changes the threat landscape.
The fundamentals still matter:
AI may change how attacks are executed, but it does not eliminate the importance of strong security hygiene.
One of the biggest challenges created by AI-assisted attacks is scale.
If attackers can generate more phishing messages, conduct more reconnaissance, and launch more campaigns, security teams need ways to respond efficiently.
Automation helps MSPs:
Automation does not replace human expertise.
Instead, it reduces repetitive administrative work so technicians can focus on investigation, remediation, and strategic security improvements.
Organizations increasingly recognize this need. Security teams are adopting automation to improve detection, accelerate response times, and manage growing workloads.
For MSPs, automation can be a force multiplier that helps teams handle more endpoints without sacrificing visibility or control.
AI-related cybersecurity risks are not limited to one specific attack type.
MSPs should pay attention to several categories of AI-assisted threats:
Recent enforcement actions illustrate the scale of the problem. According to Reuters, Google filed a lawsuit targeting the operators of an alleged AI-powered phishing kit and reported identifying more than 1.5 million related URLs over a several-month period.
For MSPs, the lesson is clear: attackers are using automation to scale operations, making proactive monitoring increasingly important.
Many organizations hear the phrase "AI cyberattack" and assume the threat is entirely new or fundamentally different from previous cyber risks.
In reality, AI is primarily amplifying existing attack techniques.
A practical client conversation should focus on:
Clients do not necessarily need to understand every technical detail about artificial intelligence.
They do need to understand that scams may become more convincing, impersonation attempts may become more realistic, and attackers may operate more efficiently.
The most effective defense remains a combination of people, processes, and technology.
AI-powered cyberattacks create a strong top-of-funnel opportunity because many organizations are trying to understand what AI means for cybersecurity and what actions they should take.
For MSPs, the answer often begins with endpoint visibility.
Level is relevant because AI-assisted attacks increase the need for endpoint monitoring, automation, patch management, scripting, reporting, and operational visibility. If attackers are moving faster, MSPs need tools that help them identify issues quickly, maintain visibility across devices, and respond consistently.
Endpoint monitoring in the AI era is not just about detecting advanced threats.
It is also about answering fundamental questions:
The organizations best positioned to handle AI-assisted threats are often those that already have strong operational visibility and mature endpoint management practices.
Preparing for AI-powered cyberattacks does not require abandoning traditional cybersecurity practices.
Instead, organizations should strengthen the controls that already provide value while improving their ability to detect and respond quickly.
A practical preparation strategy includes:
AI is changing how attackers operate, but it is not changing the core principles of cybersecurity.
Visibility, verification, patching, monitoring, and response remain essential.
Organizations that strengthen these areas will be better positioned to manage both current and future AI-assisted threats.
AI-powered cyberattacks use artificial intelligence to improve some aspect of an attack, such as phishing, social engineering, reconnaissance, impersonation, or automation.
Yes. Recent cybersecurity reporting indicates that attackers are increasingly using AI to improve phishing quality and scale. Microsoft reported approximately 8.3 billion email-based phishing threats during Q1 2026.
AI can assist with malware-related tasks such as scripting, troubleshooting, and code modification. However, the more immediate concern is that AI lowers barriers for attackers and increases operational efficiency.
MSPs should care because AI can increase the speed, scale, and effectiveness of attacks against clients, making monitoring, response, and endpoint visibility more important.
Endpoint monitoring helps identify suspicious activity, unauthorized software, unusual behavior, missing patches, and other indicators that may signal compromise.
Automation helps security teams improve consistency, reduce manual effort, accelerate response times, and maintain visibility across larger numbers of endpoints.
Organizations should start with the fundamentals: endpoint visibility, multi-factor authentication, patch management, user awareness training, access control reviews, and incident response planning.
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