AI-powered security tools promise to make MSP operations more efficient, but new research from N-able suggests they may be creating additional challenges for providers already struggling with security alert fatigue.
According to N-able’s AI Fog Report: When the Signal Becomes the Noise, released October 15, 61% of MSP respondents said security alert noise disrupts incident response daily or several times per week, while 86.8% reported an increase in alert volumes over the past year.
The report draws on responses from 595 cybersecurity decision-makers and practitioners across the United States and United Kingdom, including 182 MSP respondents.
Among those MSPs, 82.4% reported increasing their use of AI-powered security tools, but just 23.6% said they fully trust autonomous AI remediation.
MSPs face greater disruption from security alert noise
The operational impact appears particularly pronounced among MSPs, which must manage security alerts across multiple customer environments.
While 61% of MSP respondents reported frequent disruptions to incident response, that figure fell to 43.4% among SMBs and 57.1% among midmarket organizations.
Across the broader survey, 50.4% of respondents identified duplicate alerts from overlapping security tools as a leading source of noise, while 48.9% pointed to AI-generated alerts lacking sufficient context.
The findings suggest that MSPs may need to prioritize security tool integration, alert consolidation, and better contextual intelligence before expanding their use of AI-powered automation.
AI security adoption rises faster than trust in automation
While 82.4% of MSP respondents reported increasing their use of AI-powered security tools, only 23.6% fully trust autonomous remediation.
“It was surprising to see how many organizations felt that adopting AI tools justified accepting some level of security risk, with 87% of respondents saying a security exception was needed,” Brendan Griffin, N-able’s director of threat research, told Channel Insider.
“That shows just how important this transformation is to businesses, but it also raises a question about whether those exceptions are becoming routine. When the exception becomes the rule, it’s time to revisit the guardrails. Organizations need to understand what risk they are accepting, who owns that decision, and when it needs to be reassessed,” Griffin continued.
Across the broader survey, only 51.9% maintained a comprehensive inventory of AI tools operating within their environments.
The trust gap could complicate MSP efforts to automate security operations, particularly when tools are authorized to take actions across customer infrastructure.
Respondents identified explainability of AI decisions (62.7%), human override capabilities (59.8%), and proven low false-positive rates (55.6%) as leading requirements for trusting autonomous AI.
“Our research underscores the importance of reducing uncertainty in automation, with over half of respondents identifying explainability and opportunities for human intervention as key priorities,” said Griffin. “MSPs should define what success looks like, where human review is needed, and how someone can intervene if an automated process goes off course.”
How MSPs can reduce alert noise and improve AI oversight
For MSPs planning future security investments, the research suggests prioritizing measurable operational improvements over simply expanding AI capabilities.
More than half of respondents (56%) identified faster detection-to-containment as a valuable AI outcome, while 45.4% prioritized context-rich alerts.
“So much of this conversation is about context: understanding how AI fits into our technology stacks, what it can access, and how it is monitored and managed,” said Griffin. “MSPs have an opportunity to turn that uncertainty into practical governance by helping customers establish visibility into AI use, define access and permissions, and set clear boundaries for automated actions.”
“Trust in AI has to be earned at the operational level. Transparency gives organizations the context to understand what AI is doing and the confidence to decide where it belongs,” he continued.
Providers should also review AI governance policies, document approved tools, and assess whether existing security infrastructure can support further automation.
Ultimately, the findings suggest that MSPs that can reduce alert fatigue, strengthen governance, and demonstrate faster incident response may be better positioned to translate AI investments into both operational efficiency and customer value.
READ MORE: We spoke with N-able CEO John Pagliuca about how AI is becoming a differentiator for MSPs across services and solutions.
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