A new report from cybersecurity vendor Cynet finds managed service providers are pulling ahead of in-house security teams in AI adoption and confidence, even as both groups identify AI-powered phishing and social engineering as their top cybersecurity threats. The findings suggest organizations are increasingly turning to MSPs for AI-driven security capabilities as cyberattacks become more automated.
Cynet’s Global AI Security Readiness Report, based on a March 2026 survey of 1,600 respondents across nine countries worldwide, conducted by Sapio Research, found MSPs consistently report higher adoption of AI security tools, greater confidence in detecting and responding to threats, and stronger plans to expand AI-driven security operations than their enterprise counterparts.
AI phishing and identity attacks top security concerns
Asked what they’re most worried about defending against in 2026, both groups landed on the same answer: AI-enabled phishing and social engineering, which 39% of MSPs and 40% of in-house teams cited as a top priority.
Identity-based attacks, things like credential theft, MFA fatigue, and OAuth abuse, came in a close second, named by 39% of MSPs and 33% of in-house teams.
Ransomware, data theft, and supply chain attacks rounded out the list of top concerns, though all trailed behind the AI-driven threats.
MSPs report higher confidence in AI-driven defense
The report highlights a split in confidence levels. Seventy-one percent of MSPs say they’re “very confident” in their ability to detect and respond to incidents, a number the report attributes largely to their heavier use of AI tools.
In-house teams are far less sure of themselves; just 43% describe themselves as very confident, while another 49% land in the “somewhat confident” camp.
That gap shows up in the numbers on actual AI use, too. MSPs reported using AI or LLM-based tools at an average rate of 60% across various security functions, compared to 44% for in-house teams.
The widest gaps appear in automated remediation and response (64% of MSPs versus 48% of in-house teams) and in AI copilots for analysts (61% versus 46%).
Security budgets rise as AI adoption pressure grows
Budgets tell a similar story of AI-driven urgency. Eighty-nine percent of MSPs and 78% of in-house teams plan to spend more on security tools in 2026 than the year before, with faster detection and response cited as the top reason for the additional spending.
For in-house teams specifically, cloud security, securing AI agents and large language models, and identity security top the list of planned investments for the year.
Still, hesitation lingers. The report notes that 14% of in-house teams say AI assistants and AI-driven security agents aren’t important to them, and 7% have no plans to adopt agentic AI in that area at all.
In-house teams report higher incident rate than MSP clients
In-house teams reported far more security incidents than MSPs saw among their client bases; 60% of in-house respondents said they’d experienced or suspected an incident in the past two years, compared to an average of just 22% of MSP customers.
The report suggests this may indicate that MSP clients are better protected in the first place, though it also notes that detection rates vary widely by region, with Southern European companies reporting both fewer incidents and lower detection rates when using their own tools.
Ransomware was the most common incident type MSPs dealt with (57%), while business email compromise topped the list for in-house teams (51%).
In-house teams look to MSPs for agentic AI deployments
Recognizing their own resource limitations, internal corporate security teams are increasingly looking to outsource their AI transformations.
A significant 59% of in-house teams explicitly plan to involve an MSP when deploying new cybersecurity capabilities, like EDR, cloud protection, or agentic AI tools.
When it comes to rolling out next-generation capabilities like agentic AI, nearly two-thirds (61%) of internal security departments prefer to deploy it either entirely through an MSP or via a hybrid co-managed model.
As the report concludes, running a sophisticated, entirely manual defensive operation in-house is becoming a losing proposition.
With threat actors fully embracing automated offensive tactics, leveraging specialized, AI-driven partnerships is no longer just an efficiency play; it is a baseline requirement for survival.