Get immediate AI-generated summaries for each Windows update, including KB details, purpose, and potential effects—helping you decide faster with better context.
Leverage AI-driven insights to evaluate patch stability and reliability with greater confidence, helping IT teams make safer, data-informed deployment choices.
Identify and prevent patch-related problems before they happen. AI insights help IT teams reduce downtime, maintain system reliability, and deploy patches more confidently.
Automatically analyze Windows OS patches for potential issues, providing context about patch stability, known bugs, and aggregated user sentiment.
View clear AI-generated patch statuses that help guide safe deployment decisions. Each Windows update is automatically categorized with a status indicator such as “–” for no data available, “Appears Stable” for patches with no major concerns, “Caution” for updates with potential issues, and “Known Issues” for Microsoft-reported problems that may include possible workarounds.
Enable or disable AI Patch Intelligence through the NinjaOne AI application, giving administrators full control over AI participation in the patching process.
Enterprise IT teams can use AI Patch Intelligence to focus on stable updates first, reducing disruptions from faulty patches. Clear risk indicators help teams plan phased deployments while maintaining consistent uptime across all endpoints. By identifying potentially problematic patches early, enterprises can proactively avoid large-scale service interruptions and improve operational resilience.
MSPs managing multiple client environments save hours per week by using AI-generated patch summaries. They can identify “Known Issues” or “Problematic” patches faster and prevent rollout problems that impact multiple customers. This automation allows MSPs to dedicate more time to strategic service improvements rather than repetitive patch research.
For organizations under strict compliance standards, AI Patch Intelligence offers audit-friendly transparency. Every AI summary adds traceability to patch decisions, helping IT teams justify delays or exclusions during audits. With clear documentation of patch status and risk level, teams can more easily demonstrate compliance with internal and regulatory patch management policies.
Experience a smarter way to patch Windows systems. With NinjaOne AI Patch Intelligence, you gain immediate patch insights, proactive risk detection, and AI-powered confidence in every update. Keep your endpoints secure and your patching strategy one step ahead.
Patch management is the process of creating, testing, and deploying software updates to various endpoints. These updates, also known as “patches,” improve the current software by fixing technical issues, tightening security, or releasing new features.
The amount of technology is growing exponentially as people and organizations undergo digital transformation. As a result, more information and data are found online and on machines than ever before. It’s important to keep this data safe in properly functioning software on devices and machines, which is why applying patches is a critical task in IT security.
100,000
Endpoints managed
“NinjaOne is a scalable solution. It’s built on a modern SaaS architecture and it’s future-proof.”
40%
More Cost Effective
“NinjaOne’s price point is 40% less than any other endpoint management tool on the market, while being more powerful and easy to use.”
10-15
Tools Replaced
“Before, I needed 10-15 different tools to execute what NinjaOne does in its centralized, single pane of glass.”
30%
Less time for patching
“We observed a 30% reduction in the time taken for patch deployments compared to our previous solution.”
2,000
Endpoints managed
“NinjaOne gives me much more flexibility and security in my work”
30%
Annual ROI
“[NinjaOne] has already shown its value in ROI…it’s at least a hundred thousand dollars annually.”
24x
Faster Endpoint Management
“Our processes have become 24x faster with NinjaOne.”
20-40
Hours Saved Each Week
“Leveraging the automations feature within NinjaOne has enabled me to save upwards of what would likely be 20 to 30 to even 40 hours per week.”
AI Patch sentiment is a feature for Windows OS patches that uses generative AI to provide instant analysis of Knowledge Base (KB) patches. This capability within the AI patch management workflow synthesizes details about patch purpose, features, potential issues, and user sentiment to provide richer context for IT decision-making.
NinjaOne’s AI patch software provides sentiment analysis indicators such as Appears Stable, Caution, and Known Issues to help IT teams decide which patches to install first, but it does not automatically prioritize or deploy them.
The AI cannot automatically prevent patch deployment. Instead, this AI patch tool delivers analysis and recommendations to highlight potential risks, allowing administrators to take proactive measures. Users should not rely solely on the AI feedback to make final patching decisions.
The feature is not fully automated. It provides manual configuration options, allowing users to enable or disable the AI sentiment analysis feature. Administrators retain full control over approvals and deployment timing within the AI patch platform.
Currently, AI Patch Intelligence is only available for Windows OS patches. It does not yet support Linux or macOS environments.
NinjaOne’s AI Patch Intelligence uses generative AI and third-party content to analyze patch information, providing intelligent insights about potential patch risks and generating sentiment statuses to help IT professionals make informed decisions.
Before deployment, the AI provides a detailed overview to help guide IT decisions. It summarizes the patch’s purpose and key features, highlights any potential issues or bugs, and includes aggregated user sentiment and feedback gathered from various trusted sources. Additionally, it assigns an AI-generated patch status to indicate overall stability and reliability, helping IT teams make more informed and confident patching decisions.
AI Patch reduces manual research time by instantly surfacing relevant patch information and known issues. This helps IT teams make faster, more informed decisions while maintaining oversight of deployment strategy.
AI Patch is built to enhance, not replace, human decision-making. While it provides valuable insights to support patching strategies, it should never be the sole source of truth. IT teams are strongly advised to validate AI-generated analysis with official vendor documentation and conduct internal testing to ensure patch stability and safety before deployment.
