Ivanti announced AI advancements to the Ivanti Neurons platform—providing solutions that transform how IT and security teams can harness AI-driven intelligence to achieve impactful business outcomes.
Features include the introduction of agentic AI capabilities to Ivanti Neurons for IT Service Management (ITSM), powerful autonomous endpoint management (AEM) and next-generation asset visibility in Ivanti Neurons for Discovery, providing IT and security teams scaled efficiency, deeper insights and reduced risk.
“Ivanti’s AI vision is about transforming how organizations harness intelligence to drive real business outcomes. Our strategy is grounded in practical innovation—embedding AI directly into the workflows our customers rely on every day," said Dennis Kozak, CEO at Ivanti. "As one of the only natively integrated AI-powered solutions unifying autonomous endpoint management, IT service management and security, the Ivanti Neurons platform helps customers enhance their AI journey and scale as business needs evolve with AI.”
This launch marks a pivotal step in transforming intelligence into impact, with highlights including:
- Agentic AI for ITSM: The new Agentic AI capabilities, built on Ivanti’s Conversational AI Framework, introduces persona-based agents directly to Neurons for ITSM. The agents will provide autonomous, goal-directed and natural-language experiences for Neurons for ITSM and ESM, accelerating resolution times and reducing service desk overhead. These agents empower teams to shift from reactive support to context-aware, autonomous service—resolving incidents and requests from start to finish through natural, conversational interaction. A customer preview launches in Q1, with general availability later in 2026.
- Autonomous Endpoint Management: Uniting DEX, UEM and security, Ivanti’s Autonomous Endpoint Management redefines how IT teams manage and protect every device by leveraging AI-powered automation and real-time data. AEM autonomously manages, secures and remediates endpoints, enabling IT and security teams to proactively reduce risk, scale efficiency and deliver seamless employee experiences.
- Asset Visibility & Exposure Aggregation: Unites software estate data with exposure management, providing foundational visibility for IT and security teams. With Ivanti Neurons for Discovery, organizations gain comprehensive asset intelligence—with embedded license management and unified risk insights—delivering real-time visibility, cost control and centralized vulnerability management across all assets.
The Latest
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...