ManageEngine announced that the cloud version of ServiceDesk Plus, its flagship IT service management solution, now includes Zia, Zoho's AI assistant as a virtual IT support agent.
Zia can answer simple questions, perform service desk operations, and interact with third-party apps, reducing response times and boosting technician efficiency. End users and technicians can chat with Zia in a conversational interface, or converse with Zia Voice to access more than a dozen out-of-the-box Zia actions, as well as any custom Zia actions created by service desk teams.
ManageEngine will debut Zia for ServiceDesk Plus at its 2019 User Conference in Dallas, Texas from April 24-26.
One of the biggest challenges for service desk teams is striking the right balance between business-critical ITSM projects and keeping up with daily firefighting or answering less crucial questions from end users. The lack of immediate access to the service desk team and service desk information can lead to end user frustration and lower satisfaction rates. A 24/7 virtual support agent helps address these challenges by offering end users prompt support. Virtual support agents are also valuable for technicians working in the field who may not have access to standard service desk interface and resources. Being able to interface by voice commands with a virtual support agent is beneficial for troubleshooting and implementing corrective actions.
"While business end users want on-demand access to IT service desk personnel, IT support staff prefer to focus on higher priority activities and do away with attending to level 1 support. Zia brings perfect balance to service desk operations by offering end users the same quality of support they’d receive from technicians, relieving support staff so they can focus on far more important tasks,” said Rajesh Ganesan, vice president of product management at ManageEngine. “We envision Zia will evolve into a smart AI-powered personal assistant offering contextual support, providing immediate assistance for every user in the organization, and elevating the user experience many notches."
Redefining First Point of Contact for IT Service Desk Users
"With the debut of Zia as a virtual support agent, we are laying the groundwork for enhancing service delivery and service desk efficiency with AI,” said Umasankar Narayanasamy, Director of Engineering at ManageEngine. “We plan to add predictive analytics and intelligent automations to Zia, so customers won’t need to write manual rules."
Zia can perform a wide variety of tasks, including:
- Providing answers to straightforward questions.
- Pulling up service desk data to answer more complex questions.
- Triggering service desk operations through a tree-structured interaction.
- Sharing relevant knowledge base articles based on end users’ inputs.
- Automatically handing off user requests to technicians via live chat or by creating a new request.
Building Custom Zia Actions for ServiceDesk Plus
Apart from the out-of-the-box Zia actions available, service desk teams can script custom Zia actions to answer questions, perform activities in external tools that integrate with ServiceDesk Plus, and more. The serverless Zia developer console offers development and production modes, making it easier for service desk teams to script and save custom Zia actions for immediate use in ServiceDesk Plus. Each custom Zia action can be built with multiple conversations, and IT staff can add provisions for Zia to collect appropriate inputs at every stage of an interaction.
Pricing and Availability
Zia is freely available in all editions of the cloud version of ServiceDesk Plus.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
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 ...