Lenovo and ServiceNow connect device telemetry to governed support workflows so teams can address some problems before employees report them.
Back to NewsLenovo and ServiceNow expanded their multi-year agreement at Knowledge 2026. The companies want to improve device support with connected data and workflows. Lenovo supplies device signals. ServiceNow helps route the response.
The goal is simple. Find some problems before employees report them. Then send each issue through a governed support process.
Large device fleets are hard to support. Different vendors often own different parts of the service. Global operations add more handoffs and more delay.
Lenovo executive Rakshit Ghura described that problem in an interview about the joint platform. He said many companies already collect useful device data. However, that data often stays separate from the workflow that could act on it.
Employees then have limited options. They tolerate the problem, attempt a fix, or contact support. Earlier action could reduce that lost time.
Lenovo's xIQ Digital Workplace runs on ServiceNow. It combines device data with service workflows and lifecycle tools. The platform can watch device signals and start a response when it detects trouble.
Ghura estimates proactive support can save 20 to 30 minutes per employee each week. That is an executive estimate, not an independent result.
Lenovo also reports up to 30% lower IT support costs and faster employee productivity. Those figures come from Lenovo. They are not a neutral customer benchmark.
Lenovo expects companies to use more AI agents at work. Those agents need clear ownership and controls. Teams must know what each agent can access and change.
ServiceNow says AI Control Tower covers five areas: discovery, observation, governance, security, and measurement. Its tools can track AI assets, permissions, costs, and activity. Lenovo selected that layer for its wider agent plans.
The design still has limits. Ghura identified token optimization as a priority. That signals an open cost problem. It does not prove the current platform controls model spending well.
Start with one common device incident. Trace it from the first signal to the final fix.
Ask where the device data lives. Confirm which system starts the support workflow. Record which steps are automatic. Identify every step that still needs approval.
Then review the AI controls. Who owns each agent? Which identities and applications can it reach? Where are its actions logged? Who can stop it?
The announcements explain the planned architecture. They do not provide detailed implementation costs or independent performance data.
Do not begin with a broad platform rollout. Test one incident type first. Measure detection time, resolution time, support effort, and false alarms.
Compare those results with the current process. Also ask for customer evidence from an organization with a similar device fleet and geographic footprint.
That test will show whether the platform removes a real support bottleneck. It may instead add another layer to manage.
