The advancement of Generative AI is setting a new standard in device management, offering a more efficient, user-friendly approach to handling enterprise mobile devices.
Via natural language processing (NLP) architectures, this technology reduces the reliance on traditional help desk calls, substantially decreasing support costs. Moreover, it harnesses predictive analytics and data-driven insights to enhance device uptime and productivity, marking a significant leap toward autonomous IT service management.
Samsung SDS and IBM are at the forefront of such innovations, collaborating on technology that embeds WatsonX Assistant and Omni channel chatbot interface into ZTM for provisioning, deployment, and lifecycle management of enterprise mobile devices at scale. This integration enables users to interact with ZTM/ServiceNow through a natural language interface with generative capabilities, accessible either through a web-based chat function or via Mobility Channels within MS Teams or Slack. This strategic implementation marks the first step towards streamlining operations and lays the foundation for a meaningful transition to self-service and to predictive and proactive maintenance of mobile devices.
The application of Generative AI in this context has led to notable outcomes, including a ~70% reduction in calls to help desks, translating to a significant cost saving of approximately $25-$35 per incident. More generally, AI impacts the employee experience through its ability to facilitate seamless and intuitive interactions with device management systems.
The integration of Generative AI into device management frameworks significantly uplifts the employee experience across various facets. As the younger generation enters the workforce, a focus on giving them access to support through interfaces that are familiar to, and expected by, them is paramount to future success and retention. People no longer remember phone numbers. In a 2022 survey by WhistleOut, they found that 16% of people don't even remember their parents' numbers, and 49% only remember 2–5 numbers from their contacts. In the case of a lost/stolen/broken device situation, where speed of reporting and action is paramount to ensuring data security and reducing downtime, giving employees access to an efficient interface to communicate with support can mean the difference between positive or extremely negative outcomes.
The conventional process of provisioning, deploying, and managing enterprise mobile devices, regardless of ownership type (COBO/COPE or BYOD) is labor-intensive and time-consuming. Generative AI simplifies this by applying automation to the entire device management lifecycle.
Consequently, IT teams can redirect their focus toward strategic initiatives that drive business value. Furthermore, this technology enables a shift from traditional self-service portals to more intuitive, natural language interfaces. Employees can now interact with device management and support systems through familiar platforms such as MS Teams or Slack, enhancing user satisfaction by providing support in a more accessible, fast, and engaging manner, no training necessary.
Generative AI can perform predictive analytics and preemptively identify and address potential device issues, ultimately minimizing the likelihood of work interruptions and eliminating costly support calls. By aggregating data from multiple siloed systems and analyzing device performance in real time, AI algorithms, in conjunction with diagnostic tools like Knox Asset Intelligence, can forecast hardware malfunctions or software issues, and remedy them, before they disrupt the end-user's activities.
This preemptive approach to maintenance ensures that avoidable problems are promptly resolved — maintaining seamless operations and enhancing the overall user productivity and experience.
One central benefit of Generative AI in device management is its capability to enhance device reliability and performance through continuous analysis and optimization. This ongoing refinement model guarantees that mobile devices remain operational, reducing the instances of productivity loss associated with device failures or downtime. In turn, employees benefit from a consistent and dependable technology environment that supports their daily activities without interruption.
Generative AI significantly lowers the operational strain on IT help desks by automating the resolution of frequent issues. It answers complex or unresolved inquiries with AI-enhanced chat interfaces, providing immediate, accurate, and context-aware support to users. This capability not only reduces the volume of calls to help desks but also diminishes the time employees spend troubleshooting device-related problems, thereby streamlining the support experience.
The overarching impact of Generative AI in device management culminates in substantial cost savings for organizations. By diminishing the frequency of device support incidents and optimizing the support process through AI-driven chatbots, companies experience reduced operational disruptions and enjoy financial benefits from lowered support expenses. These savings can then be reallocated to further technological enhancements or other areas of the business, fostering a cycle of continuous improvement and innovation.
The role of Generative AI in next-generation device management is transformative, offering unprecedented efficiencies in how enterprise IT services are delivered and managed. By enhancing the employee experience through automated processes, predictive maintenance, and interactive support systems, organizations can achieve higher productivity levels, reduced operational costs, and a more satisfied workforce.
Samsung SDS and IBM Watson are revolutionizing IT asset management by leveraging Generative AI to introduce next-generation efficiencies and innovations. This collaboration brings IBM WatsonX's advanced AI capabilities into Samsung SDS's Zero Touch Mobility (ZTM) device lifecycle management solution for ServiceNow, hyperautomating the provisioning, deployment, and management of enterprise mobile devices.
By incorporating predictive analytics and AI-driven insights, this partnership aims to significantly reduce the manual workload associated with device management, while also enhancing device uptime and reliability. The result is a proactive and predictive approach to IT asset management that not only streamlines operations but also significantly cuts support costs, estimated to save millions in operational expenses.
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