AIOps: Improve IT Efficiency and Employee Satisfaction

The Business Impact of IT Issues

From end user devices to networks and servers, IT infrastructure enables business success. Without it, operations, innovation, and productivity come to a halt.

IT teams supporting businesses today spend considerable time troubleshooting and resolving technology issues. Their time, in addition to lost employee productivity until issues are resolved, comes at a substantial cost to the business.
 

• Adobe’s “The Future of Digital Work” survey found that poorly functioning technology resulted in up to four hours a day of lost productivity, according to 58 percent of tech leader respondents.¹
• A 2023 IDC survey of midsize and enterprise businesses reported that 96 percent of employee respondents said a high-quality PC was either somewhat or very important to their productivity and job satisfaction.

Common Device-Related Issues

The most common device-related issues with significant impact on employee productivity include:

• Poor device performance, including slow system responsiveness, stuttering of audio or video streams, or “hanging” applications
• Inadequate or diminishing battery life
• System crashes, both recoverable from a restart and nonrecoverable
• Cyberattack-related issues

In many cases, employees may continue to work through less severe recurring issues without reporting them to IT to avoid being without their devices. However, this can lead to growing employee frustration, decreased employee satisfaction, and more severe problems if unresolved, including unrecoverable system failures or security breaches.

When IT teams do engage with employees to address a problem, they often face the time-consuming task of determining the root cause of the reported issue. This involves running through many standard process steps to rule out common causes before considering more-invasive steps or resorting to a system reinstall without identifying the root cause.

How to Use Artificial Intelligence to Address Your IT Ops Challenges

AIOps is an emerging strategy that uses AI-enabled tools to assist IT Ops. When applied to the management of end user devices, AI can actively monitor device hardware, use derived insights to proactively resolve potential issues, and provide real-time insights to IT teams to help with root cause analysis and quick issue resolution. The result is saved time and productivity and an improved IT and employee experience.

AIOps Use Cases

AI can rapidly process large disparate datasets and provide near-real-time insights. When AI is applied to IT Ops, it can use real-time and historical data to identify anomalies, use event correlation to alert IT team members to an issue proactively, take a prescribed action, or suggest root causes or resolution steps.

Further, device-based AI capabilities provide the additional benefits of reduced latency, improved data control, and lower cost compared to cloud-based solutions, as all data resides on the device, and AI processing and analysis are done locally.

Common AIOps use cases that can help reduce IT support costs and employee impacts include:

• Improved ability to identify and proactively prevent potential issues or failures
  • Systems monitoring and predictive analytics: AI algorithms can analyze resource usage and device performance data; identify potential issues, such as sudden battery decline, memory errors, or fan failure; and either take proactive restorative action or alert users to issues while providing next-step resolution recommendations.
  • Cyberthreat detection monitoring: CPU telemetry and machine learning (ML) algorithms can profile and detect malware, such as ransomware and cryptojacking, at the hardware level and alert the end user to suspected threats or trigger built-in device protection methods.
• Improved ability to understand the cause of the issue
  • Root cause analysis: AI algorithms can analyze system data to identify underlying hardware issues, provide suggested configuration modifications, or take proactive action. For example, a device used for heavy graphics rendering may be experiencing lag. Analysis of system data may identify an issue with a memory configuration preventing an optimal experience. Or a device used for AI workloads may be overloading the CPU, and analysis of system usage may result in an automatic system action to shift data processing to an integrated NPU or GPU.
  • Crash prediction and analysis: AI algorithms can analyze and correlate telemetry data to identify potential issues or postcrash causes. Findings and remediation suggestions can be shared with IT teams or provided as an alert to an end user before system failure.

Get Started with AI for Improved IT Ops Efficiency

Your IT teams can start taking advantage of hardware-based, AI-assisted threat detection capabilities today with enterprise AI PCs built on the Intel vPro® platform. Integrated Intel® Threat Detection Technology (Intel® TDT) uses CPU telemetry and machine learning (ML) algorithms to profile and detect cyberattacks that evade traditional detection methods, helping to improve monitoring and security performance at the hardware level.

Additionally, Intel has worked with leading security ISVs to preintegrate Intel® TDT into their solutions so IT teams can quickly activate hardware-based security capabilities on Intel vPro®-based devices. Intel vPro®-based AI PCs with Intel® Core™ Ultra processors benefit from three dedicated engines (CPU, GPU, and NPU), integrated AI accelerators, and an AI-optimized architecture to ensure a performant user experience while increasing endpoint threat protection capabilities.

Beyond integrated hardware-based security capabilities, the integrated remote management capabilities of Intel vPro® provide IT teams with the tools they need to support employees and securely manage fleets of devices, even when powered off or nonresponsive, inside or outside the firewall, and over the cloud.

Intel® Device Discovery, made possible through the Intel® Innovation Platform Framework (Intel® IPF), offers a new way for cloud services and tools to interact with Intel vPro® platforms and collect data that helps inform device management decisions, including platform brand identity, features present, wear and tear history, and other datasets intended to increase the functionality of device management software and support AIOps.

• Explore the benefits of AI PCs based on the Intel vPro® platform.
• Read “What You Need to Know to Buy PCs for Your Company” to learn how upgrading devices can help you meet IT and employee needs.