Artificial Intelligence in UEM and ITAM Systems

Introduction

Artificial intelligence is no longer just a trendy marketing buzzword. Over the past two years, it has become one of the main areas of development for software that supports IT infrastructure management, cybersecurity, and the administration of computing environments.

Administrators increasingly expect UEM (Unified Endpoint Management) and ITAM (IT Asset Management) systems not only to monitor computers and generate reports, but also to provide intelligent support for data analysis, task automation, and decision-making.

This report outlines the key areas of AI application in modern UEM platforms and demonstrates how the features available in eAuditor align with current technological trends.

Why Is AI Changing the Way IT Infrastructure Is Managed?

Just a few years ago, most UEM systems were based on simple mechanisms:

• rules,
• schedules,
• scripts,
• static reports,
• classic alerts.

These days, administrators expect something more:

• automatic data interpretation,
• suggestions for corrective actions,
• generating administrative scripts,
• risk analyses,
• intelligent information retrieval,
• support in troubleshooting.

Solutions that utilize language models (LLMs), machine learning, and advanced data analysis can significantly reduce the time required to complete everyday administrative tasks.

Evaluation Methodology

For the purposes of this report, a 100-point evaluation model was developed. It covers ten areas of AI application in UEM and ITAM systems.

The methodology used is based solely on features documented by manufacturers in technical documentation, product materials, and official announcements. Features that were announced but not yet documented, or those available only in beta versions, were not included. Each area was evaluated in terms of the actual use of AI technology, rather than traditional rule-based automation.

The analysis covered the following groups of functionalities:

• an AI assistant that supports the administrator,
• the use of LLM models,
• generating administrative scripts,
• data analysis using AI,
• classification of applications, processes, and web pages,
• classification of documents and data in DLP systems,
• risk analysis and security recommendations,
• automation of administrative tasks using AI,
• AI-assisted reporting,
• the platform’s openness to integration with AI models and the direction of product development.

Based on the established criteria, the eAuditor system received the highest rating. This is because the product has publicly documented features that utilize language models, supports administrators through AI mechanisms, and offers solutions related to data classification, information analysis, and the automation of administrative tasks.

A Comparative Analysis of AI Features in UEM and ITAM Systems

The evaluation focuses on features that utilize language models (LLMs), machine learning, and intelligent data analysis. Traditional rule-based automation was not considered an AI feature.

eAuditor – Practical Applications of AI illustrated by key features

Based on the publicly described features of the eAuditor system, several areas of application for artificial intelligence can be identified.

AI that supports the administrator

The platform enables the use of language models to support an administrator’s day-to-day work, including analyzing issues and preparing responses to questions about the IT environment.

Generating Administrative Scripts

One of the practical applications of AI is the ability to generate PowerShell scripts and administrative commands based on a task description.

This approach helps reduce the time spent on routine tasks and minimize the number of errors.

Intelligent Classification

AI can support classification:

• applications,
• processes,
• websites,
• documents,
• data used in DLP policies,
• administrative tasks.

Reports generated by AI

Modern reporting isn’t limited to presenting data. AI can generate summaries, highlight key events, and suggest actions worth taking.

AI in Cybersecurity

Artificial intelligence can support the analysis of an organization’s environment, the identification of potential threats, and the development of recommendations to enhance the organization’s security.

Business Benefits

The use of AI in UEM systems can bring tangible benefits to organizations:

• reducing incident resolution time,
• faster development of administrative scripts,
• better security analysis,
• easier interpretation of reports,
• reducing the number of human errors,
• support for less experienced administrators,
• greater automation of daily tasks.

Applications

The comparison shows that the development of AI capabilities is becoming one of the key differentiators among modern ITAM and ITSM systems. While most available solutions offer advanced automation and traditional infrastructure management mechanisms, the use of language models, intelligent data analysis, and recommendation generation remains relatively rare.

Based on publicly available information, eAuditor offers the broadest range of AI-powered features among the Polish solutions analyzed. In particular, this includes support for administrators through LLM models, intelligent data classification, automation of administrative tasks, and analysis of security-related information.

At the same time, it should be noted that the AI market is growing very rapidly. Information published by manufacturers and product functionality are subject to change; therefore, the results presented should be viewed as a snapshot of the market at the time the analysis was conducted. To ensure complete objectivity, the benchmark must be updated periodically, and each evaluated feature must be verified against the manufacturers’ official documentation.