ARTIFICIAL INTELLIGENCE IN SYSTEMS ANALYSIS

Abstract

Tools based on artificial intelligence (AI) and machine learning (ML) help systems analysts automate routine tasks of data collection and analysis. This allows analysts to focus on more complex aspects of systems analysis. However, the requirements for the professionalism of specialists in the field of systems analysis are increasing, as new tasks appear that require a high level of knowledge and skills in the field of AI and data analytics. There are various specialized professions in the field of systems data analysis, including: systems analyst, data engineer, data analyst, data scientist, machine learning engineer, machine learning engineer, natural language processing specialist, business analyst, and others. And all of them now use a wide range of AI tools in their professional activities to improve the processes of analysis, modeling, and decision-making. The article analyzes the role and possible areas of application of AI and ML algorithms in the work of various big data analysis specialists. For each profession, possible AI tools that can be useful in the activities of relevant specialists to solve specific professional tasks are systematized and characterized. The paper found that ML tools help to identify patterns and anomalies, create forecasts and analytical models, and optimize processes in real time. AI allows us to integrate new forecasting and analytics methods, which contributes to accurate, timely decision-making at all stages of data processing. AI technologies change traditional approaches to data analysis and modeling. They create new opportunities for rapid development of solutions, increasing the efficiency of business processes and optimizing information systems. AI helps specialists ensure high data quality, automate the detection of anomalies and improve forecasts to support the strategic development of organizations, particularly in a rapidly changing market environment.