Purpose Traditional performance measurement and management have faced significant criticism for their limited capacity to address the complexities and volatility of contemporary organizational contexts, particularly within the paradigm of the Fourth Industrial Revolution. IoT and sensor systems today find themselves defining a paradigm of extreme dataism, difficult to effectively represent information. Therefore, the integration of artificial intelligence (AI) into performance measurement and management represents a transformative innovation. It enhances operational efficiency and enables organizations to respond more effectively to rapidly changing environments. This study investigates the advantages of incorporating AI in the performance measurement and management to improve decision-making processes, through the transition from Industry 4.0 to 5.0, anticipating the possibility of a further sixth evolution. Design/methodology/approach Employing a systematic literature review guided by the PRISMA framework to ensure methodological rigor, this research analyzed over 100 scientific publication articles, thanks to integrative machine and human-based steps of analysis. Findings The findings highlight the AI integration across three key dimensions: organizational context, development processes and measurement and management content. AI is revolutionizing performance measurement and management by enabling real-time, precise assessments of key performance indicators, enhancing transparency and fostering objectivity. Furthermore, its predictive and prescriptive analytics capabilities empower organizations to improve strategic decision-making through advanced modeling techniques. Originality/value AI is one of the pivotal drivers in the evolution of performance measurement and management; it is recognized as foundational enabler of Industry 5.0 and a potential cornerstone of the emerging Industry 6.0 framework.

Integrating artificial intelligence into performance measurement and management: a systematic literature review

Sardi Alberto;Modarelli Giuseppe
2026-01-01

Abstract

Purpose Traditional performance measurement and management have faced significant criticism for their limited capacity to address the complexities and volatility of contemporary organizational contexts, particularly within the paradigm of the Fourth Industrial Revolution. IoT and sensor systems today find themselves defining a paradigm of extreme dataism, difficult to effectively represent information. Therefore, the integration of artificial intelligence (AI) into performance measurement and management represents a transformative innovation. It enhances operational efficiency and enables organizations to respond more effectively to rapidly changing environments. This study investigates the advantages of incorporating AI in the performance measurement and management to improve decision-making processes, through the transition from Industry 4.0 to 5.0, anticipating the possibility of a further sixth evolution. Design/methodology/approach Employing a systematic literature review guided by the PRISMA framework to ensure methodological rigor, this research analyzed over 100 scientific publication articles, thanks to integrative machine and human-based steps of analysis. Findings The findings highlight the AI integration across three key dimensions: organizational context, development processes and measurement and management content. AI is revolutionizing performance measurement and management by enabling real-time, precise assessments of key performance indicators, enhancing transparency and fostering objectivity. Furthermore, its predictive and prescriptive analytics capabilities empower organizations to improve strategic decision-making through advanced modeling techniques. Originality/value AI is one of the pivotal drivers in the evolution of performance measurement and management; it is recognized as foundational enabler of Industry 5.0 and a potential cornerstone of the emerging Industry 6.0 framework.
2026
1
44
Artificial intelligence, AI, Performance measurement, Performance management, Performance measurement and management system, Business performance, Decision making, Industry 4.0, Industry 5.0, Industry 6.0
Sardi Alberto; Modarelli Giuseppe
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2124054
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