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Using artificial intelligence (AI) to minimize errors in business enterprise management

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using artificial intelligence (AI) to minimize errors in business enterprise management/ by Helmut Becker.
Author:	Becker, Helmut.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden : : 2025.,
Description:	xxxiii, 188 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	ERROR THEORIES; ANALYSIS, CHANGE ANDDEVELOPMENT OF ORGANIZATIONAL CULTURE, ARTIFICIALINTELLIGENCE -- DEVELOPMENT AND APPLICATION OF ANINTEGRATED AUDIT APPROACH TO IDENTIFY THE WEAKNESSES OFTHE RISK MANAGEMENT SYSTEMS ISO 31000 AND COSO ERMFRAMEWORK IN CAPTURING THE ERROR CULTURE, WHICH HASTHE POTENTIAL FOR OPERATIONALIZATION THROUGH AI -- COMPARISON OF THE RISK MANAGEMENT SYSTEMSISO 31000:2018 AND COSO ERM FRAMEWORK WITH REGARD TOTHEIR ABILITY TO CAPTURE THE ERROR CULTURE -- INTERPRETATION OF RESULTS: EVALUATING ISO31000:2018 AND COSO ERM FRAMEWORKS IN CAPTURING ERRORCULTURE AND POTENTIAL IMPROVEMENT THROUGH AISOLUTIONS USING A HOLISTIC APPROACH WITH MOS.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-658-47243-6
ISBN:	9783658472436

Using artificial intelligence (AI) to minimize errors in business enterprise management
Becker, Helmut.

Using artificial intelligence (AI) to minimize errors in business enterprise management[electronic resource] /by Helmut Becker. - Wiesbaden :Springer Fachmedien Wiesbaden :2025. - xxxiii, 188 p. :ill. (some col.), digital ;24 cm.

ERROR THEORIES; ANALYSIS, CHANGE ANDDEVELOPMENT OF ORGANIZATIONAL CULTURE, ARTIFICIALINTELLIGENCE -- DEVELOPMENT AND APPLICATION OF ANINTEGRATED AUDIT APPROACH TO IDENTIFY THE WEAKNESSES OFTHE RISK MANAGEMENT SYSTEMS ISO 31000 AND COSO ERMFRAMEWORK IN CAPTURING THE ERROR CULTURE, WHICH HASTHE POTENTIAL FOR OPERATIONALIZATION THROUGH AI -- COMPARISON OF THE RISK MANAGEMENT SYSTEMSISO 31000:2018 AND COSO ERM FRAMEWORK WITH REGARD TOTHEIR ABILITY TO CAPTURE THE ERROR CULTURE -- INTERPRETATION OF RESULTS: EVALUATING ISO31000:2018 AND COSO ERM FRAMEWORKS IN CAPTURING ERRORCULTURE AND POTENTIAL IMPROVEMENT THROUGH AISOLUTIONS USING A HOLISTIC APPROACH WITH MOS.

This book explores how artificial intelligence (AI) can revolutionize error culture and error management to enhance business efficiency and resilience. Anchored in established frameworks like ISO 31000 and COSO ERM, it demonstrates how principles from High Reliability Organizations (HROs) can be adapted to diverse industries. Through comprehensive research, including a unique 56-criteria checklist, it offers actionable strategies for identifying and mitigating risk management weaknesses. By leveraging AI's predictive and real-time capabilities, the book empowers leaders to adopt proactive approaches to organizational safety and sustainability while addressing ethical considerations and practical challenges. About the Author: With over 25 years of experience in senior roles across HR, Legal, and Compliance, Dr. Helmut Becker has implemented innovative strategies in industries such as finance, wholesale and retail, healthcare and machinery, and equipment. He holds multiple advanced degrees from renowned institutions, including a recent Ph.D. focusing on AI and error management. Dr. Becker is a recognized advocate for diversity and constructive error cultures, driving forward-thinking HR and organizational strategies. As a seasoned practitioner, he has delivered impactful lectures on HR strategies and error management at leading industry events.

ISBN: 9783658472436

Standard No.: 10.1007/978-3-658-47243-6doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: HF5548.2

Dewey Class. No.: 650.028563

Using artificial intelligence (AI) to minimize errors in business enterprise management
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245 1 0 $a Using artificial intelligence (AI) to minimize errors in business enterprise management $h [electronic resource] / $c by Helmut Becker.
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300 $a xxxiii, 188 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a ERROR THEORIES; ANALYSIS, CHANGE ANDDEVELOPMENT OF ORGANIZATIONAL CULTURE, ARTIFICIALINTELLIGENCE -- DEVELOPMENT AND APPLICATION OF ANINTEGRATED AUDIT APPROACH TO IDENTIFY THE WEAKNESSES OFTHE RISK MANAGEMENT SYSTEMS ISO 31000 AND COSO ERMFRAMEWORK IN CAPTURING THE ERROR CULTURE, WHICH HASTHE POTENTIAL FOR OPERATIONALIZATION THROUGH AI -- COMPARISON OF THE RISK MANAGEMENT SYSTEMSISO 31000:2018 AND COSO ERM FRAMEWORK WITH REGARD TOTHEIR ABILITY TO CAPTURE THE ERROR CULTURE -- INTERPRETATION OF RESULTS: EVALUATING ISO31000:2018 AND COSO ERM FRAMEWORKS IN CAPTURING ERRORCULTURE AND POTENTIAL IMPROVEMENT THROUGH AISOLUTIONS USING A HOLISTIC APPROACH WITH MOS.
520 $a This book explores how artificial intelligence (AI) can revolutionize error culture and error management to enhance business efficiency and resilience. Anchored in established frameworks like ISO 31000 and COSO ERM, it demonstrates how principles from High Reliability Organizations (HROs) can be adapted to diverse industries. Through comprehensive research, including a unique 56-criteria checklist, it offers actionable strategies for identifying and mitigating risk management weaknesses. By leveraging AI's predictive and real-time capabilities, the book empowers leaders to adopt proactive approaches to organizational safety and sustainability while addressing ethical considerations and practical challenges. About the Author: With over 25 years of experience in senior roles across HR, Legal, and Compliance, Dr. Helmut Becker has implemented innovative strategies in industries such as finance, wholesale and retail, healthcare and machinery, and equipment. He holds multiple advanced degrees from renowned institutions, including a recent Ph.D. focusing on AI and error management. Dr. Becker is a recognized advocate for diversity and constructive error cultures, driving forward-thinking HR and organizational strategies. As a seasoned practitioner, he has delivered impactful lectures on HR strategies and error management at leading industry events.
650 0 $a Artificial intelligence. $3 516317
650 0 $a Business $x Data processing. $3 527441
650 1 4 $a Management. $3 516664
650 2 4 $a Organization. $3 529074
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856 4 0 $u https://doi.org/10.1007/978-3-658-47243-6
950 $a Business and Management (SpringerNature-41169)