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Artificial Intelligence in Business Decision Making

Artificial Intelligence in Business Decision Making
Author: Ms. Madhavi
Publisher: Infotech
Total Pages: 0
Release: 2022-12-29
Genre: Business & Economics
ISBN: 9782181713856
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AI is described as human-produced structured organized knowledge formed with help of machines. Human insight techniques such as learning, thinking, and self-remedy are used in the production of AIs. Artificial intelligence is the future of business. Artificial intelligence paves the way for certain decision-making and saves time and lots of money also. Artificial intelligence system has the ability to gather data, forecasting, and trend analysis. The motive of the thesis is to highlight improving agricultural productivity with the introduction of artificial intelligence in the agriculture sector. Artificial intelligence enhances the economy and increases the productivity of the organization within a very short period of time. newlineDecisions are an important part of business management. Big data and large files along with data mining are considered important in decision-making in business. The safety of data is another important task. Along with these terms, the replacement of executives is the parameter on which the thesis is based. Ai and humans are very near to each other. One uses past data and the latter uses experience to make decisions. Data is a treasure to AI as it only makes it able to take decisions. All these have been used as parameters for this study. newline study further discusses the history of AI in detail. AI can be achieved in many ways. Machine learning, natural language processing, vision, robotics, etc. are some of the ways through which AI can be achieved and these have been disused in the study. AI has always been seen as a threat to human jobs. With the pace at which AI is replacing human, it becomes scary for humans to believe in AI. However manmade intelligence is found to take better and faster decisions. Artificial intelligence makes humans superhuman. There are too many differences between artificial intelligence and human which makes it difficult in replacing each other at a job. Research also describes the role of AI in money laundering. Money laundering is a serious issue pertaining to every business.

Intelligent Decision Making: An AI-Based Approach

Intelligent Decision Making: An AI-Based Approach
Author: Gloria Phillips-Wren
Publisher: Springer
Total Pages: 414
Release: 2008-02-27
Genre: Technology & Engineering
ISBN: 3540768297
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Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.

Connected Business

Connected Business
Author: Oliver Gassmann
Publisher: Springer Nature
Total Pages: 415
Release: 2021-08-11
Genre: Business & Economics
ISBN: 303076897X
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How do you develop business in a world certain to be dominated by Internet of Things, Artificial Intelligence, and the Economy of Things?This book brings together leading scholars from academia, established practitioners, and thought-leading consultants who analyse and provide guidance to answer this question. Case studies, checklists, success factors, help readers get a grip on this fast-paced development. At the same time, the authors do not shy away from addressing the hurdles and barriers to implementation. This book provides an essential food-for-thought for leaders and managers, both visionary and pragmatic, who are faced with the responsibility of steering their business through these challenging, yet exciting, times.

The Economics of Artificial Intelligence

The Economics of Artificial Intelligence
Author: Ajay Agrawal
Publisher: University of Chicago Press
Total Pages: 172
Release: 2024-03-05
Genre: Business & Economics
ISBN: 0226833127
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A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Artificial Intelligence in Business Decision Making

Artificial Intelligence in Business Decision Making
Author: Miss Madhavi
Publisher:
Total Pages: 0
Release: 2020
Genre:
ISBN:
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Artificial intelligence has become a way of life for most of the person in the invisible form. Accord of worldometer.info the total population of India is 1,374,603,661 as of Friday, February 7, 2020. While the users and knowers of AI are very low in India. Accord of emerge.com AI is used in different sectors of India as Health Sector, Agriculture Sector and education Sector. And experts said the Top AI application in India in Automation in business process, Chatboat, Natural Language process (NLP) and image Recognition. According to pheonixresearch.com southern region of India captured the major pie for the using of artificial Intelligence. We should do some activity for increasing the users of AI in Business sector for making decisions. The purpose of this paper is to enhance the awareness of Artificial intelligence in trade premises for making decisions. The study provides the various factors for supporting the study of AI.

Decision Intelligence Analytics and the Implementation of Strategic Business Management

Decision Intelligence Analytics and the Implementation of Strategic Business Management
Author: P. Mary Jeyanthi
Publisher: Springer Nature
Total Pages: 236
Release: 2022-01-01
Genre: Technology & Engineering
ISBN: 3030827631
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This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.

Artificial Intelligence and Decision-Making Applications in a Business Context. Chances and Risks

Artificial Intelligence and Decision-Making Applications in a Business Context. Chances and Risks
Author:
Publisher: GRIN Verlag
Total Pages: 92
Release: 2020-12-21
Genre: Business & Economics
ISBN: 3346317285
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Bachelor Thesis from the year 2020 in the subject Business economics - Business Management, Corporate Governance, grade: 1,1, University Pontificia Comillas Madrid, language: English, abstract: This thesis is concerned with what AI is capable of in decision-making when involved in organizational decision-making processes or embedded in offered products that per-form decisions. It is also concerned with what is lost and what is gained through its use and which risks businesses face when applying it. It adds value to previous work conducted on challenges and risks by explaining these from a business perspective focusing on the economic implications for organizations. The resulting overview on chances and risks can serve organizations interested in AI investments to augment or automate decision-making in understanding the risk situation and potentials in this field. In the first chapter AI is introduced in a comprehensible way for non-computer scientists and its relevance for business is outlined. Subsequently, decision processes and how humans and AI tackle them are explained which provides a foundation to under-stand respective strengths and limitations of humans and AI in decision-making. The third chapter explains how AI can be applied in decision-making in businesses processes and products that perform decisions providing benchmark examples. Autonomous driving and recruiting are presented as examples for decision automation and decision augmentation respectively on the basis of which benefits and challenges will be explained. Focusing on these examples aims at making the possible associated effects of using AI in decision-making processes more tangible and understandable for business professionals.

AI Meets BI

AI Meets BI
Author: Lakshman Bulusu
Publisher: CRC Press
Total Pages: 0
Release: 2020-11-03
Genre: Computers
ISBN: 1000281957
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With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI.

Artificial Intelligence in Industrial Decision Making, Control and Automation

Artificial Intelligence in Industrial Decision Making, Control and Automation
Author: S.G. Tzafestas
Publisher: Springer Science & Business Media
Total Pages: 778
Release: 2012-12-06
Genre: Computers
ISBN: 9401103054
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This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.

Decision Intelligence For Dummies

Decision Intelligence For Dummies
Author: Pamela Baker
Publisher: John Wiley & Sons
Total Pages: 323
Release: 2022-02-08
Genre: Computers
ISBN: 1119824842
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Learn to use, and not be used by, data to make more insightful decisions The availability of data and various forms of AI unlock countless possibilities for business decision makers. But what do you do when you feel pressured to cede your position in the decision-making process altogether? Decision Intelligence For Dummies pumps the brakes on the growing trend to take human beings out of the decision loop and walks you through the best way to make data-informed but human-driven decisions. The book shows you how to achieve maximum flexibility by using every available resource, and not just raw data, to make the most insightful decisions possible. In this timely book, you’ll learn to: Make data a means to an end, rather than an end in itself, by expanding your decision-making inquiries Find a new path to solid decisions that includes, but isn’t dominated, by quantitative data Measure the results of your new framework to prove its effectiveness and efficiency and expand it to a whole team or company Perfect for business leaders in technology and finance, Decision Intelligence For Dummies is ideal for anyone who recognizes that data is not the only powerful tool in your decision-making toolbox. This book shows you how to be guided, and not ruled, by the data.