Gaining competitive advantage through artificial intelligence adoption

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Rui Gonçalves ◽  
Álvaro Dias ◽  
Renato Lopes Da Costa ◽  
Leandro Pereira ◽  
Teresa Bento ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Competitive Advantage

scholarly journals Artificial Intelligence Sebagai Penggerak Industri 4.0 dan Tantangannya Bagi Sektor Pemerintah dan Swasta

2019 ◽  
Vol 10 (1) ◽  
pp. 68
Author(s):  
Reza Yogaswara
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Competitive Advantage ◽  
Smart City ◽  
Chief Information Officer ◽  
Deep Learning Neural Network

Artificial Intelligence (AI) atau kecerdasan buatan menjadi penggerak revolusi industri 4.0 yang menjanjikan banyak kemudahan bagi sektor pemerintah maupun industri. Internet of Things (IoT) dan big data contohnya dimana AI dapat diimplementasikan, teknologi yang telah banyak diadopsi di era industri 4.0 ini mampu menghubungkan setiap perangkat, seseorang dapat mengotomatisasi semua perangkat tanpa harus berada di lokasi, lebih dari itu, saat ini telah banyak mesin yang dapat menginterprestasi suatu kondisi atau kejadian tertentu dengan bantuan AI, sebagaimana telah kamera cerdas pendeteksi kepadatan volume kendaraan di jalan raya menggunakan teknologi Deep Learning Neural Network, yang telah diimplementasikan pada beberapa Pemerintah Daerah Kabupaten dan Kota dalam mendukung program Smart City yang telah dicanangkan. Pada sektor industri, banyak juga dari mereka yang telah mengotomatisasi mesin produksi dan manufaktur menggunakan robot dan Artificial Intelligence, sehingga Industri 4.0 akan meningkatkan daya saing melalui perangkat cerdas, setiap entitas yang mampu menguasai teknologi ini disitulah keunggulan kompetitifnya (competitive advantage). Namun ditengah perkembangan industri 4.0 yang cukup masif pemerintah harus bergerak cepat dalam mengadopsi platform ini, jika tidak, mereka akan menurunkan efisiensi proses bisnis untuk menjaga stabilitas layanan publik. Oleh sebab itu diperlukan keilmuan dan pemahaman yang benar bagi pemerintah dalam menghadapai era Industri 4.0, dimana Chief Information Officer (CIO) dapat mengambil peranan penting dalam memberikan dukungan yang didasari atas keilmuan mereka terkait tren teknologi industri 4.0, khususnya AI yang telah banyak diadopsi di berbagai sektor.

scholarly journals Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

2021 ◽  
Vol 17 (33) ◽  
pp. 47-63
Author(s):  
Isabel Cristina Arango-Palacio
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Competitive Advantage ◽  
Sources Of Information ◽  
Intelligent Software ◽  
Searching Method

La inteligencia artificial ofrece grandes oportunidades para la cadena de suministro, siendo esto una ventaja competitiva para el mercado cambiante de hoy en día. Este artículo tiene como objetivo identificar los impactos y oportunidades que puede ofrecer el software con inteligencia artificial para facilitar la operación y mejorar el desempeño de la cadena de suministro en el sector bananero de Colombia. La metodología de trabajo consta de seis pasos en donde se obtuvo un total de 72 investigaciones. Las fuentes de información fueron cuatro bases de datos. Como conclusión principal, la cadena de suministro del sector bananero tiene todo lo necesario para que se implementen soluciones basadas en software inteligente con el fin de lograr una adaptación, flexibilidad y sensibilidad al contexto y dominio de ejecución. Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain.

Organizational Data Mining (ODM)

2011 ◽  
pp. 1-8
Author(s):  
Hamid R. Nemati ◽  
Christopher D. Barko
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Competitive Advantage ◽  
Current Status ◽  
Decision Making Process ◽  
Actionable Knowledge ◽  
The Core ◽  
Mining Tools

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage (Nemati & Barko, 2001). The fundamentals of ODM can be categorized into three fields: Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the core differentiator between ODM and data mining. We take a brief look at the current status of ODM research and how a sample of organizations is benefiting. Next we examine the evolution of ODM and conclude our chapter by contemplating its challenging yet opportunistic future.

scholarly journals Sztuczna inteligencja w redakcji – o zmianach technologicznych w dziennikarstwie

2021 ◽  
pp. 171-183
Author(s):  
Jakub Czopek ◽  
Keyword(s):  
Artificial Intelligence ◽  
Competitive Advantage ◽  
Computer Algorithms ◽  
Technological Changes ◽  
Media Messages ◽  
Advanced Applications

Editorial offices of all types of media must constantly adapt to the increasing processes of convergence and digitization of media messages. One of the elements that can help them gain a competitive advantage is the use of technologically advanced applications and computer algorithms that not only accelerate the journalist's work, but in many cases can even replace them. The main goal of the article is to familiarize the reader with the most important technological changes related to the use of artificial intelligence programs, which in recent years have started to increasingly affect the work of journalists.

Organizational Data Mining (ODM)

2008 ◽  
pp. 2289-2295 ◽  
Author(s):  
Hamid R. Nemati ◽  
Christopher D. Barko
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Competitive Advantage ◽  
Current Status ◽  
Decision Making Process ◽  
Actionable Knowledge ◽  
The Core ◽  
Mining Tools

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage (Nemati & Barko, 2001). The fundamentals of ODM can be categorized into three fields: Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the core differentiator between ODM and data mining. We take a brief look at the current status of ODM research and how a sample of organizations is benefiting. Next we examine the evolution of ODM and conclude our chapter by contemplating its challenging yet opportunistic future.

Artificial Intelligence as a Competitive Advantage in the Manufacturing Area

2019 ◽  
pp. 171-180
Author(s):  
Juvenal Mendoza Valencia ◽  
Juan José Hurtado Moreno ◽  
Felipe de Jesús Nieto Sánchez
Keyword(s):  
Artificial Intelligence ◽  
Competitive Advantage

Selecting International Freight Forwarders: An Expert Systems Application

1993 ◽  
Vol 23 (3) ◽  
pp. 11-21 ◽  
Author(s):  
Aysegül Özsomer ◽  
Michel Mitri ◽  
S. Tamer Cavusgil
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Competitive Advantage ◽  
Broad Spectrum ◽  
International Marketing ◽  
Decision Makers ◽  
Third Party ◽  
Foreign Markets ◽  
Freight Forwarder ◽  
Selection Of

The recent changes in the international forwarding environment have witnessed the emergence of “new forms” of forwarders incorporating a broad spectrum of services under one roof. Such total logistics companies are becoming a critical third party in obtaining a competitive advantage in foreign markets. Hence, the evaluation and selection of an international freight forwarder is no longer a simple operational decision but a strategic one. Presents and explains an expert systems tool to assist decision makers in selecting the freight forwarder which fits their needs best. The system, called FREIGHT, brings together international marketing, logistics and artificial intelligence knowledge.

scholarly journals Human Creativity and Artificial Intelligence (AI): Two Distinct Requirements for Sustainable Competitive Advantage

2019 ◽  
Vol 2 (2) ◽  
pp. 44-49
Author(s):  
Nima S. Salami
Keyword(s):  
Artificial Intelligence ◽  
Competitive Advantage ◽  
Sustainable Competitive Advantage ◽  
Human Creativity ◽  
The Future

Increasing competition among industries requires them to be intelligent in order to make their best decisions and remain competitive in the market. Nowadays both human and artificial intelligence have made many contributions to this purpose and have helped businesses tremendously to achieve their goals. This paper explains why industries need to realize that intelligence and creativity are two distinct disciplines, and each needs to be treated differently in combination with artificial intelligence (AI) in order to maintain a sustainable competitive advantage in the future.

Role of machine learning in changing social and business eco-system – a qualitative study to explore the factors contributing to competitive advantage during COVID pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hishan S. Sanil ◽  
Deepmala Singh ◽  
K. Bhavana Raj ◽  
Somya Choubey ◽  
Narinder Kumar Kumar Bhasin ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Growth Rate ◽  
Competitive Advantage ◽  
Computer Technology ◽  
Small Businesses ◽  
Competitive Advantages ◽  
Business Analytics ◽  
Content Type ◽  
The World

Purpose “Machine learning (ML)” in business aids in increasing company scalability and boosting company operations for businesses all over the world. “Artificial intelligence (AI)” technologies and several “ML” algorithms have grown in prominence in the business analytics sector. In the era of a huge quantum of data being generated by the virtue of the integration of the various software with the business operations, the relevance of “ML” is continuously increasing. As a result, companies may now profit from knowing how companies may use “ML” and incorporating it into their own operations. “ML” derives useful results from the data to address very dynamic and difficult social and business problems. ML helps in establishing a system that learns automatically and produces results in less time and effort, allowing machines to discover. ML is developing at a breakneck pace, fuelled mostly by new computer technology to competitive advantages during the COVID pandemic. Design/methodology/approach For firms all around the world, “ML” in business aids in expanding scalability and boosting operations. In the field of business analytics, artificial intelligence (AI) and machine learning (ML) algorithms have become increasingly popular. The importance of “ML” is growing in an era when a massive amount of data is generated as a result of the integration of various applications with company activities. As a result, businesses can now benefit from understanding how other businesses are using “ML” and adopting it into their own operations. In order to handle very dynamic and demanding societal and business challenges, machine learning (ML) extracts valuable results from data. Machine learning (ML) aids in the development of a system that learns automatically and generates outcomes with less time and effort, allowing machines to discover. ML is progressing at a dizzying pace, fueled primarily by new computer technology and used to gain competitive advantages during the COVID pandemic. Findings According to a new study published by the Accenture Institute for High Performance, “AI” might double yearly economic growth rates in several wealthy nations by 2035. With broad AI deployment, the yearly growth rate in the USA increased from 2.6% to 4.6%, resulting in an extra $8.3tn. In the UK, AI may contribute $814bn to the economy, raising the yearly growth rate from 2.5% to 3.9%. The authors are already in a business period when huge technological development is assisting us in addressing a variety of difficulties to achieve maximum development. AI technology has enormous developmental consequences. In addition, big data analytics is helping to make AI more enterprise ready. Future developments in “ML” cannot be understated. Machines will very certainly eventually be smarter than humans in practically every way. Originality/value The introduction of AI into the market has enabled small businesses to use tried-and-true strategies for achieving greater business objectives. AI is continually offering a competitive advantage to start-ups, whilst large corporations provide a platform for building novel solutions. AI has become an integral component of reality, from functioning as a robot in a production unit to self-driving automobiles and voice activated resources in complex medical procedures. As a consequence, solving the difficulties highlighted below and finding out how to collaborate with robots will be a constant problem for the human species (Sujaya and Bhaskar, 2021).

Economic AI Literacy

2021 ◽  
pp. 135-152
Author(s):  
Dirk Nicolas Wagner
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Competitive Advantage ◽  
Business Models ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Information Goods ◽  
Economic Agents ◽  
Business Transformation ◽  
Economic Reasoning

This chapter introduces the concept of economic AI literacy as a source of competitive advantage in a world where artificial intelligence (AI) complements and transforms business models. The purpose of economic AI literacy is to allow for enhanced strategic decision making in firms that either offer and/or use AI. Data and information goods, economics of networks, and economic agents in artificially intelligent firms are introduced as basic elements of economic AI literacy. To illustrate application, the case of TensorFlow and related cases are presented. The discussion highlights the strategic relevance of economic reasoning in the light of the expected effects of AI on business transformation.

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