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You read the following paper and write the review in attached review format.    Use X in review format.Overall comments and changes that MUST be made before publication:  Please write the detailed comments on paper and review here (say in 5 – 10 bullet points) Suggestions which would improve the quality of the paper but are NOT essential   for publication: Please write the suggestions to improve the paper here (say in 2 or 3 bullet points) Digital Transformation and Its Opportunities for Sustainable Manufacturing Abstract. This paper explores the impacts of digital technologies on supply chains and coordination, the manufacturing process, energy conservation, efficiency, and environmental conservation. Digital transformation has led to the popularization of sustainable manufacturing, which entails creating sustainable products that promote social, economic, and environmental sustainability. Digital transformation has boosted sustainability in production and manufacturing in a variety of ways. These ways include increasing cross-border communication through the internet, decentralizing supply chains, Internet of Things (IoT) solutions, artificial intelligence, machine learning, big data analytics in predictive analysis, robotics, horizontal and vertical integration of businesses, efficient management, and various other ways. The findings of the paper indicate that digital transformation has changed manufacturing in various ways. Aspects like cloud computing, vertical and horizontal integration, communication, and the internet have contributed to sustainable manufacturing by decentralizing supply chains. In addition, some digital transformation tools such as predictive analysis and big data analytics have helped optimize sustainable manufacturing by reducing overproduction or underproduction through predicting customer demands. Keywords Internet of Things, Digital Transformation, Machine Learning, sustainable organization. Introduction Background Traditionally, human civilizations used technology to solve many problems. Since the Industrial Revolution, environmental degradation resulting from wastage and poor manufacturing problems has become a significant issue. As a result, the world has be- gun a global campaign on promoting sustainability in virtually all aspects of civilization. One of the areas that need to embrace sustainability the most is the industrial processes of manufacturing. Digital transformation not only holds the promise of promoting higher levels of sustainability in manufacturing but has already begun changing some manufacturing processes to make them more sustainable. In recent years, research on digital transformation has increased exponentially. Many scholars have examined the various contributions digital transformation has had on multiple sectors [1,3, 11,12]. The paper summarizes different scholarly papers that have explored the link between digital transformation opportunities and their impact on sustainable manufacturing. The table below outlines the total number of research articles published on digital 2 transformation in the 21st century. Fig. 1. Table showing the number of scholarly articles on digital transformation in the manufacturing sector. This study evaluates the role that digital transformation plays in creating opportunities that can promote sustainable manufacturing. It explores each technological advancement adopted so far and evaluates its contribution to promoting sustainable manufacturing. Although not all technological advancements have positively affected manufacturing, various manufacturers have adopted big data analytics, machine learning, artificial intelligence, the internet, and Blockchain to streamline their operations. In addition, many manufacturers have adopted these technological advancements to promote sustainable production. Sustainable manufacturing focuses on several aspects: environmental preservation, energy conservation, reduced waste, and sustainable consumption of natural resources. Most scholars refer to the digital transformation in the manufacturing sector as industry 4.0 since these technologies conceived the fourth industrial revolution. The paper also explores governments and the private sectors role in promoting the fourth industrial revolution. Sustainable Manufacturing Machado et al. [7] define sustainable manufacturing as integrating systems and processes to produce high-quality services and products while being more sustainable in consuming products and reducing the amount of wastage that further contributes to environmental degradation. Sustainable manufacturing yields many positive attributes for manufacturers globally through a variety of added benefits, including cost reduction due to increased efficiency and compliance with existing regulatory policies, access to new markets, improved brand perception and reputation, and reduced labor turnover. This is partly due to the added benefit of artificial intelligence reducing the workload and promoting a long-term business focus, promoting longterm organizational growth and progress [7]. In the age of globalization, sustainable manufacturing offers organizations worldwide the competitive edge due to increased competition. Most consumers are sustainable consumers who solely purchase products that companies produce ethically. Several inventions make sustainable manufacturing possible. These inventions include autonomous robots, simulations,3 systems integration, Industrial IoT (Internet of Things), cloud computing, cybersecurity, augmented reality, and big data and analytics. In short, digitizing the manufacturing process is the archetype of the fourth industrial revolution, creating a situation where every piece of data collected remains instrumental when making any decision. Policies Promoting Sustainable Manufacturing International bodies and policymakers such as the United Nations have been at the forefront of advocating for increased sustainability in producing and consuming products. In 2015, the United Nations outlined 17 sustainability goals known as the SDG (sustainable development goals). Another policy developed to promote sustainability to avert a political disaster was Agenda 21, which covers all the sustainable goals set out by the United Nations [9]. The 9th and the 12th sustainable development goals mainly focus on innovation to promote sustainable manufacturing. The 9th goal (Industry, Innovation, and infrastructure) plays a vital role in promoting innovation and advancement in technology in the manufacturing sector, while the 12th goal (Responsible Consumption and Production) is primarily concerned with sustainable production and consumption. The purpose of these SDGs is to reduce waste and prevent a climate disaster that is looming due to the high influx of carbon dioxide released into the air. Despite the high level of incompatibility of manufacturing processes with environmental concerns, these systems play an instrumental role in social structures by promoting peoples livelihood by making their lives more accessible and providing them with jobs and employment opportunities that keep the economy afloat. With the understanding of the potential impacts of climate change on the human population, manufacturers have employed a three-dimensional consideration approach. They set out economic, environmental, and social goals that will promote the overall advancement of society [9]. Sustainable manufacturing has become a common theme in virtually all industries. Sustainable manufacturing has adopted several dimensions, including manufacturing sustainability by reducing waste, material science, environmental science, and energy science, whose primary goal is to reduce carbon emissions into the atmosphere [3]. Digital transformation, on the other hand, is a tool that most manufacturers are currently using to reduce emissions and wastage. After understanding the impacts of industrialization, most governments, policymakers, and even private-sector veterans thought there was no possible way to curb the environmental effects of carbon dioxide without severely affecting the rest of the population [3]. However, digital transformation has indicated the potential benefits of using the technological advances made in communications and information technology to monitor energy use, wastage and promote efficient production methods that reduce pollution. Furthermore, the fourth industrial revolution is instrumental in reducing carbon dioxide emissions by promoting efficiency and developing better energy sources such as solar and wind to use coal to produce electricity for the industries [1]. With the advent of these technologies, policymakers have thus deemed it necessary to regulate manufacturing processes and ensure that they promote higher levels of environmental sustainability throughout the world. 4 Nevertheless, Blunck and Werthmann [1] contend that inventors developed these technologies to reduce the cost of production in this overly competitive global environment but have also proven helpful in promoting sustainability. This concept, therefore, illustrates that digital transformation might have arisen out of the need for manufacturers to promote more efficiency and higher profitability as opposed to the intentional promotion of a sustainable workplace. However, it has also given various policymakers a platform to institute mandatory sustainability measures for all manufacturers. Nevertheless, the technologies developed in the fourth industrial revolution will pro- mote improved sustainable manufacturing, leading to higher degrees of profitability while simultaneously reducing the environmental impact that industries cause. In addition, the potential rearranging of value chains, changing and emerging business models, and other digital technologies will significantly reduce the carbon footprint and promote social sustainability. Digital transformation applications Digital Transformation in Manufacturing Digital transformation refers to cultural, organizational, and operational change using digital technologies, processes, and competencies. In short, digital transformation has taken place through a simple process, which mainly entails developing, improving, and introducing new technological advancements that can promote higher levels of optimization in organizational productivity. These digital technologies ranging from big data analytics, smart or intelligent machines, rearranging supply chains, internet of things, communication integration, and similar factors. Digital transformation in the manufacturing industry has replaced mechanized industrial plants with digitized and computerized plants, promoting ubiquitous optimization of companies production processes, eliminating inefficiencies and providing a centralized operation that relies heavily on data management. Different digital transformation technologies have significantly contributed to the overall improvement and advancement of manufacturing. Most digital technologies rely mainly on data collection and analytics processes that improve organizational performance. Digital Transformation of the Supply Chains Big data has been the pivotal aspect of the digital transformation, making it possible to develop various other inventions in this field. Data analysis and collection play an instrumental role in making virtually all decisions concerning manufacturing and other areas where companies use these technologies, such as finance and machine learning. The high level of digitization has made it possible to develop an intelligent, connected, and decentralized production process, reducing the amount of money spent in centralized production models [7]. Data collection and analysis have also contributed to developing alternative supply chain models that challenge the traditionally used centralized system, making it possible for companies to reduce the amount of fuel used in transporting goods cross-country or shipping them to global centers. In the contemporary industrial setting, companies will open branches in Asian countries to produce goods sold in Asia, despite the manufacturer being an American company. 5 This process makes it easier to transport goods produced in these regions to their immediate customers. Without the internet, this level of decentralization would not have been possible. Therefore, a significant upside of data analytics as part of the digital transformation model entails decentralizing supply chains and logistical problem-solving. Without the rise of the internet and the various technological advancements made possible by the digital transformation era, the modification of supply chains to reduce the distances of transporting goods would have been impossible. Despite the added benefits that digitization has had on altering the supply chains to promote sustainable production in various fields, a significant digitization process continually makes many business models redundant [4]. Opportunities in Vertical and Horizontal Integration Horizontal and vertical integration, though rarely explored, have immensely contributed to sustainable manufacturing. Stock and Seliger [12] propose that the evolution of sustainable manufacturing relies heavily on the increase in companies interconnection and communication speed. Horizontal integration refers to how companies collectively exchange information using various ICT infrastructural developments. In contrast, vertical integration refers to the ease of communication between the top-level management and the subordinates in various geographical locations. Vertical integration has made it possible for various branches and departments of a geographically scattered company to remain in touch and communicate in real-time. Integration has made it increasingly easy for companies to source products for themselves by developing branches near the sources of the raw materials. It has made it possible to outsource some manufacturing processes that the company does not perform sustainably to an organization that mainly focuses on such processes. The intelligent cross-linking of manufacturers with suppliers and their workforce is a critical component that has promoted sustainable manufacturing by increasing production efficiency, reducing worker turnover, and improving the shelflife of products through timely production processes. The speed in the exchange of data has incredibly transformed the process of manufacturing. The Promise of Blockchain Although the industry has made incredible strides in improving this field as it currently is, there are still countless numerous opportunities that digital transformation has for promoting sustainable manufacturing. One of the recent inventions in digital transformation is the Blockchain used in the development of cryptocurrencies. Although the adoption of Blockchain in promoting sustainable workplaces is still in its hype phase, very few companies have wholly embraced the invention to promote sustainable manufacturing [5]. Blockchain refers to a digital ledger or a database in which the files recorded in the database are unchangeable once published. It has become an incredible tool for book-keeping and for managing various supply chains. Notably, Blockchain is applicable in the manufacturing process in the elimination of many unnecessary processes. For instance, aspects such as warehousing, inventory management, the monitoring of goods in transit, and the quantities of products dispatched, can rely on Blockchain to prevent modifying these figures, thereby 6 promoting transparency. Likewise, blockchains are admissible in recording all products purchased by the manufacturer and the quantities used in each phase of the production process, thereby allowing the organization to make some radical changes to the production process to make it more effective. Thus, this record-keeping tool will have some instrumental contributions to promoting sustainable manufacturing altogether. Cloud Computing and Predictive Analysis Collecting data throughout the manufacturing process is crucial in promoting sustainability by identifying areas within the production process where the company is ineffective and implementing changes to increase this efficiency. Data collection and storage have also been instrumental in monitoring organizational progress in becoming more sustainable. In this regard, cloud computing has been incredibly instrumental in promoting sustainability in the manufacturing process. Since sustainability is a long-term strategy, monitoring and measuring the organizations progress critically impacts the organizations decisions to arrive at the desired outcomes. In the past, companies commonly responded to customer demands after the customers had expressed them. However, in the contemporary business setting, customers expect the companies to implicitly react to their demands before they have realized them themselves. This change in customer demands calls for a predictive model that will expect companies to predetermine the changes in customer trends beforehand and respond to them before the reaction of the customers demanding a radical change in these demand patterns [4]. This degree of predictive analysis is only possible due to data analysis and collection. The availability of data online and its customers data has made it possible for companies to predict their customers demands before expressing them. One brilliant example was when Target started sending coupons for baby products to a household where a teen daughter was pregnant long before disclosing this fact to her parents. The company used the cookie data on the girls browsing history to predict that she was pregnant. When the parents sued the company for sending them baby product coupons, yet they were not pregnant, the parents realized that their daughter had been pregnant (Hill, 2012). This illustration is a perfect example of how companies use artificial intelligence to predict their customers needs before explicitly expressing their needs. The amount of data that companies collect on customers by building individual profiles for their customers and using data analytics to predict their purchase patterns based on their browsing history has been another pivotal component of sustainable manufacturing. It allows companies to meet the demand for some of their products. The concept of predictive analysis of customer needs is a critical component of intelligent manufacturing, allowing companies to be ahead of the demand curve. The digital supply chain, which entails monitoring goods in transit, inventory, demand curves, and other similar aspects, has made it possible for manufacturers to focus on producing products and services that meet the demand without having a surplus in the production process. For instance, manufacturers can7 predict the demand for their products by using the digital supply chain, preventing and over-production, unsustainable. The ability to make predictive models of the demand of the products promotes sustainability by reducing waste [8]. Though most people concentrate on complex technologies when evaluating sustainable production, such as robotics and machine learning, few people understand that communication and the collection of digital information such as the demand and supply of products are the backbones of sustainable manufacturing. Smart Manufacturing and Artificial Intelligence Optimizing a companys production capacity depends extensively on Smart Manufacturing, which heavily relies on artificial intelligence. Artificial intelligence relies on extensive data collection and analysis to make decisions beforehand, which are more effective than human managers decisions based on their intuition [10]. Unlike humans, artificially intelligent manufacturing software makes decisions based on data collected, thereby increasing the accuracy of the decisions that they eventually make. These intelligent models promote the production process by ensuring that companies have minimal waste resulting from delayed production or overproduction of products that customers do not necessarily need. Likewise, artificial intelligence has also been instrumental in various other areas and predictive analysis of demand and supply trends. Organizations use artificial intelligence to tweak manufacturing processes and increase their efficiency. Sharma, Jabbour, and Jabbour [11] contend that companies rely on artificial intelligence software to map out areas where organizations waste the most resources. Promoting efficiency depends heavily on the wise use of resources throughout the production model. Companies use simulations to outline the manufacturing inefficiencies in organizations by indicating areas where the process wastes the most re- sources. For instance, some institutions use artificial intelligence to identify potential materials for recycling, thereby saving the costs of acquiring more material that is not necessary. Such programs have also identified areas that consume the most energy, deeming it necessary for the companies to evaluate ways to save electricity or substitute the electrical sources used in supplying this part of the production process with renewable energy sources (see [11]). A significant upside of using artificial intelligence in manufacturing is its broad applicability since developers create each AI program to accomplish a specific task. AI software has had a critical impact on reducing redundancy in the organization, thereby streamlining the production process to promote sustainability in the manufacturing process [6]. The evolution of artificial intelligence promises more advances in the field that will streamline production processes extensively. Energy Sustainability One of the fields that require the implementation of the most sustainability-oriented strategies is energy conservation. As the world becomes exceptionally materialistic, the amount of energy that a single household uses has exponentially increased compared to the energy consumed before the Industrial Revolution in the 19th century. Manufacturing contributes to increased energy sustainability by controlling energy consumption and relying on renewable energy sources. The manufacturing of solar panels, wind turbines, hydroelectric turbines, and nuclear plants is one solution that 8 manufacturing has introduced to promote energy sustainability. However, the digital transformation of manufacturers plants that do not directly produce these products has also contributed immensely to increased energy sustainability. Notably, through using renewable energy sources to power their plants, companies have contributed to energy sustainability immensely due to the individual efforts of the private sector or through compliance with the mandatory energy restrictions that governments around the world have imposed on organizations. For instance, the imposition of carbon credits is one of the simple methods governments regulate manufacturers energy sources, leading them to reduce their carbon footprints as much as possible despite being reluctant to do so. Energy conservation has also become a focal point in most manufacturing plants as energy costs rise due to the high demand for energy from virtually all aspects of our civilization. Companies relying on their internally built solar fields and windmills to power their plants have realized the urgent need to be self-sustaining in terms of energy, as the energy costs throughout the world increase exponentially. The regulation of fossil fuels to power several manufacturing plants have also adversely affected these firms overall standing from a financial standpoint, driving them to rely on digital technologies to solve this crisis. The use of artificial intelligence, for example, has contributed to increased energy conservation. Automated plants can shut themselves off whenever they are not functioning, leading to the conservation of energy. Likewise, artificially intelligent machines are more effective than traditional manual machines, significantly reducing the energy used in producing the same amount of goods. Nevertheless, from another standpoint, the overreliance on robotics and artificially intelligent machines increase energy consumption. Companies outsource some of the jobs traditionally done by people to intelligent machines, which require electricity to run. Therefore, the use of artificial intelligence in manufacturing is a double-edged sword [5]. It promotes sustainable manufacturing and efficiency in the production process and consumes much energy, although the existing energy reserves cannot support its current world. As the world becomes increasingly digitized and filled with intelligent technology, the concept of sustainable manufacturing will need to focus on reducing the energy consumed extensively. Radical changes to the manufacturing process are necessary to promote energy sustainability as more organizations emphasize manufacturing sustainability. Contributions of digital transformation to sustainable manufacturing and challenges The auto industry uses IoT to continually maintain and monitor the quality of their products, allowing these manufacturers to prolong the lifecycles of these products and their attractiveness to customers. A perfect example of this case is Tesla Motors, which enables car owners to update their vehicles, improving the speed, performance, and features the car contains. Finally, a meaningful way digital transformation has led to increased sustainability in manufacturing is through logistics management. Logistics management entails the management of the fleets owned by a company as a way to reduce the emissions produced by their fleets, reduce the cases of theft in transit, and 9 decentralize the supply chain as a way to curb the amount of time and money spent on moving goods from one place to another. In addition, decentralized supply chains have led to establishing new plants near the areas where the products are in demand, reducing the distance these products travel to reach their customers. Through these five modifications to the production process, organizations have improved their sustainability and simultaneously reduced the amount of money spent in producing products while taming the wastage and pollution that factories cause. However, not all manufacturers have invested in the industry 4.0 advancements which have been highly effective in promoting sustainable manufacturing. Some manufacturers will have little if any interest in sustainable manufacturing if they make a profit. The high cost of investment required to adopt these technologies into all manufacturing units has been a critical determinant that has driven many potential investors to shy away from adopting digital transformation tools or embracing sustainable manufacturing processes in their organizations [6]. Other companies shy away from these technological advancements because they need them to completely replace all their traditional manual equipment and replace it with modern plant equipment, which can be extremely expensive. With this understanding, the goal of attaining sustainable manufacturing processes from all producers worldwide seems like a far-fetched dream for most companies. Nevertheless, change is inevitable, and the manufacturers who fail to embrace these changes will be out of business soon. Because all governments are currently working towards sustainability in virtually all sectors, the most probable outcome is that sustainable manufacturing will be mandatory. Notably, some of the implemented policies entail curbing carbon emissions and the wide use of fossil fuels in various companies [9]. Despite the wide use of digitized information, digital transformation inventions have little impact on the direct re duction of carbon emissions. One of the exceptionally effective strategies is using a digital-focused supply chain to reduce the carbon emissions from supply fleets from the manufacturer by reducing the distance of transporting goods. The rearranging of the supply chain reduces carbon emissions from vehicles but does not limit the carbon produced during manufacturing. Therefore, despite being highly effective in promoting sustainability within the company with a high degree of efficacy, these technologies have impending limitations to offering solutions for environmental sustainability, which is currently the most pressing issue. The graph below shows a simple breakdown of the present and future investments that the various manufacturers worldwide will invest in in the future. More companies have started the digital transformation of their plants to promote higher levels of sustainability. In the future, all industries will be fully digitized and dependent on digital transformation. 10 Fig 2: Table showing the investment projections on various types of digital transformation tools from 2016 to 2028. Conclusions The digital transformation which has resulted from the increase and improvement of data management technologies has led to the radical modification of the manufacturing process, with the goal being to reduce waste and promote environmental sustainability. Sustainable manufacturing encompasses social, environmental, and economic sustainability. The manufacturing process will reduce environmental degradation, improve the lives of communities, and simultaneously promote the economic progress of the manufacturers through improved efficiency. Digital technologies have promoted sustainable manufacturing in a variety of ways. Technologies such as machine learning, cloud computing, artificial intelligence, IoT, extensive data analysis, and logistical management have brought about radical changes to the manufacturing process while simultaneously improving the overall financial standing of the existing companies by improving efficiency. However, digital transformation contributes to job losses, with artificially intelligent software and machines replacing people. At the same time, companies have also used these digital technologies to reduce energy consumption by de- centralizing their supply chains and using renewable energy sources to power most plants. In summary, digital transformation has increased the sustainability of manufacturing in various ways but still has a long way to promote the overall sustainability of the environment and existing communities. Furthermore, the high costs of installing industry 4.0 plants that can encourage more sustainability are still critical challenges that deter many manufacturers from adopting sustainable manufacturing plants. Nevertheless, the involvement of government bodies in advocating for sustainability has made it necessary for various manufacturers throughout the world to embrace this new manufacturing model for their overall success and compliance with existing regulatory policies. References [ 1 ] Blunck, E. & Werthmann, H. Industry 4.0 – An Opportunity to Realize Sustainable Manufacturing and Its Potential for a Circular Economy. Dubrovnik International Economic Meeting, 3(1), 644-666. (2017). [ 2 ] De Carolis A., Macchi M., Negri E., Terzi S. A Maturity Model for Assessing the Digital Readiness of Manufacturing Companies. In: Lödding H., Riedel R., Thoben KD., von Cieminski G., Kiritsis D. (eds) Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing. APMS 2017. IFIP Advances in Information and Communication Technology, vol 11 513. Springer, Cham. (2017) https://doi.org/10.1007/978-3-319-66923-6_2 [ 3 ] Lee, HT., Song, JH., Min, SH. et al. Research Trends in Sustainable Manufacturing: A Review and Future Perspective based on Research Databases. Int. J. of Precis. Eng. and Manuf.-Green Tech. 6(1), 809–819. (2019). https://doi.org/10.1007/s40684-01900113-5 [ 4 ] Leipzig, T. P., Gamp, M. Manz, D. et al. Initialising Customer-orientated Digital Transfor- mation in Enterprises. Procedia Manufacturing, 8(1), 517-524. (2017). [ 5 ] Leng, J. Ruan, G., Jiang, P. et al. Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey. Renewable and Sustainable Energy Reviews 132,(110112), 1- 12. (2020). https://doi.org/10.1016/j.rser.2020.110112 [ 6 ] . Lepore, D., Micozzi, A. & Spigarelli, F. Industry 4.0 Accelerating Sustainable Manufacturing in the COVID-19 Era: Assessing the Readiness and Responsiveness of Italian Regions. Sustainability, 13(5), 2670, (2021). https://doi.org/10.3390/su13052670 [ 7 ] Machado, C. G., Winroth, M. P. & da Silva, E. H. D. Sustainable manufacturing in Industry 4.0: an emerging research agenda. International Journal of Production Research, 58(5), 1462-1484. (2019). [ 8 ] Ngu, H. J., Lee, M. D. & Osman, M. S. B. Review on current challenges and future opportunities in Malaysia sustainable manufacturing: Remanufacturing industries. Journal of Cleaner Production 273(123071), (2020). [ 9 ] Sartal, A. Bellas, R., Mejías, A. M. & García-Collado, A. The sustainable manufacturing concept, evolution and opportunities within Industry 4.0: A literature review. Advances in Mechanical Engineering, 12(5) (2014).https://doi.org/10.1177/1687814020925232 [ 10 ] Savastano, M., Amendola, C., Bellini, F. & DAscenzo, F. Contextual Impacts on Industrial Processes Brought by the Digital Transformation of Manufacturing: A Systematic Review. Sustainability, 11(3), 891, (2019); https://doi.org/10.3390/su11030891 [ 11 ] Sharma, R., Jabbour, C. J. & Jabbour, A B. Sustainable manufacturing and industry 4.0: what we know and what we dont. Journal of Enterprise Information Management, 34(1), 230-266. (2020). https://doi.org/10.1108/JEIM-01-2020-0024 [ 12 ] Stock, T. & Seliger, G. Opportunities of Sustainable Manufacturing in Industry 4.0. Procedia CIRP, 40(1), 536-541, (2016). Authors Photo Short Biography PAPER REVIEW Chapter Title: Digital Transformation and Its Opportunities for Sustainable Manufacturing Authors: NOTE: Please put X to show your selection Type of this paper   Research Survey Tutorial Speculative Others Your Choice Evaluation:   Very Poor Poor Average Good Very Good Significance of the main idea(s)  Originality Technical quality of the paper  Awareness of related work Clarity of presentation  Organization of the manuscript References Paper Length Overall comments and changes that MUST be made before publication: · Please write the detailed comments on paper and review here (say in 5 – 10 bullet points) Suggestions which would improve the quality of the paper but are NOT essential for publication: · Please write the suggestions to improve the paper here (say in 2 or 3 bullet points) Overall Recommendation:   Strongly Reject Reject Marginally Accept Accept Strongly Accept Recommendation Referee’s Name and Date NOTE: Please put X to show your selection Type of this paper Research Survey Tutorial Speculative Others Your Choice X Evaluation: Very Poor Poor Average Good Very Good Significance of the main idea(s) X Originality X Technical quality of the paper X Awareness of related work X Clarity of presentation X Organization of the manuscript X References X Paper Length X How comfortable are you in reviewing this pape r? Very Confident Confident Adequate Not Confident Not my Area Your Choice X Overall comments and changes that MUST be made before publication: · Author discusses the role of artificial intelligence and machine learning in the finance sector. · Introduction section should be improved. · Separate section for related work will be an added advantage for this paper. The authors need to inject the section of Related Work preferably after Introduction and investigate majority most of the previous work. · Nothing is novel since it is a survey article. But it can be good reference work for new researchers. · However, in order to present both the results and the conclusions as clearly as possible, we suggest to the authors of the paper the presentation of personal scientific contributions to the literature, as well as the presentation from an applicative point of view. · More references should be cited in reference section as well as body of the article. · Increase the length of the paper by making each section more comprehensive. · his work resembles an awareness of the use of artificial intelligence and its benefits in the financial field. Indeed the author in his awareness: - presents artificial intelligence in general - the financial areas in which it could be used - presents the importance of the diversity of data handled in finance. This could increase the level of risk associated with the processing of this data. The author tells us that artificial intelligence could make it possible to put in place triggers allowing to know the presence of possible risks. In these writings does not present how (in terms of algorithm - of process implemented) artificial intelligence comes to have a very important role in finance. It could be based on a practical case to support his remarks, especially since the manuscript is a succession of affirmations without associated scientific references Suggestions which would improve the quality of the paper but are NOT essential for publication:  1 - expand your bibliography 2 - carry out a good bibliographic review 3 - identify recent work carried out in connection with the role and associated results 4 - carry out a comparative study with the existing ones in technical terms of artificial intelligence used in the field of finance 5 - make scientific proposals with regard to the limits of what already exists by supporting these proposals with at least one practical case. Overall Recommendation: Strongly Reject Reject Marginally Accept Accept Strongly Accept Recommendation X