Impact of AI on Amazon Business Performance Assignment Sample

Introduction Of Impact of AI on Amazon Business Performance

Research project description

Amazon is a trillion-dollar giant company in e-commerce space headquarters in the US. They directly employ 1.3 million employees and offer almost every product that is possible to be purchased. The company continuously enhances customer-centric innovation by using Machine Learning (ML) and Artificial Intelligence (AI), which has taken the company to the next level. An AI-based solution such as product recommendations was first initiated by Amazon nearly 20 years ago that recommend the right product at the right time to the customers. It helps the company to enhance their sales as well as to satisfy the customers. Such approaches have given the company a competitive edge. Currently, the company uses automation and AI to boost their efficiency in their business operations and, more importantly, to enhance customer experience. For example, Amazon also includes AI-powered search relevancy. When customers use the search bar, then, there are 42% chance that the individuals are clicking for potential purchase, whereas the chances are only 16% for Wal-Mart (Gupta et al., 2023). This is possible through AI. The company hires a huge number of engineer's expert in search relevance, and the company uses an algorithm – A10 that successfully increase sales conversation. Amazon is also using AI in its supply chain, which is helping Amazon to optimize its supply chain (Gupta et al., 2023). AI is helping to predict customer demand, evaluate product availability, optimize delivery routes, track supply chain, robotics in warehouse management and personalize customer communication and others. It is helping Amazon to streamline its delivery process and to offer a delightful shopping experience. Likewise, the research shall interpret the impact of AI adaptation on Amazon on their business performance. The research findings shall discuss related literature and highlight the impact of AI-based solutions on supply chain and customer management in Amazon. The advantages, as well as the challenges related to AI, shall be explored.

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Research rationale

Currently, the world is encountering huge improvements in technological infrastructure, and Artificial Intelligence (AI) is one the result of technological innovation that is helping businesses to streamline their procedure, such as through enhancing customer service. Various big brands are using AI in every aspect of their business, and that is giving them competitive advantages. AI is helping in personalized product recommendations based on interpreting customer behavior. It is also helping in pricing optimization. For example, AI can suggest the brands how much discounts to offer. It is also enhancing customer service by using virtual assistance, supporting smart logistics, and helping to forecast transit times, shipment delays, demand levels, and others (Bawack et al., 2022). Though, often, some brands, such as smaller brands, do not include AI as they think it might cost huge. However, this research shall help to understand how brands can be benefitted and enjoy competitive advantages by using AI. This research shall discuss the organization- Amazon and how they are using AI in their supply chain to manage their customers, and enhance customer service, and how AI is giving advantages (Panigrahi and Karuna, 2021). The research shall help to gather knowledge regarding different AI-based solutions and their functions. The advantages and challenges regarding the solutions can also be understood. The research findings shall help to learn how AI-based solutions can improve various business aspects as well as reduce operational costs.

Research aim

The research aims to gather related literature and review them to analyze the extent to which Artificial Intelligence influences Amazon's business, including customer service, supply chain management, a recommendation system, and market competitiveness. The study also aims to understand the benefits, challenges as well as future prospects of AI adaptation in Amazon. The research shall aim to include an effective methodology to reach the findings.

Research Objectives

The research shall be conducted to meet the following objectives:

• To evaluate the role of AI in enhancing the efficiency and effectiveness of Amazon's supply chain management
• To access the impact of AI-powered customer service systems on customer satisfaction and retention
• To investigate the effectiveness of AI-based recommendation systems in driving sales and personalized shopping experience
• To analyze the competitive advantages gained by Amazon through AI adaptation

Research questions

The research findings shall help to answer the following questions:

• What is the role of AI in increasing the efficiency and effectiveness of Amazon's supply chain management?
• What are the impacts of AI-powered customer service systems on customer satisfaction and retention?
• What is the effectiveness of AI-based recommendation systems in driving sales and personalizing customer experience?
• What competitive advantages are gained by Amazon through AI adaptation?

Literature Review

Introduction

Amazon includes a complex supply chain where millions of products are shipped across the world. In order to handle the process, amazon has included AI to streamline their supply chain in various ways. AI is being used for demand forecasting, optimizing the inventory level, optimizing routing orders to efficient fulfillment centers and others, customizing customer communication, and tracking the entire supply chain. Amazon is also using Artificial Intelligence and Machine learning to compare the availability of products according to future product demand, and that helps to reduce waste. Amazon also includes AI-based product recommendation systems, chatbots, and others that help in enhancing customer relations (Soni, 2020). Similarly, this section shall gather a wide range of data and information by exploring different articles, journals, books, and other sources. The gathered literature shall be reviewed to understand the role of Artificial Intelligence in enhancing Amazon's supply chain, customer satisfaction, and sales channels, as well as the overall advantages and challenges that Amazon experience through AI adaptation.

Main Body

Role of AI in enhancing efficiency and effectiveness of Amazon's supply chain management

Supply Chain Management based on Artificial Intelligence has been proven to be highly effective in helping organizations in overcoming challenges that are reflected in modern supply chains. Dash et al. (2019) discussed that companies like Amazon use AI-based solutions to enhance their management and to achieve superior performance. Using predictive models and correlation analysis, AI-based solutions help the organization understand the cause and effects of their supply chains. For instance, Amazon is using an AI-based demand forecasting system called "Amazon Forecast," which is a fully managed service that use Machine Learning algorithm and Statistical data to reflect highly accurate time-series forecasts. It uses weather patterns, historical sales data, social media trends, and other relevant data to predict future data efficiently. Amazon also uses AI-powered route optimization system. The system considers factors such as weather, delivery priorities, road conditions, and traffic and suggests the best possible route. It helps to reduce the delivery time, reduce transportation costs as well as to enhance customer satisfaction. Likewise, Amazon uses a “Matric routing” system that evaluates the best routes that help both the organization and its customers.

Pervaiz (2020) discussed that Amazon includes effective warehouse management systems and includes automation in inventory management, picking, and packing function. Amazon is using AI-powered robots, and they move around the warehouse to sort packages for delivery. For example, Sparrow is the new intelligent robot of Amazon that streamlines the fulfillment process through moving products and in packaging and that support the employees.

Jones (2023) discussed that Amazon is also using AI-powered delivery system to optimize the last mile of the delivery process, which is the most time-consuming and expensive part of the supply chain. For example, Amazon is using AI-powered drones like “Prime Air drone” in locations such as California, Texas, and others, which help in fast delivery as they do not struggle with traffic and are also cost-saving as they do not require fuel and vehicles.

Figure 2: Showing the drone delivery system in Amazon

Source: (Jones, 2023)

Impact of AI-powered customer service system on customer satisfaction and Retention

He and Zang (2022) comprehend that Amazon use a "voice-enabled shopping experience via Alexa”. Rather than clicking on the screen, Amazon includes a voice assistant- Alexa, that helps users to search for products, purchase products, and navigate the checkout process and others. It helps users to purchase and checkout without using their hands. Users can also create a shopping list, and Alexa recommends products that make shopping from Amazon more convenient and give the users an experience of offline shopping. Moreover, Amazon is also using “Amazon ,Go” which is a e-commerce mobile application that helps customers to buy items in physical stores; however, they do not have to wait in lines. The system uses sensor technology, Machine Learning, and Artificial Intelligence that enhance customer satisfaction and retention.

AI is also helping to enhance customer service via Chatbots, which are AI-based computer applications that can replicate human communication and respond to the queries of the customer rapidly 24 hours per day. Prentice et al. (2020) highlighted that Chabots is helping Amazon to enhance customer interaction and also offer personalized advice and offering prompt responses. Amazon using AI-based solution, is able to enhance customer satisfaction and retention as when any individual purchases anything from Amazon, then, continuous communication is maintained from the company. AI solutions offer customer-tailored communication that gives personalized user experience, and helps to enhance customer relationships and sales. AI also helps in sentiment analysis using NPL or Natural Language Processing. It analyzes attitudes and emotions which are expressed in text data like in social media posts, customer reviews, e-mails, or surveys. It helps Amazon to identify areas that need improvements. Likewise, customers can be satisfied more. Moreover,

Effectiveness of AI-based recommendation systems in driving sales and personalized shopping experience

Organizations operate in a competitive environment where the expectations of the customers are high. In order to retain customers, firms need to offer timely, personalized, and as well as relevant services that can create value and satisfaction. Similarly, Masyhuri, (2022), discussed that Artificial Intelligence is helping the firms to understand customer's needs, behaviors and likewise; they can optimize interactions and service delivery. Acharya et al. (2023), using a quantitative research design, investigated the effect of AI-driven RSs in e-commerce. Data was collected from 452 active purchasers from Amazon via an online cross-sectional survey. The data was analyzed using a partial least square structural equation modeling system. The findings reflected that Recommended Systems (RSS) based on AI and ML are "interaction-based" technologies that recommend suitable products to potential customers. Likewise, Amazon uses AI-based solutions for personalized recommendations. Recommendations are generated through an algorithm depending on data from peoples or objects rating profiles. The use the system of "item to item collaborative filter" for personalized recommendation where individuals who have purchased previously shall be recommended similar products (as it is believed that such previous types of products are preferred or required by the customer) to influence their purchasing decision and it helps to anticipate the requirements of the customer. The AI-based system also recommends products based on sentiment analysis, search history, market trends, and previous purchasing history. Such personalized product recommendation helps to increase purchasing process and to offer a personalized shopping experience.

Competitive advantages gained by Amazon through AI adaptation

Amazon gains various advantages due to the implementation of AI. Paljwal et al. (2021) mentioned that there are certain challenges related to AI, such as including biased or incomplete data that can result in huge errors. However, Amazon is using AI in an effective way, and the Demand forecast system allows the company to optimize inventory levels and reduce waste. It helps in cost savings. Moreover, the robotics in the warehouse helps to sort out products, and push weighty products without errors. It helps the company to operate accurately, and they can save costs related to hiring employees to perform those jobs. Moreover, employees can focus on more important jobs as compared to those picking and sorting jobs. Furthermore, the drone delivery system helps them to deliver products on the expected schedule as drones do not have to go through congested roads, and that enhances customer satisfaction. Moreover, it reduces the cost of delivering vehicles such as bikes and others.

Amazon heavily invests in Artificial Intelligence that develops personalized shopping experience for the clients. Some of the advantages are better customer retention. AI recommendation systems help in customer engagement, and that helps in customer retention. Similarly, Saisubramian et al. (2022) reported that Amazon using AI-based solutions, became able to enjoy competitive advantages, and they achieved e-commerce markets share in the US of 37.8%. The website of Amazon receives around 2 billion visitors monthly and is the top e-commerce website in the US. They have more than 200 million prime members across the world. Above 1.9 million SMEs sell on Amazon, and according to the latest financial reports, the company is worth $485.9 billion. Feedvisor consumer survey mentioned that around 89% of buyers are likely to purchase from Amazon as compared to other sites (Saisubramian et al., 2022).

Research gap

To summarize the section, it shall be discussed that Amazon is one of the major e-commerce giants that has reached greater heights, and one of the major factors for their success is technological innovation. The company has included innovation in every aspect of their business. They have included AI in their supply chain management. For example, they are using AI to predict their demand forecast and are including products as much as the demand is forecasted. It is helping the company to reduce waste and cost. Moreover, they are using robots for warehouse management, and that is helping to reduce errors in inventory management. The company is also using AI-powered drones for last-mile delivery that is helping to deliver the products at low cost and rapidly as compared to their competitors. AI is also helping the company to enhance customer satisfaction. They use Chatbots to interact with customers continuously. They are using product recommendations, and based on previous purchasing history, searchers, and others, AI-powered systems are recommending the preferred products to the customers, and it is enhancing their sales. Likewise, the company is getting competitive advantages. However, it shall be discussed that many small enterprises do not use AI due to the myth that AI implementation needs huge costs and that it is a complex process. However, the research gap is that the existing literature is that certain articles (as shown below) discuss regarding the drawbacks of AI. However, this research shall help to overcome such gap and highlight the AI- based applications that are benefitting Amazon.

Burns, E., Laskowski, N. and Tucci, L., 2021. What is artificial intelligence.Search Enterprise AI.	The article discussed that AI based solutions are “Expensive; Requires deep technical expertise; Limited supply of qualified workers to build AI tools; Only knows what it's been shown; and Lack of ability to generalize from one task to another”.
Rana, N.P., Chatterjee, S., Dwivedi, Y.K. and Akter, S., 2022. Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm's operational inefficiency and competitiveness.European Journal of Information Systems,31(3), pp.364-387.	This article discuss AI based solutions has perceived risk and can be responsible for a firm's “operational inefficiency, competitivedisadvantage and supplychainpractices.
Gregor, B. and Gotwald, B., 2021. Perception of artificial intelligence by customers of science centers.Problemy Zarz?dzania, (1/2021 (91)), pp.29-138.	The research results showed that the major disadvantages of AI are the limitation of choice in terms of preferred products (for example, during online shopping) and threats of data leaks.

Table 1: Showing the articles and their gaps Source: (Developed by the learner)

Research methodology

Gantt chart

Events	1st and 2nd week	3rd and 4th week	5th and 6th week	7th and 8th week	9th and 10th week	11th and 12th week	13th and 14th week	15th week
Selecting the research topic and aims of the research
Selecting research method and gathering relevant data
Reviewing the data
Analyzing the ethical considerations
Reaching to research findings

Figure 3: Showing the project timeline

Source: (Developed by the learner)

Research structure

The research took 15 weeks to be completed. Various topic related to business in the digital world was explored and the research topic – Impact of AI in Amazon's business performance along with the aim and objectives of the research was selected in the first week that is from 1.03.2024 to 7.03.2024. The data collection also initiated from 1st week that is from 01.03.2024 and it is expected to be completed on 3.06.2024 that is on the 8th week. From 9th to 12th week data shall be reviewed that is the data analysis is expected to be completed on 1.07.2024. Ethical consideration shall be monitored in the 13th and 14th week that is from 7.07.2024 to 21.07.2027. In the last week that is on the 15th week – 30.07. 2024, the research shall be concluded

Research methodology

The research shall be based completely on secondary method. Interpretivism research philosophy shall be used as research philosophy as it helps to observe and interpret the gathered data. Inductive research approach shall be used as it shall interpret specific theories and underlying patterns and reflect general theory that shall help to understand the impact of AI in supply chain management, customer relation management and other in Amazon. Mono-method and qualitative method shall be used and only non-numeral data shall be gathered and interpret to understand the impact of AI on business performance of Amazon and how AI gives competitive advantage to the mentioned company. Qualitative research has been included as it helps to ask questions that cannot be easily put in numbers for understanding human experience (Iovino, and Tsitsianis, 2020). It has help to comprehend everyday realities of social phenomenon such as impact of AI in business phenomenon. Data shall be collected through secondary method. Some search terms shall be formulated such as “impact of AI”, AI in Amazon” and others and using the term related articles shall be searched from database like Google Scholar, CINAHL and others. Data shall be gathered from organizational website, magazines and other secondary source. The data shall be analyzed using thematic analysis. Such method shall help to analyze qualitative data. It helps to read through a data set and to identify patterns and themes from the data (Al-Ababneh, 2020). Such analysis helps to generate different themes and that shall help to answer the research questions.

Ethical considerations

Research ethics shall be followed. Activities such as plagiarism shall be avoided. Data taken from other articles and journals shall be duly  (Iovino and Tsitsianis, 2020). None of the findings or discussion shall harm any individual.

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Conclusion

Thus, to conclude it shall be discussed that AI is impacting business performance positively. AI based solutions such as demand forecasting system, warehouse robotics, drone delivery systems, personalized recommendation systems and others are helping organizations like Amazon to enhance their performance. It is also enhancing shopping experience for the customers. However, if data becomes biased or incomplete then the technology shall fail to reflect efficient results. Thus, organizations need to overcome such challenges in order to enjoy the advantages of AI.

Reference

• Acharya, N., Sassenberg, A.M. and Soar, J., (2023). Effects of cognitive absorption on continuous use intention of AI-driven recommender systems in e-commerce.foresight,25(2), pp.194-208.
• Al-Ababneh, M.M., (2020). Linking ontology, epistemology and research methodology.Science & Philosophy,8(1), pp.75-91.
• Bawack, R.E., Wamba, S.F., Carillo, K.D.A. and Akter, S., (2022). Artificial intelligence in E-Commerce: a bibliometric study and literature review.Electronic markets,32(1), pp.297-338.
• Burns, E., Laskowski, N. and Tucci, L., (2021). What is artificial intelligence.Search Enterprise AI.
• Dash, R., McMurtrey, M., Rebman, C. and Kar, U.K. (2019). Application of artificial intelligence in automation of supply chain management.Journal of Strategic Innovation and Sustainability,14(3), pp.43-53.
• Gregor, B. and Gotwald, B., (2021). Perception of artificial intelligence by customers of science centers.Problemy Zarz?dzania, (1/2021 (91)), pp.29-138.
• Gupta, S., Singhvi, S. and Granata, G., (2023). Assessing the Impact of Artificial Intelligence in e-Commerce Portal: A Comparative Study of Amazon and Flipkart. InIndustry 4.0 and the Digital Transformation of International Business(pp. 173-187). Singapore: Springer Nature Singapore.
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• Iovino, F. and Tsitsianis, N., (2020). The methodology of the research. InChanges in European energy markets(pp. 79-95). Emerald Publishing Limited.
• Jones, W.D., (2023). Amazon Plans to Take Home Delivery to New Heights.IEEE Spectrum,60(1), pp.16-17.
• Masyhuri, M., (2022). Key Drivers of Customer Satisfaction on the E-Commerce Business.East Asian Journal of Multidisciplinary Research,1(4), pp.657-670.
• Paliwal, M., Patel, M., Kandale, N. and Anute, N., (2021). Impact of artificial intelligence and machine learning on business operations.Journal of Management Research and Analysis,8(2), pp.70-75.
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• Rana, N.P., Chatterjee, S., Dwivedi, Y.K. and Akter, S., (2022). Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm's operational inefficiency and competitiveness.European Journal of Information Systems,31(3), pp.364-387.
• Saisubramanian, S., Kamar, E. and Zilberstein, S., (2022). Avoiding negative side effects of autonomous systems in the open world.Journal of Artificial Intelligence Research,74, pp.143-177.
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