There is a lot of good to be said about the applications of AI in retail, but there still exists the concern for ethics and bias, especially when AI is being used by companies to get customers to spend their money. On the other side of things, for companies it costs a lot of money to implement, budget, and apply a technology that will need constant updates, maintenance, and an ability to be tailored for the needs of that company.

I chose to discuss the application of AI in retail, because this is an area of technology I interact the most with. Firsthand, I have experienced being a consumer and using websites to purchase products that have AI assistance programmed into their website. While I have had great experiences with quick customer service, I have also had bad ones with websites not working properly, and sometimes the programming being ineffective. This makes me curious about how these technologies will continue evolving to make the retail experience and industry even better. 

In my Padlet wall I will include examples of AI usage with specific companies, examine future trends like autonomous stores, address ethical considerations with privacy concerns and algorithmic bias, analyze societal impact such as in the workplace and consumer behavior, and reflect on what I have learned from my extensive research on the topic of retail. AI in retail is changing how we shop, how businesses operate, and how consumer relationships are built. 

Generative AI is key in retail, giving up small tasks to technology, in order for staff to focus on more social-like issues such as relationship building and customer problem-solving. Visibility is another key feature in retail we are sure to see in the future, because customers and stores alike will have more awareness as to what items are available, how smoothly a website or store is running based on web traffic, and even the condition of vehicles that are delivering such items. The personalization and interactiveness of AI will only get better as this technology continues to grow in the retail industry. Operations will become as efficient as ever with advanced data collection for powerful consumer insights, connecting customers with their biggest needs and answers. 

The implementation of AI has done wonders in the retail world, but its rapid implementation has raised concerns about privacy and fairness. Some ethical issues that have been raised about AI include algorithmic bias, consumer privacy, data protection and fairness. Many customers that have used AI in retail have felt like AI systems do not treat customers equally, and that there’s a lack of trust with how their data is being used and stored. One of the biggest challenges for retailers to tackle is finding a way to be as transparent as possible; while also maintaining the protection of data they collect from customers. Some studies suggest for retailers to address biases, use the voices of concerned consumers for AI development, and assure customers of the measures taken to uphold data privacy. I myself find data privacy to be a valid area of concern, especially when personalization is so unique and specific to a person. I believe that it’s important to remember not to overshare with chatbots and use them mostly for questions that can be answered with a “yes” or “no”. As for the future of AI in retail, it is proving to be a major positive breakthrough for both consumers and retailers. With AI taking over smaller jobs within retail, there are going to be many more opportunities created to operate and manage these systems, which is both exciting and innovative.

Employment is affected by the implementation of AI in retail, but it’s not to say that it’s a complete negative impact. While inventory clerks and cashiers may not be needed, there are new roles for data analysis, and customer experience specialists. Workforce retraining and adjustments are needed, and not all workers will be able to acclimate which is a negative, but a positive is that AI is not taking over jobs without giving one in return.

Privacy will continue to be an issue as long as retailers collect the amount of consumer data that they do which goes unprecedented. These privacy concerns consist of facial recognition, tracking the location of customers, and stalking their browsing history. An environment has been created where consumers are constantly being surveilled, and the question becomes, is the convenience of personalization worth the surveillance?

Equity issues exist with algorithmic bias, an area of AI that is prevalent in retail as a lot of it has to do with who the consumer is. Recommendations are many times based on demographics, and this could lead to some consumers being presented with the best items they have, while others are offered budget options based on algorithmic assumptions. I personally have experienced this with buying hair products on Amazon, where I have purchased curl creams and gel before. I have been recommended bonnets and a pick comb after my hair product purchases, intended for the use of Afros, yet my hair is not curly enough for a pick comb to even achieve what it’s used for. I felt like they used my information to classify me into a particular race category, and from there filtered out a universal result for all of those in that same demographic. It didn’t feel as personalized anymore. Due to this, while I think AI can be super helpful and convenient, there are definitely flaws that exist in how the algorithms are built and by who. This type of technology might benefit some over others, and it varies from store to store, person to person. 

Adanyin, A. (2024, October 27). Ethical AI in Retail: Consumer Privacy and Fairness. European Journal of Computer Science and Information Technology, 12(7), 21-35. https://eajournals.org/ejcsit/wp-content/uploads/sites/21/2024/10/Ethical-AI-in-Retail.pdf [Rationale: This article provided the ethical dilemmas of consumer trust in AI applications. More specifically with data privacy and fairness.]

Fairlie, M. (2024, October 29). The Business of Automation and AI-Powered Retail Predictions. Business.com. Retrieved March 4, 2025, from https://www.business.com/articles/automation-ai-powered-retail-predictions/ [Rationale: Assesses AI’s ability to analyze data for retail and consumer insights.]

Intel. (n.d.). Artificial Intelligence (AI) in Retail. Intel. Retrieved March 13, 2025, from https://www.intel.com/content/www/us/en/learn/ai-in-retail.html#:~:text=drive%20greater%20return.-,AI%20in%20Retail%20Use%20Cases,in%20crowded%20and%20competitive%20spaces. [Rationale: Explains the future trends of AI in retail and its benefits.]

Marotta, D. (n.d.). Artificial Intelligence: How AI is Changing Retail. Hitachi Solutions. Retrieved March 4, 2025, from https://global.hitachi-solutions.com/blog/ai-in-retail/ [Rationale: Explains the way in which AI is socially impacting the lives of many consumers.]

Nagaraja, A. K. (2024, October 22). How Generative AI and Data are Redefining Retail Experiences. AWS Industries. Retrieved March 4, 2025, from https://aws.amazon.com/blogs/industries/how-generative-ai-and-data-are-redefining-retail-experiences/ [Rationale: Amazon quicksight is explained to provide faster issue resolution and an improved customer experience.]

Spencer, A. (2024, April 19). Artificial Intelligence in Retail: 6 Use Cases and Examples. Forbes. Retrieved March 4, 2025, from https://www.forbes.com/sites/sap/2024/04/19/artificial-intelligence-in-retail-6-use-cases-and-examples/ [Rationale: A general idea of how AI is used in the retail industry.]

Walmart Innovation. (2024, October 9). Walmart Reveals Plan for Scaling Artificial Intelligence, Generative AI, Augmented Reality and Immersive Commerce Experiences. Walmart Innovation. Retrieved March 4, 2025, from https://corporate.walmart.com/news/2024/10/09/walmart-reveals-plan-for-scaling-artificial-intelligence-generative-ai-augmented-reality-and-immersive-commerce-experiences [Rationale: Walmart explains their generative AI program Wallaby and other LLMs.]