Investing in AI: How Retailers Are Future-Proofing Profits and Leading the Industry
The retail industry is undergoing a transformation, driven by the rapid adoption of Artificial Intelligence (AI). Retailers are strategically investing in AI to enhance productivity, foster innovation, and secure a leading position in the industry. This article explores these investments, focusing on generative AI, productivity enhancements, and industry leadership.
One day this trend may even include in-store robots helping customers with their purchasing decisions. (AI generated image)
Generative AI in Retail
Generative AI is emerging as a key area of focus for retailers. By leveraging algorithms that can generate new data instances, retailers may enhance customer experiences. According to the Future Consumer Index (FCI) by EY, 50% of consumers are comfortable using AI to improve purchase experiences [1]. What are some of the experiences that customers may expect?
Personalised product recommendations: Generative AI can analyse customer data and browsing history to provide tailored product suggestions that align with their preferences and needs. This creates a more engaging shopping experience.
Virtual try-on: Retailers can use generative AI to allow customers to digitally "try on" clothing and accessories. This would reduce returns and enhance the shopping journey. There are already examples of this, such as Loreal’s app for virtual makeup try-on [2] to Wayfair’s app to see new furniture styles in your home [3].
Personalised content and promotions: Generative AI is beginning to transform marketing by creating personalised content, such as text, scripts, and videos, and targeted promotions based on individual customer preferences and habits [4].
Productivity Enhancements
AI is not only transforming customer interactions but also boosting productivity within the retail sector. From inventory management to demand forecasting, AI is enabling retailers to make data-driven decisions. Around 47% of respondents believe that AI can greatly enhance inventory management, leading to cost savings and better alignment with buyers' needs [5]. Examples of productivity enhancements include:
Demand forecasting: AI algorithms can analyse vast amounts of data, including sales history, market trends, and customer preferences, to generate accurate demand forecasts. This enables retailers to optimise their supply chain, reduce stockouts, and improve customer satisfaction [6].
Inventory management: AI can greatly enhance inventory management by analysing historical sales data, customer behaviour, and external factors to accurately predict demand and optimise inventory levels. This helps retailers avoid overstocking or understocking, leading to cost savings and better alignment with buyers' needs [6].
Industry Leadership
Investing in AI is seen as a key to future-proofing profits and becoming an industry leader. Retailers who are ahead of the game in AI adoption are redefining loyalty and setting new standards in the industry. As the report by KPMG highlights, 90% of retail business leaders believe their employees are prepared for AI adoption, reflecting a significant increase in readiness since early 2020 [7].
According to a study by IBM Corporation, the adoption of AI in retail and consumer products is expected to leap from 40% of companies currently to more than 80% in three years [8]. Retailers are investing heavily in AI to future-proof profits and become industry leaders in the retail sector. Some examples of retailers that are investing in AI include Walmart, Amazon, and Alibaba [9].
Challenges and Ethical Considerations
While the benefits are substantial, retailers must also navigate challenges such as cybersecurity breaches, AI bias, and ethical considerations. Ensuring transparency and trust with customers in the era of AI-driven retail is paramount.
Cybersecurity Vulnerabilities: In the process of gathering and scrutinising extensive customer data, retailers must give paramount importance to cybersecurity to shield sensitive details from unauthorised intrusion and breaches. The establishment of stringent security defences and encryption methods is vital to preserving customer confidence and securing information.
AI Prejudice: Training generative AI algorithms on pre-existing data may inadvertently instil biases and foster unjust practices. Retailers have the responsibility to actively combat AI prejudice by utilising diverse and unbiased training datasets, conducting routine bias examinations in algorithms, and instituting principled standards for AI creation and execution.
Ethical Obligations: The ethical ramifications of employing generative AI, encompassing aspects like data confidentiality, informed consent, and conscientious handling of customer information, must be a focal point for retailers. The formulation of transparent policies and adherence to pertinent legal standards, such as GDPR, is of the utmost importance.
Ultimately the strategic investments in AI by retailers are shaping the future of the industry. From enhancing customer care to optimising inventory management and leading the industry, AI is proving to be a vital asset for retailers. As the market continues to evolve, the integration of AI across online and offline platforms will redefine the retail landscape, offering opportunities for growth and innovation. Who knows, one day this trend may even be the new norm and include in-store robots helping customers with their purchasing decisions.
References
[1] Drenik, G. (2023, June 14). AI And Retail: Consumer Adoption On The Rise, Yet Uncertainty Looms. Forbes.
[2] Consantine, J. (2016, January 19). Augmented Reality For Trying On Makeup Is A Booming Business. TechCrunch
[3] Wiggers, K. (2023, July 25). Wayfair's new app uses generative AI to transform your space. TechCrunch
[4] Gill, L. (2023, April 3). Generative AI In Marketing: 5 Use Cases. Forbes. Retrieved from Forbes
[5] Statista. (2022). Global AI use cases for consumer goods and retail 2020.
[6] Databricks. (2023, April 13). Retail in the Age of Generative AI.
[7] KPMG. (2021). Impact of AI on the retail industry.
[8] Mordor. Artificial Intelligence In Retail Market Size & Share Analysis - Growth Trends & Forecasts (2023 - 2028). (N.d.). Retrieved August 19, 2023
[9] Gonzalez, W. (2021, December 1). Putting The AI In Retail: How AI Is Changing This Year’s Holiday Retail Landscape. Forbes.
