The advent of artificial intelligence (AI) solutions over the last few years and the burgeoning use of generative AI, in particular, is revolutionizing retail.
From the supply chain to consumer-facing chatbots, AI has emerged as a catalyst for online retail and brick-and-mortar retail experiences. The technology is used to predict and anticipate a consumer’s preferences throughout the shopping journey, adding personalized suggestions to the experience. It can also finely tune inventory management to ensure products are in stock and customized to that store’s location.
The fusion of AI and retail has ushered in an era of unparalleled convenience and innovation, particularly in light of OpenAI’s ChatGPT, which has introduced a fresh new perspective. The technology debuted in late 2022 and has captured the world’s attention. But are retailers ready? Are consumers ready?
With novelty comes responsibility. Entirely autonomous AI systems make mistakes or misinterpret situations that humans would handle differently. For this reason, retailers must ensure that a human is always in the loop for critical decision-making. It’s essential to review the big picture as retailers embark on their AI journeys.
Challenges and risks in artificial intelligence
When working with new technology, retailers must be aware of the risks, rewards, opportunities, and challenges. For AI, like the generative AI used to power ChatGPT and Google’s Bard, retailers should be aware of the following risks and challenges:
- Maintaining Data Privacy and Security: AI systems rely heavily on data, and the collection, storage, and processing of customer data raises concerns about privacy and security. Retailers must ensure that customer information is safeguarded and that AI algorithms comply with data protection regulations.
- Fostering Customer Trust: Over-reliance on AI can lead to reduced human interaction, impacting customer relationships and trust. Customers may feel uncomfortable if they believe their interactions are solely with machines, leading to a decline in brand loyalty.
- Balancing Human Oversight: Fully autonomous AI systems may make mistakes or misinterpret situations that humans would handle differently. Retailers should ensure that there's always a human in the loop for critical decision-making.
- Unveiling Generative AI's Potential: The artistic output of generative AI tools holds immense potential, but vigilance is crucial to curbing its misuse. Preventing the generation of misleading content and fake reviews is integral to retail's ethical framework.
To address these risks, retailers should adopt a thoughtful and comprehensive approach to AI implementation. This includes conducting thorough risk assessments, investing in data quality and governance, maintaining human oversight, and fostering transparency in AI decision-making processes.
By proactively addressing these challenges, retailers can unlock the potential benefits of AI while minimizing its associated risks.
AI offers a plethora of opportunities for retailers to enhance various aspects of their operations and customer experience.
Four ways to leverage AI in the retail industry
Artificial intelligence has hundreds, if not thousands, of applications within the retail industry. Four impactful AI-driven opportunities that can benefit retailers include:
- Loss Prevention and Fraud Detection: AI can be employed for real-time shopping and return behavior to identify suspicious activities, potential theft, or other anomalies. Retailers can use predictive analytics to detect patterns associated with fraudulent transactions, both online and in-store. By leveraging AI for loss prevention and fraud detection, retailers can enhance security and protect their bottom line.
- Personalized Customer Experiences: AI enables retailers to analyze large volumes of customer data and derive insights to create personalized shopping experiences. By understanding customer preferences, purchase history, and behavior, retailers can deliver targeted recommendations, customized promotions, and product suggestions. AI-powered models can provide real-time personalized incentives to ensure loyal customers replace/exchange a product instead of simply returning it.
- Optimized Pricing: AI-driven pricing algorithms analyze market trends, competitor prices, customer demand, and other factors to determine optimal pricing strategies. Retailers can also use AI to run experiments and A/B tests to identify the most effective pricing strategies for different products and customer segments.
- Cost Reduction and Customer Service: AI algorithms can help analyze consumer behaviors to assess if certain operational fees/costs should be applied. For example, should consumers who return multiple ‘damaged’ items be charged for shipping items back? When should re-stocking fees be implemented? AI algorithms can help assess the most cost-effective ways to protect the retailer’s bottom line while continuing to provide excellent customer service.
Embark on your AI retail journey
AI can be harnessed to transform retail operations. The key is to identify areas where AI can have the most significant impact based on the retailer's unique goals and challenges. This can include:
- Optimizing in-store and ecommerce returns
- Minimizing fraudulent Did Not Arrive and Item Not Received claims
- Enhancing the consumer returns experience
- Avoiding hiring and onboarding costs
- Gaining inventory visibility and reduce retail shrink
By strategically integrating AI into their operations, retailers can enhance customer satisfaction, improve operational efficiency, and gain a competitive edge in the dynamic retail landscape.
Dr. Adi Raz, Vice President of Data Science, Appriss Retail
Adi has more than 25 years of experience managing data scientists and modeling teams, developing and integrating analytical products, and building efficiencies in data operations, analytics, and modeling. Adi is responsible for end-to-end management of all operational aspects of the data and analytical products for Appriss Retail across hundreds of global retailers. Before joining the company in 2004, Adi was the senior director of data sciences at Washington Mutual and a pricing analyst for Circuit City. Adi earned her Doctorate in Business and an MBA from Pepperdine University.