Retailers can leverage generative AI to enhance support for customers and employees.

As the retail industry witnesses a shift to a more digital, on-demand consumer base, AI is becoming the secret weapon that allows retailers to better understand and cater to evolving consumer behavior. With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further leverage a variety of benefits that can improve customer care, talent innovation, and application performance.

Generative AI excels at processing a variety of data sources, including emails, images, videos, audio files, and social media content. This unstructured data forms the backbone for model creation and continuous training of generative AI, ensuring it remains efficient over time. Leveraging this unstructured data can extend to many aspects of retail operations, including enhancing customer service through chatbots and facilitating more effective email routing. In practice, this may mean directing users to appropriate resources, such as connecting them to the right agent or directing them to user guides and FAQs.

Retailers are recognizing the need to build strategies around AI and integrate it into many aspects of their operations. According to a recent CEO study from IBM, industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed saying they will use generative AI, deep learning, etc. to deliver results over the next three years. They answered that they use AI technologies such as machine learning. This data tracks closely with recent IDC Europe research, which found that 40% of retailers and brands globally are in the generative AI experimentation stage and 21% are already investing in generative AI implementations.

The impact of these investments will become clear in the coming years. Generative AI is expected to have a total financial impact of $9.2 trillion on retail by 2029, according to a recent forecast from research and analytics firm IHL Group. While generative AI currently accounts for just 9% of the retail industry’s revenue impact in 2023, IHL predicts that generative AI will account for 78% of the total financial impact by 2029, totaling $4.4 trillion that year.

Generative AI can reveal key insights

AI can help retailers leverage the vast amounts of data they have access to, much of which has been untapped until now. From customer behavior prediction to supply chain efficiency and personalized marketing, AI has the potential to transform industry efficiency and productivity in many critical areas, including customer care, operational efficiency, and talent transformation.

• Customer Support: According to IBM’s recent CEO study examining the retail and consumer goods sector’s perspectives on artificial intelligence, customer care is the top priority for these industries today. In the realm of customer care, generative AI can help retailers adopt a customer-centric approach by leveraging valuable insights from customer feedback and purchasing habits. This data-driven approach can help improve product design and packaging and help drive higher customer satisfaction and increased sales.

Generative AI can also act as a cognitive assistant for customer care, providing context-sensitive guidance based on conversation history, sentiment, analytics, and call center recordings. Generative AI can also enable personalized shopping experiences that increase customer loyalty and provide a competitive advantage.

• Operational Efficiency: In terms of operational efficiency, AI technology can improve pricing strategies, inventory management, and logistics to optimize profits and provide a seamless shopping experience for customers. For example, generative AI can be used to predict changes in demand for dynamic pricing and improve logistics by analyzing factors such as delivery time and transportation costs, thereby potentially reducing costs and improving customer service through pricing and fulfillment strategies. can be optimized.

Generative AI can also use historical sales data and external factors to more accurately predict demand, preventing stockouts and excess inventory while automating inventory replenishment and allocation. By managing these aspects efficiently, retailers can streamline operations and increase overall performance.

• Talent Innovation: A third potential area of ​​impact is talent innovation, where retailers can leverage chatbots for recruiting and onboarding to make the process more efficient. Once onboarded, employees can receive customized, adaptive training programs created by generative AI that help identify individual learning styles and knowledge gaps.

Building new skills for existing employees is the most important talent issue for C-suite leaders, according to a recent IBM Institute for Business Value (IBV) study. Retail executives surveyed cited “tech illiteracy” and “building new skills for existing talent” as two of the biggest talent challenges for their organizations today. Retail executives surveyed predicted that more than 41% of their workforce will need to reskill due to AI and automation implementation over the next three years. Nearly half of responding retail executives said they invest in retraining rather than external hiring.

IBM-generated AI is ready for retail.

IBM has developed AI solutions to help address these requirements. The retail industry can access IBM’s AI through three modes: Chief among them is IBM® watsonx™, a cloud-based AI and data platform that provides design control and flexibility. Other IBM AI products include IBM® watsonx Orchestrate™, IBM® watsonx Code Assistant™, and IBM® watsonx Assistant™. The third mode is through seamless integration with open source platforms and partner products, such as Red Hat® OpenShift® AI.

IBM launched watsonx to help businesses leverage the opportunities of generative AI and underlying models. Watsonx consists of IBM® watsonx.ai™, IBM® watsonx.data™, and IBM® watsonx.governance™. Watsonx.ai is a next-generation enterprise studio that allows AI builders to train, validate, tune, and deploy both traditional machine learning and new generative AI capabilities based on foundational models through an open and intuitive user interface. Watsonx.data is a data store based on lakehouse architecture and open data formats designed to manage enterprise data for foundational models. The third component is watsonx.governance, scheduled to be available in December 2023. It is a powerful set of tools to specify and manage enterprise governance processes and control risk.

Going forward, retailers will be able to use watsonx.data to leverage large amounts of heterogeneous, unstructured customer data and build models in watsonx.ai to leverage recommendation algorithms for personalized shopping recommendations. With customer consent and based on past purchasing and browsing behavior, retailers can create virtual try-on tools and develop interactive shopping assistants. Integrating Watsonx.governance into this process helps retailers manage customer data ethically and responsibly.

By leveraging these tools, retailers will be well-positioned to embrace generative AI as an integral part of their strategy and equipped to navigate an increasingly complex and rapidly changing consumer landscape.

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