As the retail industry witnesses a shift towards a more digital, on-demand consumer base, AI is becoming the secret weapon for retailers to better understand and cater to this evolving consumer behavior. With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications.
Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. Leveraging this unstructured data can extend to various aspects of retail operations, including enhancing customer service through chatbots and facilitating more effective email routing. In practice, this could mean guiding users to the appropriate resources, whether that’s connecting them with the right agent or directing them to user guides and FAQs.
Retailers recognize the need to build their strategies around AI, integrating it into many aspects of their operations. According to IBM’s latest CEO study, industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years. This data tracks closely with a recent IDC Europe study that found 40% of worldwide retailers and brands are in the experimentation phase of generative AI, while 21% are already investing in generative AI implementations.
The impact of these investments will become evident in the coming years. A recent forecast by the research analyst firm IHL Group predicts that generative AI will have a total financial impact of USD 9.2 trillion on retail businesses through 2029. While generative AI currently makes up only 9% of the retail industry’s bottom line impact in 2023, IHL anticipates generative AI will grow to represent 78% of the total financial impact by 2029, reaching a total of USD 4.4 trillion in that year.
Generative AI can reveal key insights
AI equips retailers to harness the vast amount of data they have access to, much of which has been underutilized until now. From customer behavior predictions to supply chain efficiency and personalized marketing, AI has the potential to revolutionize the industry’s efficiency and productivity in several important areas, including customer care, operational efficiency and talent transformation.
Customer care: According to IBM’s recent CEO study, where we examined the retail and CPG sectors’ perspectives on artificial intelligence, the top priority for these industries today is customer care. In the realm of customer care, generative AI empowers retailers to adopt a customer-centric approach by harnessing valuable insights from customer feedback and buying habits. This data-driven approach can help improve product design and packaging and can help drive high customer satisfaction and increased sales.
Generative AI can also serve as a cognitive assistant for customer care, providing contextual guidance based on conversation history, sentiment, analysis, and call center transcripts. Additionally, generative AI can enable personalized shopping experiences, fostering customer loyalty and providing a competitive advantage.
Operational efficiency: When it comes to operational efficiency, AI technologies can enhance pricing strategies, inventory management, and logistics, optimizing revenue and creating a seamless shopping experience for customers. For example, generative AI could be used to optimize pricing and fulfillment strategies by predicting demand fluctuations for dynamic pricing and analyzing factors including delivery times and shipping costs to improve logistics, potentially resulting in cost savings and enhanced customer service.
Generative AI can likewise use historical sales data and external factors to help predict demand more accurately to prevent stockouts and excess inventory while also automating inventory replenishment and allocation. By efficiently managing these aspects, retailers can streamline their operations and boost overall performance.
Talent transformation: A third area of potential impact is talent transformation, where retailers can leverage chatbots for recruitment and onboarding, making the process more efficient. Once onboarded, employees can be given personalized and adaptive training programs created by generative AI that help identify individual learning styles and knowledge gaps.
Building new skills for existing employees is the top talent issue for C-suite leaders, according to a recent IBM Institute for Business Value (IBV) study. Retail executives surveyed ranked “technology illiteracy” and “building new skills for existing talent” as two of their organizations’ top talent challenges today. Retail executives surveyed estimate more than 41% of their workforce will need to reskill as a result of implementing AI and automation over the next three years. Nearly half of the responding retail executives say they invest in reskilling, as opposed to hiring from the outside.
IBM generative AI is ready for retail
IBM has developed AI solutions to help address these needs. The retail industry can access IBM’s AI through three modes. Foremost among these is IBM® watsonx™, our cloud-native AI and data platform, which offers 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 open-source platforms such as Red Hat® OpenShift® AI and seamless integration with our partners’ products.
IBM launched watsonx to help businesses capitalize on the opportunities of generative AI and foundation models. Watsonx consists of IBM® watsonx.ai™, IBM® watsonx.data™ and IBM® watsonx.governance™. Watsonx.ai is a next-generation enterprise studio for AI builders to train, validate, tune and deploy both traditional machine learning and new generative AI capabilities powered by foundation models through an open and intuitive user interface. Watsonx.data is our data repository based on a lakehouse architecture and open data formats designed to manage enterprise data for foundation models. The third component is watsonx.governance, anticipated to be available in December, 2023, which is a powerful set of tools to specify and manage enterprise-wide governance processes and control risk.
Looking ahead, a retailer might use watsonx.data to help tap into large amounts of disparate, unstructured customer data and build models in watsonx.ai to leverage recommendation algorithms for personalized shopping recommendations. With customer consent, based on past purchases and browsing behaviors, retailers could create virtual try-on tools and develop interactive shopping assistants. Once available, watsonx.governance could be integrated into this process to help retailers manage customer data ethically and responsibly.
With these tools at their disposal retailers are well-positioned to embrace generative AI as an integral part of their strategies and will be equipped to navigate the increasingly complex and fast-paced consumer landscape.
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