Generative artificial intelligence (GenAI) tools such as Azure OpenAI have gained a lot of attention in recent months, and there is a growing consensus that these technologies can revolutionize the retail industry. The most well-known GenAI application is ChatGPT. This is an AI agent that can generate human-like conversational responses to queries. Other well-known GenAI applications generate descriptive text to summarize or query large amounts of data, generate images and videos in response to descriptive phrases, and generate complex code based on natural language questions. You can even generate
GenAI technology offers great potential benefits for retail organizations, such as rapid price adjustments, customized behavior-based incentives, and personalized recommendations based on search and customer preferences. These technologies can create new written, visual, and auditory content based on natural language prompts or existing data. Their advanced analytics capabilities help you determine better locations for new stores or where new investments can be made. Generative AI chatbots can provide faster and more relevant customer assistance, increase customer satisfaction, and potentially reduce costs and churn. To better understand how retailers can benefit from generative AI applications, we talked about: James Caton, Microsoft, Data and Artificial Intelligence Practice Leaderand Girish Phadke, Technology Head, Microsoft and Cloud Platforms, Tata Consultancy Services (TCS)James and Girish described three ways generative AI could transform retail. Accelerate innovation, create better customer experiences, and drive growth.
How can generative AI accelerate retail innovation?
James Caton: We’re already seeing a lot of data-driven innovation in the industry. The Microsoft Azure OpenAI service, which provides access to OpenAI’s large language models, enables deeper exploration and deeper questions of data. Frontline employees can “chat with the data” to conversationally query inventory, shipping options, and more, see responses in charts, and seek trend analysis and deeper insights. can.
Basically, you provide an assistant or co-pilot to help you with your work. Imagine having multiple assistants parsing data, querying data, and displaying data reports and visual charts. And you can send the co-pilot back and say, ‘Look here,’ ‘I want more information.’ As a retail sales manager, OpenAI enables you to develop more innovative solutions, more customized strategies, and more personalized experiences.
How does Generative AI Conversation Flow enable a more engaging customer experience?
Girish Padke: Existing call center tools can be conversational and have access to a 360-degree view of the customer, but how far back can you go and what data can be processed to answer customer queries? is limited.
New generative AI models can dig deeper into historical information, summarize it, and present it in human-like conversations. These models can pull data from multiple interactions and sources from vast amounts of information to create the best response to answer a specific customer question. Essentially, it tailors responses based not only on its vast knowledge base of data, but also on individual customer preferences.
Can you give an example of how one of your customers has benefited from using OpenAI to process and analyze vast amounts of information?
Katong: CarMax reviews millions of vehicles. The challenge for new buyers was that there were too many reviews to really understand why people liked or disliked a particular vehicle. Analyzed and presented a summary. When a customer was looking at a particular make and model, the Azure OpenAI service summarized the review and presented the top 3 reasons people liked it and the top 3 reasons they didn’t like it. The technology summarizes millions of comments so customers don’t have to, improving customer experience and satisfaction.
Are there steps for retailers to prepare for OpenAI and similar tools?
Katong: If retailers want to take advantage of these capabilities, the first thing they need to do is move their data to the Microsoft Cloud. Partners like TCS can then help develop his case for preferred uses, such as applying generative AI to inventory and sales data, or helping develop more customized marketing campaigns. TCS knows the industry as well as most retailers. They understand technology, how to manage and migrate data, and how to optimize to take full advantage of new capabilities.
Padque: I understand that this is new technology. Retailers can be cautious. You can start by extending existing capabilities such as Azure ChatGPT to be more comprehensive, and adjust your governance model as you learn more about your data and processes. As trust grows, you can start automating larger deployment mechanisms.
How long does it typically take for an organization to see a return on investment from generative AI?
Padque: With the right strategy and the right set of use cases, the system can start generating positive ROI very quickly. TCS offers a six-week discovery assessment to assist in the development of vision and strategy. Within 12-16 weeks of adopting Azure OpenAI services, organizations can have a more scaled-out implementation.
Should retailers adopt generative AI technology now if they want to stay competitive?
Padque: I think we risk being left behind if some retailers choose to ignore this technology. Early adopters may gain a competitive advantage. This technology is disruptive in nature and will have a huge impact on many industries, including retail.
Katong: OpenAI is the fastest application with 100 million users, faster than Facebook, Instagram or WhatsApp. The risk of a late adopter is that competitors may adopt it and gain a competitive advantage. It is very widely adopted and very rapidly.
Learn how to master your cloud transformation journey with TCS and the Microsoft Cloud.
TCS
Girish Phadke, TCS Technology Head, Microsoft and Cloud Platforms
Girish Phadke leads the Edge to Cloud Solutions, AI and Innovation focus areas within the TCS Microsoft business unit. He advises customers on next-generation architecture and business solutions. He tracks and incubates new technologies through his TCS Microsoft Business Unit Innovation Hubs around the world. Girish is based in Mumbai, India and in his spare time he loves watching science fiction movies.
https://www.linkedin.com/in/girish-phadke-ab25034/
microsoft
James Caton, Practice Leader, Data and Artificial Intelligence, Microsoft James Caton is an AI practice leader at Microsoft, helping global system integrators build sustainable Azure artificial intelligence businesses. He has held technical and commercial leadership at his software companies SAS and IBM, as well as leading India’s smart city business at Larsen & Toubro Construction. James lives in Ave Maria, Florida with his wife and his three daughters. https://www.linkedin.com/in/jmcaton/
