Generative AI: Future-Proofing the Grocer’s Industry
At a Glance
- Grocery Doppio hosted "AI-in-Grocery" virtual event with game-changing discussions.
- The evolving grocery landscape has vast opportunities and potential in the realm of generative AI for grocers to capitalize and enhance customer experience and boost sales.
- Discussion was led by our expert panelists, Shish Shridhar(Microsoft),Deepak Jose(MARS),Adil Ladhani(WynShop)and Gaurav Pant(Grocery Doppio)
Grocery Doppio’s AI in Grocery virtual event explored the profound impact of AI on the grocery industry and what is next for the disrupting technology.
In our recently published report, "The Times They Are A-Changing: Impact of AI in Grocery," we uncovered that digital influence played a significant role in 69% of all grocery sales in 2023, signaling a transformative shift towards omnichannel experiences. To succeed in this evolving landscape, grocers must undergo substantial transformations in supply chain efficiency, store operations, marketing, and merchandising.
AI integration across all functions is a crucial catalyst for these changes, with a projected increase in value to the industry of $113 billion over the next two years. Operational enhancements, particularly in supply chain and merchandising, account for a significant portion of this value at $97 billion. With 74% of grocery tech executives actively seeking AI capabilities in new software, understanding the potential of generative AI and how grocers can leverage its capabilities has become essential.
On Day 1 of the highly anticipated AI in Grocery event, we hosted three exceptional speakers who provided invaluable insights into generative AI. Shish Shridhar, global retail lead, Microsoft; Deepak Jose, global head of data science, MARS; and Adil Ladhani, SVP R&D, Wynshop; and Gaurav Pant, chief insights officer, Incisiv, shared their expertise on how generative AI holds the game-changing potential to revolutionize the grocery industry.
Insights from Industry Leaders: Demystifying Evolution and Value of Generative AI
During the fascinating discussion, the panelists delved into generative AI's evolution and profound transformation and its implications for the grocery sector. The conversation explored the significant impact of generative AI on operational efficiency and its practical application for grocers. The panel examined the nuances that grocers can extract from this technology, identified crucial use cases that can be tested, and gained insights into the recommended approach for embracing and leveraging generative AI. Below are some of the highlights of the conversation:
Shridhar shed light on the evolution of AI, highlighting its significant advancements and transformative functionality. Initially, AI focused on automating business rules to make decisions based on predefined criteria. Subsequently, machine learning and deep learning emerged, enabling systems to learn from data patterns and generate new content. This evolution led to the development of generative AI, a technology that is revolutionizing creative content generation and grocers’ approach to solving business challenges.
Within the dynamic landscape, Shridhar emphasized two crucial areas for grocers to achieve success:
He stressed the importance of aligning unique business challenges with the capabilities offered by generative AI. This strategic alignment empowers grocers to unlock growth opportunities and enhance operational efficiency. Shridhar highlighted the significance of prioritizing internal use cases and technology that align with specific business objectives. By focusing on these areas, grocers can implement generative AI solutions in a targeted and impactful manner.
He emphasized the need for a balance between harnessing the transformative power of generative AI and addressing ethical considerations associated with its use.
Jose emphasized the significance of a strategic framework that revolves around three key questions: "How can we do things?", "How can we do things better?" and "How can we do better things?". This framework helps guide the integration of generative AI into various aspects of the grocery industry. For instance, incorporating generative AI into chatbots enables grocers to unlock hyper-personalization capabilities and revolutionize customer experiences. Deepak further elaborated on three operating models that grocers can explore when leveraging generative AI
- External Solutions: This model involves using external solutions without sharing internal data. Grocers can still benefit from cleaning and utilizing external data to enhance their operations.
- Internal Solutions: Grocers can build custom solutions using their internal data, particularly in areas such as knowledge management. Leveraging technologies like large language models (LLM) on top of existing data foundations can yield valuable insights.
- Hybrid Model: This approach integrates both internal and external solutions. It combines internal data with external resources to maximize the potential of generative AI.
He also highlighted the importance of responsible usage of generative AI and the ongoing exploration of ethical considerations. The focus is finding ways to effectively harness generative AI capabilities while ensuring ethical and responsible practices are in place.
Ladhani believes that true innovation lies not in the technology itself but in its democratization and accessibility to a broader consumer market. The power of generative AI lies in its ability to open doors that were once only accessible to data scientists and analytics teams. It enables individuals, even those without technical expertise, to engage in previously unimaginable tasks. This shift towards democratization also extends to analytics, where the goal is to make it accessible to all users, empowering them with self-service capabilities.
Personalization is crucial in e-commerce, allowing for nuanced conversations and personalized recommendations based on various factors. Another vital aspect is supporting head office users with self-service analytics, automating the interpretation of information. Lastly, composable commerce is vital, providing an open ecosystem that allows grocers, brands, and partners to build and expand upon e-commerce solutions through public APIs and flexible CMS components. The platform should offer a foundation while enabling customization to meet individual needs.
Empowering Grocers: Addressing Talent Challenges, Integration Strategies, and Evolving Software Procurement in the Grocery Industry
One of the most significant concerns examined was the need for individuals to upskill themselves and stay relevant in an era where AI is rapidly transforming job landscapes. 82% of grocers believe AI will be important in the future, but only 9% have the analytic talent to meet their future needs. This raises important questions about acquiring the necessary skills and staying ahead of the evolving technology. Since generative AI is a relatively new field, individuals are curious about the most effective ways to upskill. The discussion highlighted the need for a comprehensive approach to evaluating talent, as traditional resumes may only partially capture the potential of individuals with skills in this emerging field.
Shridhar said there is a learning curve for everyone involved, given the novelty of generative AI and the relatively recent democratization of the technology. As we explore this new frontier, it becomes crucial to actively engage and familiarize ourselves with generative AI through practical use. One way to do this is by diving into and experimenting with the technology firsthand. Developers, in particular, can leverage available APIs to gain hands-on experience. Additionally, there are numerous tutorials and resources, such as those offered by Microsoft's learn.microsoft.com, that can aid in understanding and mastering generative AI. Notably, prominent figures like Andrew Yang have also developed specialized courses which can provide valuable insights and preparation. In this evolving landscape, continuous self-learning remains a potent force for personal growth and proficiency in generative AI.
Jose said that for organizations to drive successful implementations, they should focus on three critical areas. First, the conversation should shift from technology and data to understanding the business problems that can be solved. Organizations can prioritize and drive value effectively by starting with the business problem first and then aligning the appropriate technology. Second,, having the right mindset is crucial for data and analytics practitioners. Clarity on business problems and the ability to prioritize them enables practitioners to consistently deliver value to the organization, regardless of changing technologies.
Additionally, investing in a connected data foundation is essential. And adopting the concept of agile and innovative teams, like Amazon's "two pizza teams," is beneficial for large organizations. These three recommendations offer a robust framework for organizations aiming to create successful implementations.
Navigating the Billion Dollar AI Revolution: The Critical 90-Day Action Plan for Grocery Retailers and Essential Steps for Individuals Embracing the Resilient AI Era
Generative AI is a transformative technology with great potential for grocery retailers and individuals. To set things into motion, developing a 90-day action plan is crucial. Our esteemed panelists provided key takeaways to guide this process.
Shridhar recommends that companies focus on understanding the capabilities of tools like ChatGPT and determine how to apply them to address specific business challenges. The key priority is to map these capabilities to address the most pressing business needs and prioritize their implementation. Prioritizing internal productivity use cases is recommended before moving on to consumer-oriented use cases.
Ladlani emphasized the importance of conducting a proof-of-concept (POC) centered around customer-facing personalization. This approach aligns with the broader consensus on prioritizing and aligning AI initiatives with business objectives as the first step. It is widely acknowledged that internal use cases tend to yield more immediate success in terms of return on investment (ROI) compared to consumer-oriented applications. However, Ladlani highlighted the value of exploring customer-facing POCs while maintaining realistic expectations.
Deepak recommends embracing Mother Teresa's quote to scale generative AI: "Do small things with great love." Focus on a specific area, be passionate, and ensure success. This serves as a launchpad for scaling AI capabilities. Whether you are an organization embarking on a proof-of-concept (POC) or an individual seeking to build expertise, the key is to find that specific area where you can learn and excel, laying a solid foundation for further growth and development.