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Generative AI in Consumer Goods: Insights from Unilever’s Arun Nandi

Arun Nandi from Unilever delves into the evolution and potential of AI in the consumer goods industry, emphasizing the balance between innovation and managing expectations.

In a recent session at Machinecon USA 2023, Arun Nandi, who leads data and analytics at Unilever, shared his perspective on the trajectory of artificial intelligence (AI) within the consumer goods giant. His insights offer a deep dive into the evolution, risks, and opportunities of AI in the consumer-facing industry.

The Evolution of AI at Unilever

Unilever, one of the world’s largest consumer goods companies, has been on an AI journey for several years. Nandi, who has been a part of this evolution, highlighted the company’s transition from descriptive and diagnostic analytics to predictive, prescriptive, and now cognitive analytics. Interestingly, he mentioned that they had been working on generative AI even before the term “Gen AI” became popular. While there’s a current hyper-focus on Gen AI, Unilever continues to harness traditional AI and machine learning methodologies that add significant value to the organization.

Balancing Expectations and Reality

One of the challenges Nandi pointed out is managing the expectations surrounding generative AI. Both leaders and consumers are fascinated by the technology, leading to both realistic and unrealistic expectations. It’s crucial for data and analytics practitioners to set a clear foundation on what Gen AI can achieve and where it can unlock value. There are areas where other AI methodologies might be more suitable than Gen AI.

Risks and Opportunities

In the consumer-facing industry, there are both risks and opportunities associated with AI. One of the primary risks is the potential overhype and unrealistic expectations from Gen AI. On the other hand, the opportunities are vast. Nandi emphasized the potential of Gen AI in enhancing existing products, rather than just focusing on creating new ones. He used an analogy, stating that while there’s always excitement around new products, it’s essential to think about how Gen AI can be integrated into existing solutions to make them more democratized.

In conclusion, Arun Nandi’s session provided a comprehensive overview of the role of AI in the consumer goods industry. He emphasized the importance of understanding the technology, managing expectations, and integrating AI into existing solutions to drive value. His insights are invaluable for anyone looking to understand the transformative potential of AI in the consumer goods sector.

AIM Research

AIM Research

AIM Research is the world's leading media and analyst firm dedicated to advancements and innovations in Artificial Intelligence. Reach out to us at info@aimresearch.co

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