Soumya, a seasoned business technology executive with 17+ years in strategic planning across FMCG, consumer healthcare, food & beverages, and telecom industries. She is expert in leveraging digital, data, and analytics technologies to drive large-scale change and innovation. Renowned for empowering teams and using technology as a competitive advantage.

In a recent conversation with the Global Woman Leader Magazine, Soumya explores how AI and machine learning are reshaping the consumer goods sector in Asia, highlighting key trends and disruptions. She examines essential factors for successful AI integration, innovative approaches for supply chain management, and strategies for leveraging AI to gain a competitive edge.

How are AI and machine learning currently transforming the consumer goods sector in Asia, and what are the most notable trends or disruptions you've observed in the market landscape?

These are exciting times; the world is more interconnected than before and is changing at a rapid pace. This had led to a need to transform and streamline various business processes. AI and machine learning are playing a huge role in making this possible.AI is being used to drive efficiency, innovation, and enhance customer experiences. Top disruptions that come to my mind are AI enabling real-time, autonomous planning in supply chain, AI-driven personalized consumer apps and tailored product recommendations, AI driven product innovation and enhanced online shopping experience through chatbots for customer service.

In your view, what are the key factors that organizations must consider when integrating AI and machine learning into their existing business processes to ensure they enhance overall business performance rather than just add complexity?

This is a great question. In my view, the key criterion for integrating any technology in business processes should be “value”created by doing so. Same is applicable for AI and ML as well. The value generated could be in the form of cost saving, business growth or increasing process effectiveness. Once the value goal is clear then one should identify the simplest way to achieve this without over complicating or over transforming. This requires very careful planning and a high level of collaboration between the business and technology teams. It is also important to have the right talent and ethical considerations while implementing AI and ML based initiatives. To keep it simple, the focus should always be on “What problem are we solving” rather than “Technology we are enabling”.

How can AI-driven insights be effectively used to not only predict consumer behavior but also to personalize and elevate the overall customer experience in the consumer goods sector?

I think both go hand in hand. Understanding the consumer is the only way to enhance their experience. For example, we know that ecommerce websites use AI algorithms to analyze customer behavior, including browsing history and previous purchases, to provide highly targeted product recommendations. This personalization increases the likelihood of purchases and hence enhances customer satisfaction. Similarly, Content Streaming platforms use AI to personally recommend what content to watch which in turn keeps us hooked.

In consumer good industry, first party data is being used to understand different customer segments better, companies can tailor their marketing strategies and product offerings to meet specific needs, leading to more personalized and effective customer interactions. Many companies use AI-powered chatbots to provide instant customer support and personalized assistance. These chatbots can handle a wide range of queries, from product information to order tracking, improving customer service efficiency and satisfaction.

What innovative approaches can AI and machine learning offer to streamline supply chain management and inventory control in the consumer goods industry, especially in the context of the rapid shifts in consumer demand?

Supply Chain is one of the areas where AI and ML have huge potential to transform. It is estimated that a value generation of 10% to 15% can be unlocked by reduction of inventory costs and improved sell-throughby integrating AI in supply chain area. AI is being extensively and effectively used in areas of Real-Time Demand Forecasting, Autonomous Supply Chain Planning, Predictive Maintenance, Enhanced Route Optimization, Inventory Optimization and Supplier Risk Management.

How can companies leverage AI to gain a competitive edge in the consumer goods sector, and what role does strategic foresight play in adapting to emerging technological advancements?

A lot is happening across industry in leveraging AI, so in order to gain a competitive edge one has to plan strategically. Technology adds value only when it is applied impactfully. The approach should be to look at the business strategy to establish clear focus areas where AI can provide a competitive edge and then prioritize use cases within these focus areas to move fast. It is also important to build capability within the organization to not only enable AI but also to use it in the right way. Lastly, ensure proper change management to bring in new ways of working along with the disruption.

Considering your experience across various industries, what cross-industry innovations or practices in AI and machine learning could be applied to the consumer goods sector to drive growth and efficiency?

I started my career with telecom sector in India and I think telecom sector has been a pioneer in using technology very early on to provide personalized offers to subscribers based on their usage pattern. This is a great example of understanding the consumer and providing them with the solution that they need. Telecom companies have been systematically storing usage data for every consumer and made very good use of that information to drive more business.

The consumer product industry have started to see such usage of first party data very recently and that too in limited pockets. Learning from telecom, consumer goods companies should give serious thought of generating, managing and storing first party data to harness its value using the technologies that are now available to us.