E-commerce has seen a massive transformation in recent years, with artificial intelligence (AI) and data science playing a crucial role in shaping customer experiences, optimizing operations, and driving business growth. To understand how these technologies are revolutionizing the industry, we spoke with Sabarna Choudhuri, a senior IEEE member, data science expert, and recognized thought leader in AI and machine learning (ML).
With extensive experience in AI-driven applications, Sabarna Choudhuri has contributed to the advancement of data science in e-commerce, helping businesses leverage machine learning for personalized recommendations, fraud detection, and supply chain optimization.
Sabarna, thanks for joining us today. What inspired your journey into AI, ML, and data science?
Thanks for having me. Since childhood, I’ve been fascinated by problem-solving and logical reasoning. My academic and professional journey naturally led me to AI and data science. These fields allow us to derive insights from vast amounts of data and build intelligent systems that can enhance decision-making, improve efficiency, and even automate complex tasks.
E-commerce, in particular, is an industry where AI and data science have made an immense impact, making shopping experiences more seamless, secure, and personalized for customers.
How is AI currently reshaping the e-commerce landscape?
AI is transforming e-commerce in multiple ways. Some of the most notable applications include:
- Personalized Recommendations: AI-driven recommendation engines analyze user behavior, past purchases, and browsing history to offer relevant product suggestions. This boosts customer engagement and increases conversion rates.
- Chatbots and Virtual Assistants: AI-powered chatbots provide 24/7 customer support, handling queries efficiently while reducing operational costs.
- Dynamic Pricing: Machine learning models analyze market trends, competitor pricing, and demand patterns to adjust prices dynamically, ensuring competitive advantage.
- Fraud Detection and Prevention: AI algorithms identify fraudulent transactions by detecting unusual purchasing patterns, reducing financial risks for businesses.
- Inventory and Supply Chain Optimization: Predictive analytics help businesses manage stock levels, forecast demand, and prevent supply chain disruptions.
Data science is at the core of AI innovations. What are some of the biggest challenges in leveraging data for e-commerce?
The biggest challenges revolve around data quality, privacy, and real-time processing. Many businesses struggle with fragmented data sources, making it difficult to extract meaningful insights. Data privacy is another major concern, with increasing regulations like GDPR and CCPA requiring e-commerce companies to abide by PII regulations and ensure responsible handling of customer data.
Another challenge is real-time data processing. E-commerce operates in a fast-paced environment where businesses need instant insights for fraud detection, customer service automation, and demand forecasting. AI-driven big data solutions are helping overcome these challenges, enabling businesses to process vast amounts of information in real time.
How do you see the role of AI and ML evolving in e-commerce over the next five years?
AI and ML will continue to redefine the industry. In the next five years, we can expect:
- Hyper-personalization powered by AI, where shopping experiences will be tailored to individual preferences in real time.
- Voice commerce will grow significantly, with AI-driven voice assistants handling transactions.
- Augmented reality (AR) integration, allowing customers to “try before they buy” using AI-powered visual recognition.
- Automated supply chains with self-learning algorithms optimizing logistics and inventory management.
What advice would you give to professionals looking to build a career in AI and data science?
Stay curious and keep learning. The field of AI is evolving rapidly, and professionals need to continuously upskill by exploring emerging technologies like deep learning, NLP, and edge AI. Networking with experts, contributing to research, and participating in hackathons can also help accelerate career growth.
For women in tech, I strongly encourage breaking stereotypes and pursuing leadership roles in AI and data science. The industry needs more diverse perspectives, and we should empower the next generation of women in STEM.
AI and data science are at the forefront of e-commerce transformation, making shopping more intuitive, efficient, and secure. As AI continues to evolve, industry leaders like Sabarna Choudhuri are driving innovation, ensuring businesses stay ahead in the competitive digital marketplace.
