Abstract
In today’s data-driven business landscape, organizations are increasingly turning to advanced analytics and predictive modeling to drive decision-making. However, many are still experiencing a gap between model implementation and measurable business outcomes. This research explores how generative AI can bridge this gap by enhancing traditional data science approaches to deliver more significant ROI. Drawing from over a decade of experience implementing high-impact data science solutions across e-commerce, job platforms, cybersecurity, and retail industries, this talk will demonstrate how generative AI can transform conventional analytics workflows. Attendees will learn how AI-augmented models can accelerate A/B testing, enhance lead scoring precision, and provide deeper customer journey insights—all illustrated through real-world case studies that have delivered measurable business improvements including 35% YoY growth in core metrics and millions in incremental revenue. The session will provide practical frameworks for seamlessly integrating generative AI into existing data science practices, addressing common implementation challenges, and establishing metrics to quantify business impact. Whether you’re a data scientist looking to enhance your modeling toolkit, a product manager seeking to improve decision velocity, or an executive focused on maximizing analytics ROI, this presentation offers actionable strategies for leveraging generative AI to transform data science from a technical function into a strategic business driver.
Presenters
Vijaya Chaitanya PalankiSr Manager Decision Science, Data, Glassdoor, Texas, United States
Details
Presentation Type
Theme
KEYWORDS
Generative AI, Predictive modeling, Data science ROI, Business intelligence
