Deepak Agarwal will outline LinkedIn’s holistic approach to shaping the future of work through AI, a vision anchored in building intelligence that is trustworthy, capable, and efficient. He will delve into three foundational pillars driving this transformation: personalized recommendations, semantic search, and AI agents. Drawing from his personal journey and innovations such as the Hiring Assistant, Deepak will demonstrate how these systems are designed to empower members, support recruiters, and scale opportunity through responsible, human-centric AI. Grounded in the power of LinkedIn’s Economic Graph, this talk will explore how AI is not only connecting professionals with the right jobs but also redefining how work gets done in a rapidly evolving world.

As Global Capability Centers shift from cost arbitrage to value creation, can they build in‐house AI competencies to become true innovation engines, or will plug-and-play agentic SaaS solutions render them obsolete? Industry heads debate the strategic roadmap for GCCs to invest in internal AI talent, platforms, and IP generation.

With ambitions to close the gap with Silicon Valley and Beijing, will India’s combination of academic talent, vast data, and policy support propel it to AI leadership, or will gaps in research funding and commercialization slow that ascent? Thought‐leaders discuss the ingredients—investments, regulations, talent pipelines—needed to transform the nation into an AI powerhouse.

Core Idea: This topic will focus on how AI is enabling a shift from traditional, generalized farming to data-driven, precise agricultural practices in India, with UPL SAS at the forefront of this transformation. Outline: I. Introduction: The Imperative for Precision in Indian Agriculture ● Current Landscape: Challenges faced by Indian farmers (fragmented landholdings, climate variability, resource scarcity, pest & disease outbreaks). ● The Promise of AI: How AI can address these challenges by enabling data-driven decision-making. ● UPL SAS's Vision: Empowering Indian farmers with accessible, scalable AI-powered solutions. II. Revolutionizing Traditional Practices with AI at UPL SAS ● Limitations in traditional practices: Generic fertilizer application, limited understanding of soil health, challenges with manual inspection, delayed identification of issues, optimized water management, flood irrigation, inefficient water usage. ● AI Revolution: AI-driven soil testing (e.g., UPL's focus on soil health, use of sensors/data analytics), personalized nutrient recommendations, optimizing fertilizer use (reducing waste and cost) focusing on Smart Soil Management. ● UPL SAS Solution: Discuss specific platforms or services that integrate AI for soil analysis and recommendations. ● AI Revolution: Drone-based imaging, satellite data analysis, AI algorithms for early detection of pests, diseases, and nutrient deficiencies. Predictive analytics for crop stress emphasizing on Intelligent Crop Monitoring & Health ● UPL SAS Solution: Highlight solutions like AI-powered pest risk prediction APIs (as developed with Microsoft) and remote sensing services that provide real-time crop insights and targeted intervention advisories. ● AI Revolution: Smart irrigation systems leveraging weather forecasts, soil moisture sensors, and AI to deliver precise water amounts, reducing water consumption (e.g., UPL's Zeba technology). ● UPL SAS Solution: Elaborate on how UPL SAS's solutions, potentially integrated with AI for predictive needs, are aiding in water conservation and sustainable practices. III. Impact on Farmers' Lives and the Agriculture Industry ● Increased Productivity and Yields: Quantifiable improvements in crop output due to optimized inputs and timely interventions. ● Reduced Costs and Enhanced Profitability: Savings on fertilizers, pesticides, water, and labor due to efficient resource allocation. Discuss how AI helps in unlocking affordable financing options for retailers via credit scoring models. ● Climate Resilience: How AI-driven insights help farmers adapt to changing weather patterns and mitigate climate risks. ● Empowering Smallholder Farmers: Making advanced technology accessible and easy to use for the majority of Indian farmers. Mention UPL SAS's focus on "Digital Agriculture Mission" and "Namo Drone Didi" as examples of empowering initiatives. ● Data-Driven Market Access: How AI helps in forecasting demand and optimizing supply chains for better market linkages and price realization (e.g., nurture.retail platform). IV. The Road Ahead: Future of AI in Indian Agriculture with UPL SAS ● Scaling AI Adoption: Challenges and opportunities in wider implementation. ● Integration of AI with Biosolutions: UPL's strategy of combining traditional crop protection with natural solutions for holistic farming. ● "OpenAg" Philosophy: Collaborative approach to innovation and partnerships in the agritech ecosystem. ● UPL SAS's Commitment: Continued investment in R&D and digital platforms to drive sustainable agricultural growth in India.