
This policy paper examines how artificial intelligence can help address India’s deeply strained healthcare system—marked by workforce shortages, infrastructure gaps, and widening inequities—when deployed through purposeful, cross-sector collaboration rather than isolated technological adoption. It situates AI as a catalyst for change across diagnostics, predictive analytics, operations, and personalized care, while emphasizing that technology alone is insufficient without shared governance, trusted data ecosystems, and institutional alignment.
Drawing on global collaboration models and Indian case studies from both the public and private sectors, the paper outlines how partnerships among government, healthcare providers, technology firms, and research institutions are already delivering measurable impact. It concludes with a three-pillar strategic roadmap focused on infrastructure and policy, ecosystem building, and workforce empowerment—offering policymakers and healthcare leaders a practical framework for leveraging AI to build a more resilient, equitable, and inclusive healthcare system for India

This research paper examines why blockchain technology has yet to achieve widespread, sustained success despite significant investment, innovation, and early promise. Drawing on a multi-stakeholder discussion among practitioners, investors, academics, and policymakers—supported by an extensive review of academic literature—the study identifies seven systemic barriers to adoption, including the decentralization paradox, technical trade-offs embodied in the blockchain trilemma, enterprise adoption constraints, misaligned investment models, regulatory uncertainty, and persistent confusion between infrastructure- and application-layer development.
To clarify these challenges, the paper introduces a novel taxonomy distinguishing between organizations that use blockchain as an enabling tool and those whose business models are built on blockchain itself, arguing that these two categories face fundamentally different success criteria and risk profiles. The analysis concludes that blockchain’s limited success is driven less by technical immaturity than by misalignment between its decentralized ethos and prevailing business, governance, and investment structures. The paper closes with practical recommendations for entrepreneurs, investors, enterprises, and policymakers, outlining pathways toward more realistic expectations, tier-specific evaluation frameworks, and sustainable models for blockchain adoption and impact.

This position paper argues that supply chain transparency failures persist not because of inadequate technology but because dishonesty remains economically rational. It examines how centralized audits, digital tracking tools, and voluntary certifications repeatedly fail when verification depends on the integrity of the very actors being verified. Drawing on real-world cases from fashion, finance, healthcare, and food systems, the paper exposes how engineered opacity enables wage theft, fraud, and systemic exploitation at global scale.
The paper proposes a new economic architecture for trust: a three-party verification system combining blockchain-based incentives, distributed AI verification, and reputation-based stakes to make honesty more profitable than deception. By aligning economic incentives across independent verifiers, producers, and buyers, the framework enables continuous, scalable, and enforceable transparency. Intended for policymakers, industry leaders, and investors, the paper positions verification infrastructure as a strategic asset—transforming transparency from a moral aspiration into an economic imperative and competitive advantage.