Leveraging AI, ML, and Gen AI in Automotive and Financial Services: Data-Driven Approaches to Insurance, Payments, Identity Protection, and Sustainable Innovation

Abstract

Digital native and tech-savvy ‘born-digital’ or netizens are coining new ethics, norms, and behaviors all at once based on AI and ML algorithms that are ‘self’-bagging their couriers, nudging them for politically sensitized and personalized information, provisioning for bedrooms as Primordial soup, and shatterproofing their gizmos. We dub the born-digital netizens as Gen AI and the future as the Hybrid World, where humanity and ‘self’ will co-exist integrating the ‘self’ conditioned in algorithmic dreams. We extend this narrative to discuss the design domains of IoT, wearables, smart apparel, VR/AR MR, Industry 4.0, Reinforcement Learning, Smart U, Big data analytics, gossip-crawling, and MotionBI applications. This elaborates on our prior work on IoT, AR/MR, and digital twin technologies with 70 elements of AI and ML algorithms, thereby producing a tapestry of digital twins in multifarious domains, specifically financial services and automotive. The digital twin algorithms not only nudge the design and decision-making processes but also enable innovation in products, services, and business models through smart data-driven decisions, optimizations, simulations, and predictions, leading to productive, efficient, resilient, and competitive organizations. We use these designs to identify ethical, responsible, and sustainable implications and regulations for future-of-work, future-of-society, and future-of-planet. At a broad level, we make policy suggestions for GDPR, Autonomous Vehicles, computer-aided design, Regtech regulatory compliance tech, SME small and medium enterprise Finance 3.0, data assets, and data-driven decisions.