This study explores how AI-powered digital innovations are reshaping organisational accountability in a transnational governance context. As AI systems increasingly mediate decision-making in domains such as auditing and financial reporting, traditional mechanisms of accountability, based on control, transparency, and auditability, are being destabilised. We integrate the Technology Acceptance Model (TAM), Actor-Network Theory (ANT), and institutional theory to examine how organisations adopt AI technologies in response to regulatory, ethical, and cultural pressures that transcend national boundaries. We argue that accountability is co-constructed within global socio-technical networks, shaped not only by user perceptions but also by governance logics and normative expectations. Extending TAM, we incorporate compliance and legitimacy as key factors in perceived usefulness and usability. Drawing on ANT, we reconceptualise accountability as a relational and emergent property of networked assemblages. We propose two organisational strategies including internal governance reconfiguration and external actor-network engagement to foster responsible, legitimate, and globally accepted AI adoption in the accounting domain.

My journey through the intertwining worlds of computing and manufacturing began, unexpectedly, in the halls of the University of Illinois at Urbana-Champaign. Under the guidance of my doctoral advisors, Professors George McConkie and Chris Wickens, my fascination with technology deepened. McConkie's pioneering work in eye tracking, particularly its application during reading and perception, highlighted the dynamic dance between technology and human behavior. Meanwhile, Wickens bridged theoretical constructs with real-world applications, notably in aviation and driving, revealing how intricate systems influence human attention. Post-Ph.D., I joined Siemens Corporate Research in Princeton, NJ.

The internet has come a long way since its inception, from the static and centralized Web 1.0 to the interactive and social Web 2.0. Now, we are on the cusp of the next evolution of the internet, the decentralized and intelligent Web 3.0. The combination of artificial intelligence (AI) and Web 3 has the potential to transform the digital landscape and create a more intelligent, personalized, and secure decentralized web. In this blog, we will explore the concept of Web 3, the potential of AI to enhance Web 3, and the challenges and risks associated with AI in Web 3. Web 3, also known as the decentralized web, is the next evolution of the internet. It is a paradigm shift from the current centralized model of the internet, where large tech companies control the flow of information and user data, to a more decentralized, open, and community-driven internet.

Digital-industrial innovation can now prove its mettle. For the last ten years, digital-industrial innovation has been seen as the poor, unglamorous cousin of pure digital innovation. It arrived late to the party. Its applications were developed on factory floors, in what was looked down upon as "old" economy. General Electric GE, which pioneered what it called the Industrial Internet, found that attracting software talent was one of its biggest difficulties.

South Korean auto major Hyundai Motor Company has partnered TeamViewer, a leading global provider of remote connectivity and workplace digitalisation solutions to digitalise business operations and manufacturing processes for Hyundai Motor Group Innovation Center in Singapore (HMGICS). The partners will cooperate to maximise digitalisation benefits in HMGICS' smart factory using TeamViewer's augmented reality (AR) platform, which includes mixed reality (MR) and artificial intelligence (AI) capabilities. The platform will support assembly, maintenance, quality management, logistics, client experience projects and workforce training. They will also conduct joint research and development (R&D) activities in AR-powered smart factory operations, immersive digital experience for frontline workers and AI support for a future automotive factory. Overall, the partnership aims to drive increased productivity, accuracy, speed and safety of frontline production workers.

The covid-19 implications coupled with customer expectations have raised the need to go digital. As a result, retail stores have become experience centers than just store outlets in the digital transformation era. To provide an engaging customer experience and boost the marketing strategy, facial recognition has brought a whole new level of advancement in AI technologies. The Allied Market Research Report states that the "facial recognition market will reach $16.74 billion by 2030." And don't you find it fascinating if shoppers pay the bill at check-out by just representing a face, not any card or wallet?

Many companies struggle to reap the benefits of investments in digital transformation, while others see enormous gains. What do successful companies do differently? This article describes the five stages of digital transformation, from the traditional stage, where digital and technology are the province of the IT department, through to the platform stage, where a comprehensive software foundation enables the rapid deployment of AI-based applications. The ideal is the native stage, whose hallmarks are an operating architecture designed to deploy AI at scale across a huge, distributed spectrum of applications; a core of experts; broadly accessible, easy-to-use tools; and investment in training and capability-building among large groups of businesspeople. Over the past decade, Novartis has invested heavily in digital transformation.

Vistra, a major U.S. power producer, had a problem. For its plants to operate efficiently, workers had to continuously monitor hundreds of different indicators, tracking temperatures, pressures, oxygen levels, and pump and fan speeds -- and they had to make adjustments in real time. The process involved a huge amount of complexity, and it was too much for even the most skilled operator to get right all the time. To address this challenge, the plant installed an AI-powered tool -- a heat-rate optimizer -- that analyzed hundreds of inputs and generated recommendations every 30 minutes. That may not sound like much, but it translates into millions in savings as well as lower greenhouse gas emissions.

With 2020 well behind us, COVID-19's presence continues to linger worldwide. Of all the industries that have been forever changed by the impacts of the global pandemic, healthcare arguably has changed the most. With significant advances in technology and methods necessary to support the high demand for access to healthcare and the growing digitization of protected health information, the healthcare industry has evolved in novel ways to continue to deliver the same exceptional quality of service. As we press on into the future, it's critical to remain mindful of the trends driving healthcare technology in 2022. Although legacy software and infrastructure are critical to the success of modern hospitals and care centers, it's important that we consider how those systems can integrate with newer technologies or how they may eventually be replaced with more reliable systems. The focus should be on improving performance, productivity, efficiency, and security without sacrificing reliability or accessibility. If you're ready to explore the tech innovations driving the healthcare industry towards digital transformation this year, let's take a look at the most important technologies that have the potential to transform your organization.

Banks are turning to a range of new technologies to improve the customer experience and fend off competition from new players in the financial services marketplace. Banks today are operating in a highly dynamic economic and business environment, and the pressure is on to modernize their IT operations. They face some significant challenges. Low interest rates, along with the significant impact of COVID-19 (which increased credit risks), are reducing core profitability. Banks are looking for ways to reduce costs and grow revenue to counter increasing competition from Fintech firms and digital giants (Bigtechs).