This teaching case examines the role of machine learning, deep learning, and artificial intelligence algorithms in the development and operation of self-driving cars. Using examples such as Waymo and Tesla, it explores how autonomous vehicles collect, process, and respond to real-time data through sensor systems, computer vision, object detection, and neural networks. The teaching case compares the functions of machine learning and deep learning in autonomous driving, emphasizing their importance in decision-making, pedestrian detection, traffic navigation, and safety improvement. It also discusses the potential benefits of autonomous vehicles, including increased convenience, reduced traffic accidents, improved fuel efficiency, enhanced accessibility, and more efficient transportation systems. At the same time, the teaching case addresses major concerns involving public trust, legal liability, cybersecurity, data privacy, infrastructure readiness, job displacement, and performance limitations in unusual driving conditions. By examining current applications and future possibilities, the teaching case argues that self-driving cars represent both a major technological advancement and a complex social challenge. Continued progress will depend on reliable algorithms, strong data security, regulatory guidance, public confidence, and responsible implementation.
This teaching case discusses the benefits, barriers and options for implementing novel drone technology in the construction industry. It supports readers in evaluating and justifying investments in innovative technologies and navigating the barriers to their implementation, anchoring the discussion in concrete examples of drone implementation in the construction industry. The case is based on a literature review and in-depth interviews of nine construction professionals in Finland, focusing the case geographically in Europe due to the common regulatory environment for drones in the area. The case demonstrates how drones have already been proven to achieve significant time and cost savings in various construction tasks but require technology managers to counter various organizational, regulatory and technological barriers to realize benefits from the investments. Specific guidance is given in the case for estimating costs and benefits for the drone implementation and thus justifying investments in novel drone technology.
Digital transformation has become a strategic priority for banks seeking to improve operational efficiency, strengthen controls, and remain competitive. In highly regulated environments, however, technology projects cannot be evaluated on operational merit alone; they must also satisfy regulatory, security, audit, and governance requirements. This teaching case examines the implementation of an outsourced Real-Time Gross Settlement (RTGS) high-value payment processing system at ‘Treasury Bank’, a large commercial bank, and traces how compliance shaped decision-making across the entire project lifecycle. What began as a seemingly straightforward automation of a manual, email- and paper-based treasury process evolved into a broader organisational transformation involving Compliance, Risk Management, Information Security, System Audit, Legal, and Data Governance functions. The case follows five implementation phases – project assessment, vendor assessment and business approval, system development, testing and validation, and go-live – showing how governance reviews influenced vendor selection, security assessments, audit requirements, and final approvals. Drawing on interviews with business and IT stakeholders directly involved in the project, the case highlights both the benefits of embedding compliance throughout the transformation, including stronger controls, greater transparency, improved auditability, and higher system quality, and the challenges this approach created, such as additional reviews, increased coordination, and extended timelines. It concludes with the strategic dilemma facing senior management: how to maintain robust compliance and governance while keeping digital transformation responsive and timely. The case suits undergraduate and postgraduate courses in Information Systems, IT Governance, Digital Transformation, and related fields.
JioHotstar was formed through a US$8.5 billion joint venture between Reliance Industries Limited and The Walt Disney Company. Within a year of its launch, it reshaped the Indian digital entertainment industry and emerged as India’s largest digital entertainment platform. The case traces how the Reliance–Disney joint venture led to the formation of JioHotstar and highlights the strategic moves and technological innovations that contributed to the platform’s success. It examines how JioHotstar built a technology-enabled digital entertainment ecosystem by integrating premium content, live sports, artificial intelligence, advanced streaming technologies, and diversified monetization strategies. It also highlights how JioHotstar is changing sports broadcasting and competing with traditional broadcasters. The case further assesses JioHotstar’s competitive position against global and domestic over-the-top (OTT) platforms. By examining JioHotstar’s rapid growth and the key factors that contributed to its market leadership, the case offers insights into the changing dynamics of India’s digital entertainment industry. It also examines the challenges of sustaining this leadership, highlighting the need to balance continued innovation, consumer engagement, and profitable growth.
This teaching case examines how Starbucks sought to redesign its store operations as digital ordering, artificial intelligence (AI), and algorithmic technologies became increasingly embedded in its business. Mobile ordering enhanced customer convenience but also intensified operational pressures as digitally generated demand interacted with store capacity, extensive customization, staffing constraints, and the coffeehouse experience. The case places students in the position of Brian Niccol, Starbucks’ Chairman and Chief Executive Officer, in late September 2025. Niccol initiated the Back to Starbucks turnaround, including menu simplification, increased staffing, store improvements, and renewed emphasis on customer experience. At the same time, Starbucks was deploying technologies such as Smart Queue, Green Dot Assist, automated inventory counting, and a next-generation point-of-sale system. The unresolved decision concerned the operating logic that should guide the next phase of Starbucks’ digital transformation. Students evaluate four strategic paths: digital-first standardization, capacity-synchronized digital operations, a format-differentiated network, and a partner-augmented technology model. The case enables students to examine how technology redistributes operational roles, the choices between automation and human augmentation, and the implications of algorithmic coordination for frontline discretion and control. Students ultimately design and justify a technology-enabled operating model that addresses trade-offs among scalability, operational performance, employee discretion, customer convenience, and Starbucks’ coffeehouse experience.
