Business Transformation Requires Transformational Leaders

There is perhaps only one thing more crucial to secure than money: information. The heavy burdens associated with securing the authenticity and history of data are well-known to several sectors.

Based on the demand for Agile skills in the workplace, it is quite clear that leaders across the globe are coming to rely more and more on Agile principles and practices to achieve their goals. What makes some of these leaders successful with their Agile adoptions while other leaders seem to struggle? What is going on in these organizations?

Keng Siau and Weiyu Wang examine prevailing concepts of trust in general and in the context of AI applications and human-computer interaction in particular. They discuss the three types of characteristics that determine trust in this area: human, environment, and technology. They emphasize that trust building is a dynamic proc­ess and outline how to build trust in AI systems in two stages: initial trust formation and continuous trust development.

The authors emphasize the need to connect and collectively harness advances in different elements of AI and outline autonomous business entities as examples of convergence of AI. The authors discuss the application of AI, not only to improve business operations, but also for product adaptation and to enable and support business model innovations, thereby making the entire business “smart.” They also explore “data labs” and “data factories,” which facilitate business model innovation. Finally, the authors argue that while AI-driven, radical automation of businesses will replace human work in some areas, humans will remain relevant in others.

Raj Ramesh discusses business model transformation with a focus on the insurance sector. He covers the potential of AI in insurance and then expands his discussion to the ingredients necessary for AI to provide good value to the business in any sector.

Vipin Jain and Seema Jain discuss the opportunities emerging from artificial intelligence and how cognitive technologies will fundamentally change the way government works. They outline how the US public sector is currently adopting and planning to embrace AI and ML in various applications. They also highlight priorities for federally funded research in the US. To help developers in conceiving and developing AI appli­cations, the authors present an AI adoption frame­work and briefly discuss the categories of AI-branded services available from leading cloud service providers. They finish with a consideration of whether AI is a job creator or a job destroyer.

Hemamalini Kumaran, Prema Sankaran, and Raj Gururajan discuss how AI is transforming the banking sector. They outline how Indian and US banks are using AI to gain significant benefits and offer an enhanced customer experience. The authors examine the key drivers that inspire banks to embrace AI, the challenges involved in implementing it, and what needs to be considered in applying AI to best serve customers.

This article draws your attention to the design, devel­opment, deployment, and refinement of cognitive computing systems (CCSs). While CCSs are deployed in a variety of fields yielding benefits exceeding expectations, there are also major failures. Lack of appreciation for the differences inherent in developing a CCS versus a traditional software system is key to these failures. To assist in developing successful CCSs and to derive benefits from them, the authors offer a set of nine key recommendations based on their examination of over two dozen systems. They conclude that CCSs will be a dominant technol­ogy that will permeate all business operations for the foreseeable future.