Assessing the Business Impact of Artificial Intelligence

This research introduces two artefacts that contribute to the common understanding of Artificial Intelligence (AI) and aim to provide guidance for designing AI applications. On the one hand, the periodic table of AI structures the broad spectrum of AI technologies and an AI application design model supports the business-oriented conception of AI technologies. Both artefacts are key for the development of an AI impact analysis model to evaluate further organizational impacts and potentials for re-design. The research was motivated by the findings of a survey on AI application examples in a research consortium consisting of German, Swiss and Austrian bank and IT provider managers and a business user group of a Swiss private bank. Both artefacts showed to be helpful tools for change management and IT/business architects

Assessing the Impact of Artificial Intelligence on Fintech Business Models

Artificial intelligence technology is the foundation that has promoted the development of global business technology. The progress in the economic field in recent years has also led to the continuous development of e-commerce and the continuous improvement of artificial intelligence technology. The integration of the two in various fields and levels will become closer. E-commerce based on artificial intelligence technology makes e-commerce an inevitable trend towards a healthy development. This article discusses the impact of artificial intelligence payment methods on the electronic business model B2B, and sort out the application of AI in e-commerce

ChatGPT: The New Business Librarian?

With the early 2023 public release of ChatGPT, natural language models and generative artificial intelligence (AI) have been making waves across numerous industries and academic communities. Many are speculating on the impact it will have in the education industry, including libraries. Librarians may already be dealing with patrons whose inquiries are a result of information generated by AI, and some may be adopting the tool themselves to augment various work processes. This talk will briefly cover takeaways of an ongoing research project at the University of Notre Dame’s Thomas Mahaffey Jr. Business Library assessing the capabilities of ChatGPT when applied to research assistance questions in the Business subject areas. This talk will focus on some of the basic takeaways of the project which involved asking ChatGPT a sample of real research assistance questions asked at the business library between the years 2018 and 2022. On the whole, how well does ChatGPT fulfill the role of conducting business specific research assistance, and are there any ways that generative AI could ethically or efficiently be applied to Business Librarianship

Aware Adoption of Artificial Intelligence and Big Data: a Value Framework for Reusable Knowledge

Artificial Intelligence (AI) is changing the way decision-makers reason about complex systems: more information (re)sources, e.g. Big Data (BD), are now available, but decisions are not always based on reusable and explainable knowledge resulting from the direct interaction with data. Therefore, it is necessary to define new models to describe and manage this type of uncertainty. This contribution introduces a conceptual framework to deal with the notion of Value in AI-BD contexts, embracing both the multiplicity of Value dimensions and the uncertainty in their visibility as the foundations for a dynamic, relational representation of Value. The purpose is to provide ad hoc models to support Business Intelligence in assessing the impact of AI-BD projects. The framework design is based on abstract and highly scalable definitions to represent Value, even considering the interaction of different agents through comparison, combination, and update of states of knowledge. The focus on reusable knowledge is exploited in the relation between Human and Artificial intelligences, which is characterised by a non-classical form of uncertainty regarding data observability. The impact of the dynamic behaviour of Value dimensions on decision-making and potential application domains are discussed, with the aim to enhance the sustainability of AI-BD initiatives over time.Comment: 32 pages, 5 figures. Improved exposition, corrected typos. Comments are welcome

Measuring Trustworthiness of AI Systems: A Holistic Maturity Model

Artificial intelligence (AI) has an impact on business and society at large while posing challenges and risks. For AI adoption, trustworthiness is paramount, yet there appears to be a gap between theory and practice. Organizations need guidance in quantitatively assessing and improving the trustworthiness of AI systems. To address such challenges, maturity models have shown to be a valuable instrument. However, recent AI maturity models address trustworthiness only at the maturest level. As a response, we propose a model to integrate the concept of trustworthiness across the AI lifecycle management. In doing so, we follow Design Science Research to develop a holistic model highlighting the importance of trustworthiness throughout the AI adoption journey to realize the real value potential. This research-in-progress contributes to the emerging research on human-AI systems and managing AI. Our objective is to use the model for assessing, evaluating, and improving trustworthy AI on an organizational level

What can AI do for you?

Simply put, most organizations do not know how to approach the incorporation of AI into their businesses, and few are knowledgeable enough to understand which concepts are applicable to their business models. Doing nothing and waiting is not an option: Mahidar and Davenport (2018) argue that companies that try to play catch-up will ultimately lose to those who invested and began learning early. But how do we bridge the gap between skepticism and adoption? We propose a toolkit, inclusive of people, processes, and technologies, to help companies with discovery and readiness to start their AI journey. Our toolkit will deliver specific and actionable answers to the operative question: What can AI do for you

Artificial Intelligence, International Competition, and the Balance of Power (May 2018)

World leaders, CEOs, and academics have suggested that a revolution in artificial intelligence is upon us. Are they right, and what will advances in artificial intelligence mean for international competition and the balance of power? This article evaluates how developments in artificial intelligence (AI) — advanced, narrow applications in particular — are poised to influence military power and international politics. It describes how AI more closely resembles “enabling” technologies such as the combustion engine or electricity than a specific weapon. AI’s still-emerging developments make it harder to assess than many technological changes, especially since many of the organizational decisions about the adoption and uses of new technology that generally shape the impact of that technology are in their infancy. The article then explores the possibility that key drivers of AI development in the private sector could cause the rapid diffusion of military applications of AI, limiting first-mover advantages for innovators. Alternatively, given uncertainty about the technological trajectory of AI, it is also possible that military uses of AI will be harder to develop based on private-sector AI technologies than many expect, generating more potential first-mover advantages for existing powers such as China and the United States, as well as larger consequences for relative power if a country fails to adapt. Finally, the article discusses the extent to which U.S. military rhetoric about the importance of AI matches the reality of U.S. investments.LBJ School of Public Affair