This study proposes a conceptual model that explains the influence of leadership on the relationship between human intelligence (HI) and artificial intelligence (AI). A qualitative, non-systematic literature review was conducted in Scopus and Web of Science of the literature published in the last 5 years, using Boolean combinations of the terms “leadership,” “artificial intelligence,” and “human intelligence.” The thematic analysis allowed the identification of conceptual patterns and research gaps; the model elaborated from the review shows that leadership has an ethical and strategic mediation in the HI-AI relationship in a hybrid space of cooperation, in which automated decisions are put in real context through human judgment and reasoning; ethical governance mechanisms emerge for systems supported by artificial intelligence; and finally, a balancing mechanism to algorithmic efficiency is established through cognitive adaptability. The proposed framework offers organizations some guidelines for human supervision processes for AI-supported systems that integrate ethical evaluations into automated processes. It proposes elements—leadership tools that enhance the relationship between human intelligence and artificial intelligence. This article contributes to the management of organizations by proposing a model that recognizes leadership as a dynamic facilitator between HI and AI, integrating transdisciplinary knowledge of management, technological ethics, and cognitive science, and proposing an ethical interrelationship in the decision-making architectures between HI and AI. The proposed model establishes leadership mediation of human–AI interaction through four axes showing how leadership acts as the axis that brings together human and technological systems to work together. Hierarchical interaction creates a hybrid interaction that is highly flexible, efficient, and has ethical oversight. Finally, the proposed model is an open system that interacts with the environment and is understood as a flexible tool to support strategic decision-making in complex environments.

This paper deals with the arrow of complexification of engineering. We claim that the complexification of engineering consists in (a) that shift throughout which engineering becomes a science; thus it ceases to be a (mere) praxis or profession; (b) becoming a science, engineering can be considered as one of the sciences of complexity. In reality, the complexification of engineering is the process by which engineering can be studied, achieved, and understood in terms of knowledge, and not of goods and services any longer. Complex engineered systems and bio‐inspired engineering are so far the two expressions of a complex engineering. © 2011 Wiley Periodicals, Inc. Complexity, 2012

Recent literature suggests there is a natural connection between innovation and digital transformation, two key topics of interest in management and organization that have spawned large, independent and well-defined areas of study. While this connection might be analytically straightforward and notable examples are not hard to find, in everyday life, it materializes in a multiplicity of ways. A need emerges, then, to better understand the interaction between innovation and digital transformation so that it can be explored and exploited by actors in academia and the public, private and third sectors. In this article, we use a co-word analysis, a text mining technique that permits to systematically map the intellectual structure of a research field, to characterize the most notable dynamics of ‘innovation-driven digitalization’ and ‘digitalized innovation’— the two major dimensions of interaction between innovation and digital transformation. The text identifies the relevant themes, subthemes and concepts that appear in the literature, as well as their relationship and level of development. It, then, aggregates them in a taxonomy that, on the one hand, readily displays their connection and, on the other hand, (i) informs about current or potential controversies, (ii) gaps, (iii) lines for novel and further research, and (iv) alternatives to bridge to other areas of study.

This paper argues that there is a synchronicity among biological and computational levels on an organism and provides arguments and proofs based on experimental research gathered in the literature. The leading thread is the interplay between quantum biology (QB) and complexity. As the paper asks whether QB does contribute to complexity science (CS), five arguments are provided: (i) Firstly a state-of-the art of QB and its relationship to CS is sketched out. Thereafter, the attention is directed to answering the question set out; (ii) Secondly, it digs into the understanding of life toward deeper levels of reality; (iii) It is shown that non-trivial quantum effects shed insightful lights on the information processing of and within living beings; (iv) Once the distinction is made between increasing levels of complexity and increasing levels of organization, the focus lies in the importance of QB for organization, and not so much for complexity as such; (v) The role of information rises at the center of all concerns, and the intertwining of complexity and information processing. At the end some conclusions are drawn

Purpose: This study aims to explore the strategic decisions at innovation level implemented by firms to thrive and transform themselves during crises. This study also aims to provide insights to answer the question: Why do some firms decide to implement certain types of innovation during a crisis? Design/methodology/approach: This research was carried out through a multiple case study involving 22 firms. The methods were implemented in three steps to increase rigor and the replication of the study: identification and selection of cases, data collection through interviews triangulated with online information and analysis based on aggregating themes and finding patterns. Findings: In the face of the COVID-19 pandemic, the companies analyzed focused their activities mainly on developing new features or functionalities for their products or services. Most of the firms implemented innovations across nearly all ten categories outlined by Keeley et al. (2013). Many of the implemented innovations involved personalized and superior service enhancements, process efficiency optimizations, channel diversification initiatives and new ways to collaborate to generate value. In general, the main drivers that led firms to decide to implement these innovations include reducing costs, enhancing operational efficiency, generating new revenue streams, augmenting sales and enhancing client relationships. Practical implications: This research significantly advances the convergence of innovation, strategy and crisis in three impactful ways. First, it constructs a pragmatic and evidence-based framework, consolidating the primary catalysts, innovation categories and strategies adopted by firms in response to the challenges posed by the COVID-19 crisis. Second, it offers insights for guiding decision-making processes related to innovation, presenting actionable recommendations derived from the study’s findings. Thirdly, this study highlights critical perspectives that can guide governmental intervention, facilitating the formulation of more tailored and effective policies to assist companies during crisis periods. Originality/value: This study centers on developing countries, specifically examining Colombian firms, considering their unique characteristics and priorities. Surprisingly, there is a scarcity of studies delving into the innovation and transformation of firms during the COVID-19 crisis in nations sharing cultural, economic and political similarities with Colombia.