AI is a crucial technology
The pervasivity of AI in organizations
In the organizational and business framework, AI can provide assistance to decision-makers and technicians beyond the scope of humans (Groves et al., 2013; Wamba et al., 2017). Indeed, both
academics and practitioners agree that AI may substantially impact firms’ innovation processes (Bughin et al., 2018; von Krogh, 2018).
Organizations have long exploited AI-based solutions to automate routine tasks in operations and logistics. Recent advances in computational power and resources, the exponential increase in data availability, and new machine-learning techniques now allow organizations to also exploit AI-based solutions for managerial tasks (Brynjolfsson & McAfee, 2017). For example, AI-based solutions play important roles in Unilever’s talent acquisition process (Marr, 2018), in Netflix’s decision-making processes regarding movie plots, directors, and actors (Westcott Grant, 2018), and in Pfizer’s drug discovery and scientific development activities (Fleming, 2018).
AI for quality control and Industry 4.0
In the industrial field, there is a wide use of vision tools for the automation of quality control procedures by the means of AI tools that focus on the quantitative and deterministic analysis of a product, in order to ensure that it complies with the requirements expressed by the customer. Moreover, there is also the need for software tools which could allow the modeling and generalization of quantitative analyses that aim to determine the value of a product or material according to aesthetic standards.
These operations are still carried out by specialized technicians, thereby the traditional process is slowed down by the huge waste of time and human resources required, as well as by a performance limit mainly due to the high intrinsic variability among the different annotators. For these reasons, it is not surprising that the quality control task has rapidly established itself as a relevant use case for AI in the field of Industry 4.0.
Therefore, this workshop will be focused on the current technological scenario of AI for business in heterogenous fields and industries. The workshop mainly aims at allowing organizations, academics, researchers and specifically firms, decision-makers and practitioners to share and analyze heterogenous research works and business case studies dealing with AI in business fields. The idea behind this workshop is the opportunity to share knowledge and experience in how AI is actually and currently affecting business cases and intelligence. Companies will share specific case studies as well as their current issues AI is solving in their organizations. Researchers will provide scientific works and studies to contribute in the advancement of the many synergies between AI and business models and organizations. The final aim of the workshop is contributing in depicting the overall scenario and framework of the exploitation, advantages and current issues of AI in business.