The human-digital interface – acceptance and trust of Artificial Intelligence in Supply Chain (ERP) Systems

Businesses and humans are more and more faced with the fact that artificial intelligence is finding its way from shopfloor to topfloor. The rise of smart technologies, the digital age and the birth of a true intelligent enterprise, an enterprise where technology augments the human capabilities, cannot be stopped. Since their inception in the 20th century these technologies are now mature enough but still a lot of resistance, adversity and disbelief withhold companies to really embrace and adopt ai. The major factors are acceptance and trust – trust that an artificial intelligence that mimics the human brain makes predictions, assumptions and takes decisions for and with humans.   The importance in this study is to provide a clear answer on the impact of artificial intelligence (digital) on the human workforce (human) and supply chain (physical) processes (ERP, system driven) and what will be required to make the collaboration work on a continuous basis (technology adoption).   A shortcoming of earlier bodies of literature is that a large focus is placed on the advantages, disadvantages and dangers of artificial intelligence but less on what is required to accept ai and even less in the practical context of supply chain systems. Siau K. (2018) wrote that “Trust in automation, once lost, like interpersonal trust, can be hard to re-establish” and that “Trust that is absolute, verified, and reliable would, of course, be an unachievable goal”. I propose a framework that guides business decision makers on creating the right level of acceptance and trust in order to successfully embed and adopt artificial intelligence in supply chain systems. I will illustrate the idea by concrete business cases of both successes and failures and the underlying forces leading to both outcomes as well as by collecting data (e.g. surveys) across companies. My hypothesis is that trust and acceptance have such a significant impact on the outcome that without both the adoption of the technology will be less or not successful at all. I hope to extend the conversation on artificial intelligence from today’s rhetoric on e.g. self-driving cars or ai in general to the level of logistics and supply chain to make it as practical as possible. This will help to drive the conversation at businesses as well when developing or implementing an ai based solution to optimize and automate their supply chain processes, and this with the right level of acceptance and trust of the human counterpart. Key words: technology acceptance model (TAM), theory of acceptance and use of technology (UTAUT), explainable ai, theory of reason action (TRA), industry 4.0, artificial intelligence, ERP, supply chain systems, technology adoption