Exploring Intelligent Learning Systems, Artificial Intelligence, and Implications for Organizational Culture

Abstract: Abstract
The Association for the Advancement of Artificial Intelligence defines artificial intelligence (AI) as “the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines” (n.d., para. 1). AI incorporates cognitive functions typically associated with humans including learning, interacting, problem-solving, and creativity (Thwaites, 2021). Furthermore, AI evolved to include technologies like machine learning, language processing, data mining, and neural networks (Pavaloiu, 2016). Because mutually intelligent interfaces coexist between humans and machines for information, decisioning, and task improvement, implications of AI are attracting attention of the human resources (Tambe et al., 2019). Scant research exists on how early adoption of AI might be considered by human resource development (HRD). It is critical HRD observes organizational culture during early adoption of AI to mitigate negative influences.
Considering AI may enhance options for affordable adaptive and individualized learning solutions (Ågerfalk, 2020); one facet of AI meriting attention for early adoption in HRD is intelligent learning systems (ITS) as an instructor of work-related content. The purpose of this study-in-progress is to explore ITS as a method for introducing AI to HRD and seek implications on organizational culture. The research is guided by the question: What are potential HRD implications on organizational culture during early adoption of AI?
Individuals learn better in personalized environments (Bennett & McWhorter, 2017). Intelligent learning systems are computer-assisted learning environments providing highly adaptive and interactive instruction developed from fields of knowledge science, cognitive science, mathematics, and computational linguistics (Graesser et al., 2011). These systems are designed to work agnostic to direct human oversight (Guan et al., 2020). ITS follows a learner-oriented approach, adjusting to learners’ mental characteristics and pace of learning to cognitively scaffold and effectively engage learners with educational models, predictive algorithms, and neural networks (Shute & Zapata-Rivera, 2012). ITS customizes content to student-specific learning patterns or knowledge levels for personalized guidance and directed feedback. Accordingly, the potential of ITS gives HRD digital tools to help employees learn faster, better, and cheaper while improving organizational efficiencies and cost models.
Although learning environments where humans work in collaboration with AI systems to influence gain and loss is an important factor for advocating ITS for HRD, there remains absent a cogent argument AI delivers on all promises (Howarth, 2020). Other research notes AI has yet to achieve conventional adoption within organizations (Ransbotham, et al., 2017). Tambe et al. (2019) stated a gap remains between promises made by AI and reality offered by AI in human resource disciplines.
Organizational culture plays a unique role in the adoption of technology (Bennett & McWhorter, 2021). Early researchers observed computer technology a primary factor for driving employee behavior (Hirschhorn, 1984; Long, 1987). Although much has been written on the challenges some organizations have endured implementing new information technology, many organizations lack a coherent technology strategy altogether. Introducing new technologies can include profound changes in the way individuals interact within their work environment (Bennett & McWhorter, 2021). And these changes can cause stress and tension between the old way of doing things and the new way work is done (Galluch, et al., 2015). This historical framework provides a case for HRD to attend to organizational culture during any adoption of AI, especially given that organizational culture impacts the way organizations learn (Cook & Yanow, 1993). Thus, employees in high learning cultures are more apt to embrace technology change (Lingmont & Alexiou, 2020). And, because ITS has potential to improve employee learning in the organization through personalized learning environments, ITS may have potential as an early agent of adoption for organizations with little AI experience. However, it can be argued there may be adoption barriers if HRD does not facilitate a digital organizational culture.
Participants in this exploratory study will be a convenience sample of three HRD professionals with AI experience. A qualitative approach utilizing semi-structured interviews (Creswell & Baez, 2021) will be enacted to better understand ITS as an early adoption method for introducing AI to HRD and consider potential HRD implications on organizational culture. Each participant will be asked identical questions and expected duration is 30 minutes. An example question is: “What are your thoughts on the future of AI as instructor and its relationship to organizational culture?” Following data collection, a transcript of each interview will be created, read, coded; then codes will be grouped, and theme passage written (Creswell & Baez, 2021). Specific recommendations for HRD on facilitating a digital organizational culture will be discussed in the findings of the study.
Keywords: artificial intelligence, organizational culture, Virtual HRD