# Developing an Institutional AI Digital Assistant in an Age of Industry 5.0
## 5 Discussion  
The transition from Industry 4.0 to 5.0 brings a paradigm shift from automation-centric models to human-centric innovation and co-creation [6, 21, 25, 35, 36]. While in the wider sector and in this special issue several industry examples are provided [21, 22, 23], in this article we specifically focused on the development of an institutional AI digital assistant (i-AIDA) using principles of Design-Based Research [16, 17, 18] and Technology Acceptance Model [20, 39, 40] at a large distance learning provider, the Open University [4, 5, 38]. In line with the human-centric innovation and co-creation approach of Industry 5.0, this i-AIDA was (co-)created and (co-)developed together with students and staff over a period of about a year before this particular beta-test was conducted. The findings from the beta-testing of i-AIDA with 18 distance learning students demonstrated the potential and complexity of integrating i-AIDA into higher education settings within the broader context of Industry 5.0. In this sense, i-AIDA embodies this ethos, aiming to offer personalized, context-aware learning support for our distance learners while still maintaining institutional oversight regarding data privacy, academic integrity, and pedagogical alignment. In terms of RQ1, perhaps one of the most compelling outcomes of this study was the marked shift in student attitudes post-intervention. Those learners who were initially skeptical of GenAI and i-AIDA in particular demonstrated increased acceptance and even enthusiasm after engaging with i-AIDA. This shift indicates that hands-on, context-relevant exposure to i-AIDA may play a crucial role in overcoming some of the initial resistance towards GenAI, especially among distance learning students who value institutional trust and course alignment over the generalized capabilities of p-AIDA tools like ChatGPT. Nonetheless, two out of 18 participants remained \"neutral\" towards i-AIDA, and whether (or not) this would help with their studies. Furthermore, whether the positive user experience remained for the other 16 students after the beta-test obviously needs further exploration. In terms of RQ2 of the design features supporting distance learning students in the context of Education 5.0, our thematic analysis of the screencasts, logbooks, and learner feedback revealed that i-AIDA's core features of chat, quiz, and flashcards were particularly valued. Furthermore, participants appreciated the course-specific integration of i-AIDA in the students' learning environment and how it provided tailored responses to their prompts. Furthermore, participants appreciated the explicit transparency in source referencing, and where more information about a particular answer within the OU learning environment could be found. These are core functionalities that are currently not available in p-AIDA systems like ChatGPT, and given the sensitive nature of learning data, it seems unlikely that these systems will get these affordances [11]. These features address many of the concerns raised about public generative AI tools--namely, opacity, lack of context, and risks around misinformation or generic output. i-AIDA's contextual awareness and grounding in institutional data were seen as its primary strength, supporting previous literature that calls for more ethically-grounded, domain-specific AI systems in an educational context [3, 11]. At the same time, several limitations and tensions emerged with i-AIDA. While many praised i-AIDA's design and structured responses, others criticized the tool for being overly verbose or slow, reflecting the need for more streamlined UX and responsive design. Substantial efforts since January 2025 have been put in place by the research and development team to improve the speed and verbosity of i-AIDA, and preliminary findings from our own testing and the current experimental study (see below) seem to suggest that the speed of functionalities is similar to p-AIDA providers.