## 5 Discussion
### Suggestions for Future Research  
Given the large amounts of data generated by devices operating in organizational networks, informational security and data privacy in the organizational setting are key future research directions [124; 125]. Context-specific practical considerations when implementing organizational-level automation must be considered [126; 127; 128]. Discussing the challenges arising from AI adoption in management information systems helped with formulating additional future research directions. Researchers have increasingly focused their efforts on investigating the opportunities for applying AI tools and models to tasks related to process automation, as shown in the Results section of this study and previous literature reviews [4]. An interesting and relatively unexplored topic for future research would be the examination of the overlap between digital twin technology and intelligent process automation in smart factories. Research on how AI-powered robots and intelligent UAVs would affect customer and healthcare services is still lacking, with most of the research efforts focusing on the impact of such technology on logistics [129; 130], delivery [131; 132; 133; 134], and warehousing tasks [135; 136; 137; 138; 139]. Additionally, the following suggestions for future research in the field of AI implementation in MIS were identified based on the analysis of the currently available literature sources:  
* Process automation and business logic definition across different cloud ERP platforms: SAP, Oracle. * ML and computer vision applications for robotization in smart factory deployment. * Intelligent workflow modeling and business process template generation. * Impact of process automation on employee engagement. * Business strategies for the successful inclusion of LLMs and GPTs in the work environment. * Generative AI for CAD modeling and industrial design. * Intelligent quality assurance practices for generative AI design applications. * Human experience management: effects of the use of AI assistants in onboarding procedures. * Predictive analytics and process automation for human experience management. * Sales forecasting and client targeting. * Social media data analytics for advertisement targeting. * Strategies to assess job reduction threats and mitigate the fear of adoption of AI technologies. * Operational data analytics and bottleneck forecasting for production planning. * Natural language robot control for large-scale process automation. * Application of NLP and large language models for controlling unmanned aerial vehicles. * Quality control in automated production scenarios. * Intelligent warehouse management and product life-cycle tracking. * AI techniques and tools for threat and malware detection. * Data privacy and informational security for AI applications. * Cost analysis of edge vs. cloud-based AI applications. The suggested future research directions, identified by the authors in the process of analyzing the existing research in the field of AI adoption in MIS, can be of use to both the research and business sectors in deciding on future research and development efforts. In conclusion, this paper presents a systematic literature review of the existing research in the field of the application of artificial intelligence in management information systems. A classification of AI capabilities observed across the reviewed literature sources is developed. Previous related research is considered, and relevant findings and limitations are discussed. An in-depth view of the applied research methodology is provided. The primary source selection process is detailed. Key phrases and search strings are proposed. The study focuses on the integration of emerging AI technologies at the organizational level of automation and identifies research opportunities and challenges; existing capabilities and platforms; business value and research contributions; and future research directions. Conceptualization, S.S. and N.S. ; methodology, S.S.; software, S.S.; validation, S.S. and N.S.