Leveraging Situation Awareness for Human-AI Collaboration to Achieve Operational Excellence in SMEs

About the Project

Small and medium‑sized enterprises (SMEs) increasingly rely on digital technologies and AI‑enabled systems to improve efficiency, resilience, and decision‑making. However, SMEs often face challenges integrating AI effectively due to limited resources, internal capabilities, and lack of guidance to delineate the roles between humans and intelligent systems. This research proposes to apply Endsley’s Situation Awareness (SA) model as a theoretical and practical foundation to enhance human–AI collaboration in SME operations.

SA is defined as "the perception of environmental elements, comprehension of their meaning, and projection of their future status" - a construct empirically linked to improved performance across multiple domains with dynamic environment, such as military, aviation, healthcare, and autonomous vehicle (Endsley, 1995; Endsley and Jones, 2024). However, it has been relatively under-explored in the context of day-to-day business process and operations.

Existing literature highlights SA as critical for effective oversight of AI and autonomous systems, enabling operators to understand AI status, identify system limitations, and determine when human intervention is needed. Various researches around human–AI relationship also suggested the importance of transparent interfaces, mental models, and trust, all of which are essential to maintaining high levels of SA in dynamic environments.  These insights suggest that applying SA‑oriented design principles (Endsley and Jones, 2025) can substantially improve the integration of AI tools in SMEs, which also helps to maintain the required level of individual SA and shared SA to make the appropriate operational and strategic decisions.

While SA, together with its design principles and associated Situation Awareness Global Assessment Technique (SAGAT) help to enhance the human-AI relationship, we argue the critical role of business operations strategy to achieve operational excellence. For this purpose, we will explore using the Four Concepts of Flow in the Theory of Constraints (TOC) (Goldratt, 2009) as a generic operations framework to underpin the intervention introduced in SME case companies.

This research will adopt a multi-case study approach, where you will have opportunity to work with multiple SMEs with possibility of introducing intervention.

This is a cross-disciplinary research which includes operations management (TOC), cognitive processing (SA), and technology (digital and AI). At the end of this research, we aim to (i) develop an empirically validated SA-driven human-AI collaboration model for SMEs; (ii) provide a practical guide for SMEs to leverage on the AI capabilities while empowering personnel; and (iii) Increase the awareness and reduce the knowledge gap in digital technologies and AI adoption in SMEs.