Leadership-driven employee-AI collaboration for enhanced decision-making in continuous processing operations

Abstract

This research study explored how leadership can empower, equip and support employee-AI collaboration to enhance decision-making in continuous processing operations. This gap has become critical, as organisations are quickly adopting AI-disruptive technologies, leaving frontline employees often lacking the strategic tools and unprepared to use the technology safely and responsibly. Transformational leadership provided the conceptual foundation, given its emphasis on psychological safety, employee growth and capability building, and empowerment. This study employed a qualitative, interpretivist approach, utilising semi-structured interviews with 19 stakeholders from South African continuous and hybrid processing operations. Reflexive thematic analysis (RTA) showed that employees had good awareness of AI technologies and viewed them as a decision accelerator, but they relied heavily on leadership support, explainability, and governance to build trust and maintain oversight. Leaders communicated AI augmentation rather than substitution strategies and provided experimental spaces to facilitate stronger adoption. Even though leaders have made strides to enable employees, significant barriers to AI adoption remain. The study has operationalised and extended TL theory in AI embedded operations, providing practical leadership behaviour and highlighting the importance of governance mechanisms to sustain safe and responsible AI use. Research limitations include a small sample size, subjective opinions, and the rapid, transformative nature of AI technologies.