The AI Governance Paradox: Ethical Awareness Without Operational Clarity

As generative AI adoption accelerates within organisations, governance frameworks struggle to keep pace with everyday practice. Drawing on exploratory survey data from professionals and leaders actively using generative AI ( = 70), this chapter examines how AI governance is perceived and enacted in organisational contexts. The findings reveal ethical awareness without operational clarity: while respondents recognise risks such as bias, misuse, and regulatory exposure, responsibility allocation, escalation pathways, and governance mechanisms remain fragmented and informal. Framed through Transdisciplinary Innovation Theory, the chapter conceptualises AI governance as a socio-organisational process rather than a purely regulatory construct. It argues that weak feedback loops between AI users and governance structures generate latent ethical and compliance risks under emerging regimes such as the EU AI Act. To address this gap, the chapter proposes reverse mentoring as a governance design intervention enabling bidirectional learning across organisational hierarchies, supported by ISO-aligned maturity reflections and practical playbooks.