Artificial intelligence enabled transformation of green capabilities into sustainable performance: a process-based view <i>Available</i>

Green sensing positively impacts organizational learning, which subsequently drives green reconfiguration, leading to enhanced sustainable performance. The sequential mediation analysis confirms that sensing influences performance indirectly through these intermediate capability stages rather than via direct effects. Furthermore, AI significantly moderates the relationship between reconfiguration and sustainable performance.

High AI capability allows firms to translate strategic changes into tangible results more effectively, optimizing resource allocation and execution efficiency in uncertain environments.</p><p dir="ltr">Originality/value</p><p dir="ltr">This research advances the NRBV by integrating it with dynamic capabilities to reveal the sequential microprocesses of green value creation. Its primary originality lies in shifting the focus from direct effects to a sequential mediation mechanism, demonstrating how green sensing must be internalized through learning and reconfiguration to achieve sustainability.

In addition, to the best of the authors’ knowledge, this study is among the first to empirically position AI as a digital catalyst that moderates the transformation of green capabilities. These insights provide a novel framework for leveraging digital technology to enhance environmental and organizational outcomes.</p>