The rapid emergence of Artificial Intelligence (AI) as an active participant in organizational cognition is fundamentally reshaping strategic decision-making (Puranam, 2021; Raisch & Krakowski, 2021). Rather than serving as mere infrastructure, AI reshapes the cognitive architecture through which firms learn and allocate capital (Shrestha et al., 2019). However, within the framework of “The Ecology of Knowledge in the AI Era” (Carayannis et al., 2023), a knowledge ecosystem cannot optimize for technological efficiency while eroding the cultural, behavioral, and ethical foundations of corporate decisions (Nonaka & Takeuchi, 2021; Schwenzimmer & Secchi, 2023). Culture—comprising routines, values, aesthetic sensibilities, and power dynamics—acts as the vital habitat determining whether AI leads to sustainable value creation or cognitive homogenization (Schein & Schein, 2019; Alvesson, 2013). Grounded in integral ecology (Pope Francis, 2015; Pirson, 2017), this interdisciplinary track explores how technological, human, and moral dimensions interact across accounting, corporate finance, governance, organizational design, sociology, and behavioral strategy. In accounting and control, we examine how culture shapes AI-driven performance metrics (Chapman, 1997; Quattrone, 2016), questioning whether algorithmic governance marginalizes tacit and embodied knowledge (Polanyi, 1966). In corporate finance and governance, culture and executive behavioral biases strongly influence capital allocation under uncertainty, valuation, and algorithmic oversight (Barberis & Thaler, 2003; Graham et al., 2013; Guiso et al., 2015). We scrutinize whether automated financial decision support introduces systemic biases or if board cultural diversity safeguards against algorithmic conformity (Adams et al., 2010; Kahneman et al., 2021).   Sociologically, AI alters social relationships, identity, and power structures (Kellogg et al., 2020; Zuboff, 2019). As artificial agents assume cognitive tasks, routines undergo profound transformations (Feldman & Pentland, 2003; Murray et al., 2021). Trust, symbolic power, and institutional legitimacy determine whether human-AI intelligence achieves genuine symbiosis or institutional friction (Bourdieu, 1986; Suchman, 1995; Jarrahi, 2018). Incorporating behavioral dynamics and aesthetic sensibilities highlights how human judgment, imagination, and moral reasoning can be preserved alongside computational capabilities (Adler, 2006; Secchi, 2011).  By bridging business disciplines with social sciences, this track addresses IFKAD 2027’s mandate: understanding how to cultivate, govern, and sustain a healthy knowledge ecosystem where technological innovation enhances human dignity, diversity, and long-term organizational health.