In the accelerating global quest for sustainability, the synergies between digital innovation and energy efficiency are becoming increasingly evident. Recent research spearheaded by Yue, Ye, Khalid, and their colleagues, published in Humanities and Social Sciences Communications, reveals a critical nexus where digital transformation and ownership concentration jointly propel reductions in corporate energy consumption. Their comprehensive study delves deeply into how cutting-edge artificial intelligence (AI) adoption, driven by concentrated firm ownership structures, can optimize energy usage, thereby advancing global climate action agendas such as the United Nations’ Sustainable Development Goal 13.
The researchers introduce artificial intelligence technology utilization as an innovative proxy for measuring the depth of digital transformation within firms. Departing from traditional enterprise technology markers like ERP or CRM, which recent literature (Fu et al., 2024; Varriale et al., 2024) deems less reflective of true digital shifts, the study harnesses AI-related keywords extracted from corporate annual reports. This novel metric undergoes logarithmic transformation to standardize and capture firms’ nuanced engagement with AI, providing a robust indicator that encapsulates digital transformation’s tangible outcomes in optimizing operational frameworks.
Empirical tests underscore that the embrace of AI technologies correlates with significant reductions in total energy consumption across firms. Table 7 highlights that higher AI keyword density aligns with a marked decrease in energy use. Particularly compelling is the finding that firms characterized by concentrated ownership structures exhibit an amplified energy-saving effect when integrating AI into their technological repertoires. The interaction between AI and ownership concentration reveals that cohesive governance intensifies the capacity to leverage digital tools for environmental impact mitigation.
This insight aligns with extant theoretical and practical literature, which posits AI as a pivotal enabler for streamlining processes, reducing resource wastage, and enhancing overall energy efficiency (Atienza-Barba et al., 2025; Fu et al., 2024; Pimenow et al., 2024). Concentrated ownership, by fostering unified strategic direction and agile decision-making, appears to unlock the full potential of AI-driven energy optimization initiatives (Hu & Shi, 2025; Torres et al., 2024). Together, these dynamics underscore the intertwined nature of technological innovation and governance in realizing climate-related corporate objectives.
Notably, the study confirms that digital transformation’s impacts on energy management exhibit considerable heterogeneity when dissected through the lens of firm-specific characteristics. High-tech firms, which inherently possess greater dynamic capabilities and technological competence, manifest a more pronounced reduction in energy consumption linked to digital transformation compared to their non-high-tech counterparts. This disparity, captured in Table 8, corroborates the premise of the Technology-Organization-Environment (TOE) framework, which amplifies the role of technological context in facilitating impactful digital adoption.
The theoretical underpinnings are further buttressed by dynamic capability theory, which suggests that firms adept at integrating advanced technologies manifest stronger adaptive strategies conducive to sustainable energy use (Alkaraan et al., 2024; Appiah, 2024). Conversely, non-high-tech firms face infrastructural and financial barriers that may dampen their capacity to convert digital tools into tangible environmental benefits. These findings echo prior research emphasizing the imperative of aligning technological adoption strategies with inherent organizational competencies for maximal impact.
Parallel stratifications along pollution intensity also reveal intricate patterns. Firms operating within pollution-intensive industries demonstrate a greater reduction in energy consumption through digital transformation compared to low-pollution entities. This phenomenon reflects the environmental context of the TOE framework, where external regulatory pressures and stakeholder expectations induce a heightened urgency for sustainable operational practices (Agyemang et al., 2025; Xie et al., 2024). The intensified effect in pollution-heavy sectors highlights digital transformation as a key lever for compliance and reputational management.
Beyond these contextual factors, the research addresses critical econometric challenges related to potential endogeneity between digital transformation and energy consumption. The authors utilize a rigorous two-pronged approach incorporating two-stage least squares (2SLS) and system generalized method of moments (GMM) estimations to mitigate biases arising from omitted variables, simultaneity, measurement errors, and dynamic panel effects. This methodological rigor ensures robust and credible inference.
A particularly innovative aspect of the identification strategy is the use of industrial robot adoption as a valid instrumental variable. The rationale rests on industrial robots serving as a concrete manifestation of digital transformation, strongly linked with AI-driven automation, yet exogenous to individual firms’ energy consumption decisions. This approach aligns with contemporary empirical traditions, reinforcing the causal link between digital transformation and energy efficiency (Islam et al., 2024; Liu et al., 2025).
Results from these instrumental variable estimations reaffirm the core thesis: digital transformation significantly curtails corporate energy demand. The implications are profound. By articulating a clear causal chain, the study establishes digital upgrading as a cornerstone mechanism in achieving energy efficiency goals. This nexus is especially relevant within the broader spectrum of sustainability transitions, offering empirical backing for policies that incentivize digital innovation as a climate mitigation strategy.
Importantly, the study situates these findings within the evolving governance landscapes of firms. Ownership concentration emerges as a subtle yet powerful moderator, with more concentrated ownership fostering tighter alignment on digital and environmental strategies. Such governance configurations may streamline decision-making processes, catalyze resource allocation toward green digital initiatives, and enhance accountability, collectively bolstering the efficacy of digital transformation in energy savings.
Furthermore, the research contributes valuable nuances regarding sector-specific strategies. High-tech and pollution-intensive firms constitute priority targets for digital transformation policies tailored to maximize energy efficiencies. Policymakers and corporate leaders may consider these heterogeneities when designing incentive structures or supporting technological diffusion. The study thus bridges strategic management theories and practical environmental governance, yielding actionable insights.
Methodologically, the extraction and quantification of AI-related keywords from corporate filings demonstrate a pioneering integration of text analysis techniques into sustainability research. This approach captures intangible facets of digital transformation unobservable through conventional technological adoption metrics, opening pathways for future research leveraging natural language processing in corporate environmental strategy analyses.
In reflecting on the broader implications, this study resonates powerfully with the Sustainable Development Goals (SDGs), particularly SDG 13, which calls for urgent climate action. By illuminating the intersection where digital innovation and ownership structures converge to drive energy efficiency, the research offers a forward-looking blueprint for corporate contributions to global climate objectives.
Ultimately, this research enriches the discourse on the digital-economy-climate nexus with nuanced empirical evidence, affirming that digital transformation—especially underpinned by advanced AI adoption and concentrated ownership—is not merely a technological upgrade but a fundamental pathway toward sustainable energy management. It prompts a reevaluation of innovation policies, governance reform, and strategic investments essential for aligning business operations with climate imperatives.
As the global community intensifies climate efforts, integrating digital transformation within corporate sustainability frameworks presents substantial promise. This study’s findings encourage further exploration of technology-governance interactions and propel digital transformation to the forefront of strategic climate solutions for contemporary enterprises worldwide.
Subject of Research: Digital transformation’s impact on corporate energy efficiency and the moderating role of ownership concentration.
Article Title: From digital transformation to energy efficiency: ownership concentration’s hidden role in driving climate solutions.
Article References:
Yue, S., Ye, G., Khalid, F. et al. From digital transformation to energy efficiency: ownership concentration’s hidden role in driving climate solutions. Humanit Soc Sci Commun 12, 1615 (2025). https://doi.org/10.1057/s41599-025-05911-8
Image Credits: AI Generated
