Digital platforms need green value co-creation to unlock AI’s potential

AI alone does not guarantee sustainable outcomes. Although firms equipped with advanced AI capabilities report stronger economic and operational performance, much of the value depends on how these tools are applied. The analysis shows that the direct effect of AI on firm performance weakens once the mediating role of collaborative environmental practices is considered.

The role of artificial intelligence in driving sustainable performance has been less understood until now. A new study published in Sustainability explores how platform AI resources shape environmental collaboration and long-term firm performance.

Titled “Platform AI Resources and Green Value Co-Creation: Paving the Way for Sustainable Firm Performance in the Digital Age”, the research examines psychological mechanisms, such as trust in AI and environmental identity, that link AI capabilities to sustainable outcomes. The study draws on survey data from 466 platform managers across China’s leading digital hubs, covering sectors such as e-commerce, consumer goods, and healthcare.

Can AI resources directly drive sustainable performance?

The study explores whether platform AI resources (PAIRs) directly boost firm performance. The findings reveal that while AI resources improve operational efficiency, market responsiveness, and user engagement, the impact is more complex when viewed through a sustainability lens.

The researchers demonstrate that AI alone does not guarantee sustainable outcomes. Although firms equipped with advanced AI capabilities report stronger economic and operational performance, much of the value depends on how these tools are applied. The analysis shows that the direct effect of AI on firm performance weakens once the mediating role of collaborative environmental practices is considered.

This indicates that artificial intelligence must be tied to processes of stakeholder collaboration and environmental engagement to fully realize its potential. Rather than functioning as a standalone driver of efficiency, AI’s long-term value depends on whether it can foster responsible innovation and support sustainable growth strategies.

How does green value co-creation bridge AI and firm performance?

The study positions green value co-creation (GVC) as the crucial bridge linking AI resources to firm success. GVC refers to the collaboration between businesses and stakeholders to design and implement environmentally friendly products, services, and processes. When supported by AI insights, these partnerships allow firms to improve supply chain efficiency, reduce environmental harm, and enhance brand credibility.

The data highlight that firms using AI to encourage green collaboration experience superior results compared to those focusing only on technical integration. For instance, explainable AI dashboards, automated sustainability reporting, and partner-facing analytics tools significantly increase participation in eco-friendly initiatives. This in turn boosts profitability, market share, and overall resilience.

Psychological mechanisms play a central role in this process. Trust in AI emerges as a decisive factor, with transparent and ethical systems encouraging managers and partners to embrace AI-driven recommendations. At the same time, environmental identity—the degree to which individuals and organizations see themselves as committed to sustainability—strengthens collaborative outcomes. AI systems designed to reduce bias and minimize cognitive overload further reinforce these behaviors.

The findings suggest that AI resources contribute indirectly to firm performance by creating the conditions for effective stakeholder engagement. Without green value co-creation, the benefits of AI remain limited to short-term efficiency gains, rather than transformative contributions to sustainability.

What role does sustainable development context play?

The study also asks whether the institutional context, particularly sustainable development (SD) orientation, shapes the effectiveness of AI-driven green collaboration. The evidence confirms that the impact of GVC on firm performance is far stronger in regions with high sustainability demands, such as strict regulations, carbon reduction targets, or ESG-driven market pressures.

The analysis shows that firms operating under strong sustainability frameworks double the performance benefits of GVC compared to those in weaker regulatory environments. In contexts with high SD orientation, managers perceive environmental collaboration as both a compliance requirement and a market advantage. This encourages them to integrate AI-driven carbon reporting, eco-innovation tools, and co-design platforms more effectively.

On the other hand, companies in low-SD contexts see weaker returns from green initiatives. Without regulatory incentives or strong stakeholder expectations, AI resources are less likely to be applied toward collaborative sustainability goals. The results highlight the importance of aligning national and regional policies with firm-level strategies to ensure that AI capabilities translate into meaningful environmental impact.

Implications for business and policy

The research carries important implications for managers, policymakers, and technology designers. For business leaders, the evidence underscores the need to prioritize AI investments that encourage stakeholder collaboration rather than focusing solely on technical upgrades. Tools that improve transparency, reduce cognitive burden, and encourage eco-friendly decision-making should be at the forefront of digital strategies.

For policymakers, the study recommends creating incentive structures that reward the integration of AI into sustainable practices. Mandating AI transparency in sustainability reporting and offering tax benefits for green technology adoption are identified as practical measures to strengthen the AI–sustainability link. Ethical oversight is also vital to ensure that algorithms do not undervalue eco-friendly options or reinforce unsustainable practices.

Finally, the study adds to the academic conversation by bridging resource-based and behavioral theories with institutional insights. It demonstrates that AI’s contribution to sustainability lies not only in technical efficiency but also in its ability to shape human trust, cognitive processes, and collaborative behaviors.