Artificial intelligence for business model innovation in digital sustainability companies: Multiple cases from the Netherlands

PURPOSE: This research explores how sustainability companies deliver AI-powered solutions leading to Business Model Innovation (BMI). It also examines how they adopt AI to reshape business models (BM) for a balanced long-term ecological, economic, and social value across diverse industries and company sizes.

DESIGN/METHODOLOGY/APPROACH: The study adopts qualitative semi-structured interviews with the top 20 sustainability executives and founders in the Netherlands as a unique context of sustainability. A systemic theoretical framework is developed based on the TOE theory, innovation capabilities, elements of the BM, and external factors.

FINDINGS: Findings reveal differences between large and small sustainability companies from the TOE perspectives. AI is instrumental for operational efficiency, real-time environmental monitoring, supply chain traceability, and immersive realities. Organisational insights highlight design-led, inclusive leadership, bottom-up innovation, and AI alignment with business strategy. Environmental challenges include supply chain collaboration resistance, the impact of regulatory influence, and market readiness.

ORIGINALITY/VALUE: This study offers original multi-case evidence from the Netherlands, providing a systemic framework that reconceptualises AI not just as a facilitator but as a foundational input shaping sustainable BMI. 

PRACTICAL IMPLICATIONS: It guides sustainability executives & SMEs’ founders on how to embed AI strategically beyond efficiency to align with client values and promote bottom-up innovation. Policymakers are urged to accelerate national AI-sustainability strategies, fostering experimentation and collaboration to leverage AI for broader ecological and societal benefit.