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AI-Enabled Circular Business Models for Industrial Sustainability

In the ever-evolving landscape of industry, a novel breed of business models is taking shape, propelled by the intersecting influences of digitalisation, artificial intelligence (AI), and circularity. This transformation represents not only an avenue for forging more sustainable customer relationships but also a compelling response to the pressing climate change crisis. Industrial manufacturers are increasingly awakening to their pivotal role in championing a circular and sustainable sector. Within this context, AI assumes a central role in the reconfiguration of the industry towards sustainability and competitiveness.

While a multitude of industrial enterprises are championing sustainability, they are concurrently channelling investments into AI development to underpin circular business models. These models are centred around the creation of value through the reduction, reuse, and recycling of material and energy resources. The integration of AI into these circular business models heralds an unprecedented opportunity to introduce innovative paradigms of operation, while simultaneously unlocking new sources of value, revenue, and sustainability.

Nevertheless, the infusion of AI and digital technologies into these models remains largely uncharted territory, with instances of successful AI-enabled circular business models being relatively rare. This scarcity can be attributed to the rapid evolution of AI technology, often outpacing the industry’s ability to adapt. The current focal challenge lies not in the development of technology but in the effective application of AI technology to concrete business contexts, thereby translating circularity and sustainability into reality.

To address these hurdles, industrial stakeholders embroiled in digital servitisation must undergo a metamorphosis of their business models, capabilities, and ecosystem collaborations to harness the full potential of AI. This transformation necessitates the cultivation of the requisite proficiencies for addressing customers’ sustainability challenges with AI, crafting suitable solutions, and managing them adeptly over time.

Researchers have devised a framework to illustrate how AI capabilities, encompassing perceptual, predictive, and prescriptive functions, form the bedrock of various circular business models. Within this framework, dynamic capabilities crucial for expediting the commercialisation process, including value discovery, realisation, and optimisation, are delineated.

Furthermore, the framework elucidates the progression of AI commercialisation, revealing how AI capabilities such as ongoing data analysis and decision-making automation serve as the foundation for amplifying circular business models amongst industrial manufacturers. Through the employment of AI technologies, businesses can enhance their customers’ operations, bolster resource efficiency, and promote circular practices within their business models, thus contributing to sustainable and eco-friendly operations. Additionally, it establishes a perpetual feedback loop between the impact of AI-enabled circular business models and the continual evolution of AI capabilities. As companies implement these models, they accrue valuable insights and experiences that inform the ongoing advancement of AI capabilities. In essence, the adoption of AI-powered circular business models fosters the enhancement of AI technologies, culminating in a cycle of perpetual refinement of AI platforms that better support industrial circular business models.

In conclusion, this underscores the intricate interplay between AI capabilities, dynamic capabilities, and the influence of AI-enabled circular business models. It emphasises how dynamic capabilities bolster circular business models and how the deployment of these models propels the development and progression of AI technologies. The companies engaged in digital servitisation, by nurturing and effectively utilising AI capabilities for commercial circular business models, can make a significant contribution to sustainability. In essence, by addressing economic, social, and environmental concerns, they stand to gain widespread benefits.

Insights by: Dr Jay Wasim and Parnia Ahmed