Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/234626 
Year of Publication: 
2021
Series/Report no.: 
CREMA Working Paper No. 2021-11
Publisher: 
Center for Research in Economics, Management and the Arts (CREMA), Zürich
Abstract: 
The recent acceleration and ongoing development in Artificial Intelligence (AI) and its related (and/or enabling) digital technologies presents new challenges and considerable opportunity on which businesses and individuals may capitalise. In the era of BD - and with increasing societal value being placed on sustainable business to minimise or mitigate the impacts of climate change - customers and regulators alike are turning to organizations to tackle large and complex sustainable development goals. AI and BD can help interpret and monitor the environment, identify which problems need attention, design strategies, generate decisions, and action the tactics. A key challenge in sustainable entrepreneurship is a failure to integrate 'systems thinking' beyond a limited number of issues, rather than taking the time to understand the relationship between business processes, macro ecological processes, boundary conditions, and tipping points. The recent and substantial increase in data availability simultaneously advances the potential for AI and BD to enhance ecological sustainability through validation and testing of beliefs and hunches, offering empirical guidance to every stage involved in decision making, and comparing inputs against the outcomes - particularly in fast-changing and highly uncertain environments. To prepare, we must strategize by looking to and engaging with the market, our clients, and our customers for guidance. Only then can we then proceed to develop viable and sustainable business models and plans. To reap the rewards of progress in AI, BD, and related technologies, we need to find ways to race with the emerging technologies while also identifying ways to act in symbiosis with them. The demands of adapting to AI and BD are no different from the situation with past disruptive technologies such as the automobile, radio, and the Internet.
Subjects: 
Artificial Intelligence
Big Data
Entrepreneurship
Sustainability
Expert Systems
Document Type: 
Working Paper

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