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As far back as the industrial revolution, great leaps in technical innovation succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial, intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision making engendering new opportunities for continued innovation. The impact of AI is significant, with industries ranging from: finance, retail, healthcare, manufacturing, supply chain and logistics all set to be disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: technological, business and management, science and technology, government and public sector. The research offers significant and timely insight to AI technology and its impact on the future of industry and society in general.

We focus on both individual and local uncertainty to explain the innovation potential of entrepreneurs in the NUTS1 UK regions in 2005 and 2009. The ‘potential surprise function’ (Shackle, 1949) clarifying why sometimes promising business choices are truncated is taken as a determinant of an entrepreneur’s innovation decision. GEM (Global Entrepreneurship Monitor) data and data on psychological types are used in the empirical analysis. The econometric estimation strategy addresses both the issue of selection bias (due to uncertainty) and that of zero-inflated data (i.e., presence of only a few highly innovative actors in comparison to the majority in our sample). Findings suggest that local uncertainty is the predominant determinant of individual entrepreneurial choice. The regional effect appears to amount to about 4% of the innovation differences across NUTS1 UK regions, while almost one third of it is determined by the local level of uncertainty bias. Thus, the novelty of the present study is that it shows how differences in local cultural tolerance to uncertainty may explain differences in the quantity of truncated innovative ideas among localities.

The main aim of the paper is to explore the nature and consequences of intangible cultural capital, i.e., the local ‘milieu’ comprising inter alia attitudes and preferences, for the case study of Greece, 2002-2009. To pursue this study empirically, we combine basic economic and social indicators from two main sources: the EUROSTAT Regional Database and the European Social Survey (ESS). Employing a three-stage least squares (3SLS) model for both a normal and a pooled cross-sectional data set, we find that local cultural factors play an important role in the emergence and existence of spatial economic disparities in Greece. Most interestingly, among all the approximations of intangible cultural capital examined, the historical cultural variable appeared to show the most consistent results throughout all specifications. This suggests the existence of cultural persistence traits in local economic development in Greece, a phenomenon which merits further investigation.