330 Wirtschaft
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Machine learning (ML) techniques are rapidly evolving, both in academia and practice. However, enterprises show different maturity levels in successfully implementing ML techniques. Thus, we review the state of adoption of ML in enterprises. We find that ML technologies are being increasingly adopted in enterprises, but that small and medium-size enterprises (SME) are struggling with the introduction in comparison to larger enterprises. In order to identify enablers and success factors we conduct a qualitative empirical study with 18 companies in different industries. The results show that especially SME fail to apply ML technologies due to insufficient ML knowhow. However, partners and appropriate tools can compensate this lack of resources. We discuss approaches to bridge the gap for SME.
This paper addresses what we call the investment question: under what plausible circumstances, if any, can variable renewable energy (VRE, and solar photovoltaic (PV) in particular) be a good investment? Although VRE has been growing rapidly world-wide, it is generally subsidized. Under what cost and market conditions can solar PV flourish without subsidy? We employ solar insolation and market price data from the U.S. and from Germany to gain insight into the investment question. We find that unsubsidized solar PV is or may soon be a justifiable investment, but that market arrangements may play a crucial role in determining success. We end by sketching a proposal that amounts to a reformed capacity market that would afford participation of solar PV.
Der spartenübergreifende BDI-Arbeitskreis Internet der Energie hat voraussichtliche Veränderungen durch Künstliche Intelligenz (KI) auf die Bereiche Energie und Klima analysiert und den möglichen Beitrag von KI zur Lösung anstehender Herausforderungen in diesen Bereichen erörtert. KI kann einen wesentlichen Beitrag zum Gelingen der Energiewende in Deutschland leisten. Der Energiesektor ist ein zentraler Bestandteil der deutschen Wirtschaft und daher auch in diesem Kontext äußerst relevant.