Grundlagen der Künstliche Intelligenz (KI)

Mockenhaupt, Andreas

doi:10.1007/978-3-658-32773-6_3

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…This results in smart, extracted information (Faroukhi et al. , 2020; Mockenhaupt, 2021). The goal is thus to provide AI-powered information that allows data-based decision-making (Bhimani and Willcocks, 2014), which might be of value for internal or external partners.…”

Section: The Transformation From Big Data To Ai-powered Information W...mentioning

confidence: 99%

AI-powered information and Big Data: current regulations and ways forward in IFRS reporting

Leitner-Hanetseder

Lehner²

2022

JAAR

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PurposeWith the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining economic benefits. AI-powered information and Big Data (simply data henceforth) have quickly become some of the most important strategic resources in the global economy. However, their value is not (yet) formally recognized in financial statements, which leads to a growing gap between book and market values and thus limited decision usefulness of the underlying financial statements. The objective of this paper is to identify ways in which the value of data can be reported to improve decision usefulness.Design/methodology/approachBased on the authors' experience as both long-term practitioners and theoretical accounting scholars, the authors conceptualize and draw up a potential data value chain and show the transformation from raw Big Data to business-relevant AI-powered information during its process.FindingsAnalyzing current International Financial Reporting Standards (IFRS) regulations and their applicability, the authors show that current regulations are insufficient to provide useful information on the value of data. Following this, the authors propose a Framework for AI-powered Information and Big Data (FAIIBD) Reporting. This framework also provides insights on the (good) governance of data with the purpose of increasing decision usefulness and connecting to existing frameworks even further. In the conclusion, the authors raise questions concerning this framework that may be worthy of discussion in the scholarly community.Research limitations/implicationsScholars and practitioners alike are invited to follow up on the conceptual framework from many perspectives.Practical implicationsThe framework can serve as a guide towards a better understanding of how to recognize and report AI-powered information and by that (a) limit the valuation gap between book and market value and (b) enhance decision usefulness of financial reporting.Originality/valueThis article proposes a conceptual framework in IFRS to regulators to better deal with the value of AI-powered information and improve the good governance of (Big)data.

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Section: The Transformation From Big Data To Ai-powered Information W...mentioning

confidence: 99%

AI-powered information and Big Data: current regulations and ways forward in IFRS reporting

Leitner-Hanetseder

Lehner²

2022

JAAR

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Quality Management quo Vadis: A Snapshot of the German Quality Management Environment

Kainer¹,

Linke²,

Omondi³

et al. 2022

IJMSBA

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The present study was a snapshot of the status of quality management in the DACH region. As part of a survey of 229 executives and employees as well as independent consultants, the current state of quality management was investigated. Basically, it can be said that quality management is largely integrated into the companies, with a few exceptions. The majority of the companies use the standardized method of ISO EN 9001:2015, a considerable proportion use the EFQM method, which places great emphasis on the deductible and assessment. The big difference among the companies surveyed is the lived “spirit” of quality management. It is predominantly reported that the companies have a functioning quality management system; however, many report that there is great potential for improvement in the design and use. Here quality management is often seen as a necessary evil because the certificates are needed for the customers. Quality management is seen as a compulsory exercise and not as a facilitator for innovations and continuous improvement. Business excellence – in the freestyle – is a foreign word. The only remedy is a reflection on a desired reflection on future-oriented business excellence. In order to achieve this, both a reengineering of the business processes and a changed mindset and leadership of the executives and the employees involved must find their way into the company.

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User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Study Protocol for a Multimethod Research Project (Preprint)

Raszke,

Giebel,

Abels

et al. 2024

JMIR Research Protocols

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Grundlagen der Künstliche Intelligenz (KI)

Cited by 4 publications

References 2 publications

AI-powered information and Big Data: current regulations and ways forward in IFRS reporting

AI-powered information and Big Data: current regulations and ways forward in IFRS reporting

Quality Management quo Vadis: A Snapshot of the German Quality Management Environment

User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Study Protocol for a Multimethod Research Project (Preprint)

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