Artificial intelligence prompt engineering as a new digital competence: Analysis of generative AI technologies such as ChatGPT

Pawel Korzynski, Grzegorz Mazurek, Pamela Krzypkowska, Artur Kurasinski
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引用次数: 1

Abstract

Objective: The article aims to offer a thorough examination and comprehension of the challenges and pro‐ spects connected with artificial intelligence (AI) prompt engineering. Our research aimed to create a theoret‐ ical framework that would highlight optimal approaches in the field of AI prompt engineering. Research Design & Methods: This research utilized a narrative and critical literature review and established a conceptual framework derived from existing literature taking into account both academic and practitioner sources. This article should be regarded as a conceptual work that emphasizes the best practices in the domain of AI prompt engineering. Findings: Based on the conducted deep and extensive query of academic and practitioner literature on the subject, as well as professional press and Internet portals, we identified various insights for effective AI prompt engineering. We provide specific prompting strategies. Implications & Recommendations: The study revealed the profound implications of AI prompt engineering across various domains such as entrepreneurship, art, science, and healthcare. We demonstrated how the effective crafting of prompts can significantly enhance the performance of large language models (LLMs), gen‐ erating more accurate and contextually relevant results. Our findings offer valuable insights for AI practition‐ ers, researchers, educators, and organizations integrating AI into their operations, emphasizing the need to invest time and resources in prompt engineering. Moreover, we contributed the AI PROMPT framework to the field, providing clear and actionable guidelines for text‐to‐text prompt engineering. Contribution & Value Added: The value of this study lies in its comprehensive exploration of AI prompt engineer‐ ing as a digital competence. By building upon existing research and prior literature, this study aimed to provide a deeper understanding of the intricacies involved in AI prompt engineering and its role as a digital competence. Article
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人工智能促使工程成为一种新的数字能力:ChatGPT等生成式人工智能技术分析
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CiteScore
7.20
自引率
7.90%
发文量
15
期刊介绍: Entrepreneurial Business and Economics Review (EBER), as multi-disciplinary and multi-contextual journal, is dedicated to serve as a broad and unified platform for revealing and spreading economics and management research focused on entrepreneurship, individual entrepreneurs as well as particular entrepreneurial aspects of business. It attempts to link theory and practice in different sections of economics and management by publishing various types of articles, including research papers, conceptual papers and literature reviews. Our geographical scope of interests include Central and Eastern Europe and emerging markets, however we also welcome articles beyond this scope. The Journal accept the articles from the following fields: -Entrepreneurship and Business Studies (in particular entrepreneurship and innovation, strategic entrepreneurship, corporate entrepreneurship, entrepreneurship methodology, new trends in HRM and HRD as well as organizational behaviour, entrepreneurial management, entrepreneurial business, management methodology, modern trends in business studies and organization theory, policies promoting entrepreneurship, innovation, R&D and SMEs, education for entrepreneurship), -International Business and Global Entrepreneurship (especially international entrepreneurship, European business, and new trends in international business, IB methodology), -International Economics and Applied Economics (in particular the role of entrepreneurship and the entrepreneur in economics, international economics including the economics of the European Union and emerging markets, as well as Europeanization, new trends in economics, economics methodology).
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