Purpose

Artificial intelligence (AI) is the most progressive commodity among current information system applications. In-house development and sales of beneficial products are difficult for many software development and service companies (SDSCs). SDSCs have some implicit concerns about implementing AI software development due to the complexity of AI technology; they require an evaluation framework to avoid development failure. To fill the void, this study identified the factors influencing SDSCs when developing AI software development.

Design/methodology/approach

Based on complex adaptive systems theory, three aspects were developed as the main factors of hierarchy, namely, employees' capabilities, environmental resources and team capabilities. Fuzzy analytic hierarchy process (FAHP) was used to assess the SDSCs' attitude. Based on SDSCs, attitudes toward implementing AI software projects were collected to calculate the hierarchy of factors.

Findings

The outcome of FAHP is used as understanding the key factors of SDSCs for selecting an AI software project, toward the improvement of overall project planning. Employees' stress resistance was considered as a priority for the project, although professional AI skills and resources were also important.

Originality/value

This study suggested three variables developed using complex adaptive systems. This study contributes to a better understanding of the critical aspects of developing AI software projects in SDSCs. The study's findings have practical and academic implications for SDSCs and subsequent academic development, broadening the scope of AI software development research.

中文翻译：

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基于模糊层次分析法和复杂自适应系统的软件行业人工智能项目评价

目的

人工智能 (AI) 是当前信息系统应用中最先进的商品。对许多软件开发和服务公司 (SDSC) 来说，内部开发和销售有益产品很困难。由于 AI 技术的复杂性，SDSC 对实施 AI 软件开发有一些隐含的担忧；他们需要一个评估框架来避免开发失败。为了填补空白，本研究确定了在开发 AI 软件开发时影响 SDSC 的因素。

设计/方法/途径

基于复杂适应系统理论，发展了三个方面作为层次结构的主要因素，即员工能力、环境资源和团队能力。模糊层次分析法 (FAHP) 用于评估 SDSC 的态度。基于 SDSC，收集了对实施 AI 软件项目的态度，以计算因素的层次结构。

发现

FAHP 的结果用于了解 SDSC 选择 AI 软件项目的关键因素，以改进整体项目规划。员工的抗压能力被认为是该项目的优先事项，尽管专业的 AI 技能和资源也很重要。

原创性/价值

这项研究提出了使用复杂自适应系统开发的三个变量。这项研究有助于更好地理解在 SDSC 中开发 AI 软件项目的关键方面。该研究的发现对 SDSC 和随后的学术发展具有实践和学术意义，拓宽了 AI 软件开发研究的范围。