The impact of the integration of artificial intelligence on Software-as-a-service applications and industry

The study’s objective is to understand how the integration of AI impacts Software-as–a-service (SaaS) applications and industry. With the development of cloud computing, more enterprises moved their products and services from independent deployment to cloud platforms to reduce time and investment in the deployment and maintenance. As a result of it, the fast growth of SaaS market is approaching saturation and infusing artificial intelligence (AI) into SaaS applications innovation is expected to trigger unprecedented innovation in SaaS industry and differentiate SaaS enterprises from their competitors. Indeed, many big players have announced their offerings that integrated AI and applied them in the market to carve out positions in the market, which indicates the potential room for leveraging AI across various segments of SaaS industry. A review of existing literatures revealed the saturated state of SaaS industry and some theoretical benefits associated with integrating AI but lacks researches about actual impacts of implementing AI + SaaS model including opportunities, challenges, other affecting factors， potential solutions and prospect, especially compared to traditional SaaS model. To achieve the aim of this research, this study employed qualitative methods of literature review and interviews and used thematic data analysis method. This dissertation obtained some insights based on empirical findings explored in the study. Firstly, the infusion of AI provided many benefits to users as well as SaaS providers, which made most of them hold optimistic view of the future of AI + SaaS model. Secondly, cloud computing plays an important role in stimulating the development of AI + SaaS model since it provides more opportunities for SaaS start-up, reduces technology difficulties, and technically supports AI. Thirdly, CRM is regarded as the next flashpoint of the integration of AI because of its accumulated experience. Lastly, in transitioning from traditional SaaS model to AI + SaaS model, many SaaS and AI cloud services vendors have encountered some obstacles in realizing applications of AI-powered SaaS products based on actual situation. As data is the essence of AI, enterprise data acquirement is the biggest challenge because of customer data privacy. Meanwhile, the shortage of data analysis talents is another challenge. For now, AI applications is hardly to indeed penetrate into the points of various scenarios due to AI technology itself limitations. The concern of AI fully replacement of human resources is unnecessary because technology is less advanced and the combination of human efforts and AI could generate more value in SaaS. Key words: Artificial Intelligence (AI); Software-as–a-service (SaaS); Cloud computing; Dat