How AI Is Being Used as a Source of Innovation in Firms? - Paper Example

Purpose of the Study

The aim of this dissertation is to explore how AI is being used as a source of innovation in firms. To date, there is no study that has delved into this topic; thus, it will fill the gaps identified in the literature. The study is unique in the sense that it feels the research gap by exploring the concept of AI in contact centres and project management. The research will provide insights into the concept of AI with specific application to the call centres and project management. The focus of the research is on the issue of implementing AI in service desks and project management as a source of information for organisations, which been ignored in the literature. So far, little has been researched on this study probably because it is an emerging discipline. The outcome of this study is expected to make recommendations about the application of AI in call centres and project management.

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Research Hypothesis and Questions

The research stipulates that adoption of AI triggers innovation in its area of application. The research seeks to find out the relationship between artificial intelligence and innovation using the case of Atos and the use of its products service desk and project management. Therefore, the study is guided by the following research questions:

1. Does adoption of artificial intelligence lead to innovation in firms?

2. How does artificial intelligence help firms to spearhead innovation in their specific areas of application?

Literature Review

Over the past six decades, there has been a general consensus among economists about the potential for significant underinvestment in research in areas of low appropriability for companies. Consequently, useful insights have been gained into the conditions under which the innovation incentives may be distorted. Two concepts are particularly important in this literature regarding the impact of artificial intelligence on innovation and strategy. First, potential issues associated with the development of a new broadly applicable solution. Second, potential challenges related to coordination of the process from adoption to diffusion of the new general purpose technology. The areas of artificial intelligence evolving rapidly such as deep learning are more likely to experience the above issues than the technological innovations related to narrow domains such as industrial robots.

First, the organization is likely to face great challenges when providing appropriate incentives for innovation of solutions that have the potential to drive change across a wide number of distinct technological and organizational applications. Studies argue that general purpose technologies often have the tendency to enhance and influence productivity and quality across a broad continuum of sectors (David, 1990; Bresnahan and Trajtenberg, 1995). A case in point is the invention of the electric motor which studies reported brought about widespread technological and organizational transformation across many sectors such as manufacturing, retail, building and construction, and agriculture. Such general purpose technologies often meet three distinct criteria namely; applicability across sectors, the ability to spur further in innovation in the target sectors, and the tendency for the technologies themselves to improve rapidly.

Some studies have suggested that general purpose technologies are characterized by pervasiveness resulting from both vertical and horizontal externalities in the process of innovation. As such, it can lead to underinvestment and different investment types based on the capital and social returns realized across the various application sectors (Bresnahan and Trajtenberg, 1995). For example, if the general purpose technology complements applications in each sector, it is likely that lack of innovation incentives in one sector can have deleterious effects across the other sectors leading to low investment in the innovation. The market structure and conditions for appropriability play a significant role in determining private innovative investment incentives. However, sector-specific innovation also spawns innovation in the general purpose technology itself leading to the subsequent demand in other application sectors. Since these benefits often are not appropriated within the sector in which general purpose technology originated, inadequate coordination between these technologies and the application sectors is likely to significantly reduce investment in innovation. Notwithstanding these issues, the cycle of innovation between the general purpose technologies and the various application sectors is likely to create an economic transformation across diverse companies as they adopt the innovation. Studies provide empirical evidence of how the microprocessor as a general purpose technology, for example, impacts the economy as a whole (among many others, Bresnahan and Greenstein (1995); Brynjolfsson and Hitt (1999); and Bresnahan, Brynjolfsson, and Hitt (2001)). Artificial intelligence can be understood as a general purpose technology and the insights derived from the microprocessor provide a foundation for understanding their impacts on innovation and strategy.

The second theoretical framework for the exploration of artificial intelligence is the economics associated with research tools. It is worth noting that some research innovations do not just lead to new inventions in the application sectors they were intended, but rather, they lead to inventions in other sectors as well. A classic example was reported by Griliches (1957) who in his review of the hybrid corn suggested that the application of some new research tools spawned beyond the boundaries of its original...