Recent advances in technology in the fields of artificial intelligence (AI) and machine learning (ML) are significantly changing business environment. In the high-tech competitive edge, it has the immense use of computerized knowledge analytics, particularly for information management and the industrial sector. This study aims to analyze adoption of artificial intelligence among Nepalese industries, how industries are ready to adopt AI, challenges being faced and ways for improvement. Findings of the study revealed that on average 20.77% industries are ready in terms of technological sufficiency, 29.91% industries are ready in terms of management efficiency, and 39.23% industries are ready in terms of value creation potential in the firm for the adoption of AI intelligence. Further, 56% industries stated that small market size and lack of skilled manpower are the major challenges for AI adoption. Therefore, this study concludes that as stated by 44% industries, if they get adequate and relevant support from government, it would be easier for them to adopt AI.
TopIntroduction
Technological Adoption is one of the principal drivers of competition. It plays a major role in structural changes of industries as well as in creating new industries (Porter, 1985; Berry & Taggart, 1994; Smith & Sharif, 2007; Turchin et al., 2021). The future world can be said the world of machines that work as intelligently as to replicate the behavior of human mind which can be considered as the artificial intelligence. Artificial intelligence in the last two decades has greatly improved performance of the manufacturing and service systems (Yadav & Yadav, 2018). Artificial Intelligence (AI) is today’s demand all over the globe as the global business and industrial competitiveness has reached the highly defined forms of Automation and Robotics (Goel & Gupta, 2020). It is the weapon of 21st century’s market to create high-tech competitive edge which has immense use of computerized knowledge analytics, particularly for information management and the industrial sector (Xu, Wei, & Fan, 2002). As McKendrick (2021) during Pandemic in US based companies AI Adoption Skyrocketed in over the last 18 months.
With the development of internet and mobile technologies, electronics, nanotechnology, adoption of AI are now speeding up (Dirican, 2015). During the last few decades, companies have reengineered business processes on the back of digital data and computer networks (Goel & Chen, 2008). Artificial Intelligence is a tool that will increase access to cheaper and more efficient services (Semmler & Rose, 2017). So nowadays, small and medium enterprises (SMEs) are incrementally using e-business tools for competing in an extremely hostile market and gain the global access (Chatzoglou & Chatzoudes, 2014). Recently, there has been a remarkable increase in the adoption of AI technology in organizations as new forms of work have increased substantially (Alsheibani et al., 2019).
Some literature also argues that the market adoption of AI is highly variable (Weber & Schütte, 2019). Insufficiency of systematic and reliable data made it impossible to advance consistent figures about the adoption rate for all types of artificial intelligent agents (Popa, 2011). Alongside the common causes of expert systems penetration to farm level, there are also specific problems related to this adoption process. Except indoor environments 287 (greenhouses, pig and bird shelters), where integrated expert systems with a high degree of independence in making operational decisions are already commercially available, the expert systems are generally still disconnected from background and from previous experience when delivering solutions and also are highly dependent by integrity of data supplied by the operator (Popa, 2011). Despite the envisaged benefits of AI adoption, many organizations still struggle to drive their AI adoption forward (Alsheibani et al., 2019). Further, as Pillai & Sivathanu (2020), security and privacy issues negatively influence the adoption of AI technology. Further, survey results from 297 Chinese companies suggest that companies’ perceived complexity toward AI constrains AI adoption, while technology competence and regulatory support encourage AI adoption (Pan et al., 2021). In spite of its some drawbacks, plethora of literature suggest that adoption of AI helps organization to grow in modern era. But, in case of Nepal use and adoption of AI is still in infancy stage in case of industries.
Nepal is developing country which has very less presence of research and development budgets in business and industries (Shrestha, 2021). The existing technologies in Nepalese industries are the one which is already outdated in global scenario, making Nepalese production and business weak in global as well as local market, as Nepal has allowed foreign products in local market in an easy way through various treaties and regional agreements (Paudel & Devkota, 2018). Nepalese industrial sector still has majority of companies that operates with labor based manual technologies (Devkota et al, 2021) rather than automated and advanced forms of Artificial Intelligence using Hi-Tech computer technology. If required technology can be created in Nepalese territory, it can help to reduce the trade deficit, as well as helps in development of Nepalese science and technological as well as industrial sector (Rajbhandari et al., 2020).