Book Description

Why does (AI) and digital transformative combination technologies raise productivity growth or improve service performance? From 1995 to 2004 year, US experienced an acceleration in productivity growth, largely reflecting gains associated with the diffusion of ICT technologies. From the early to mid-2000 year onward, productivity growth has slowed down. The potential impacts of the ongoing digital transformation on productivity also need to consider in the context of this long term slowdown. When, the precise reasons for today's productivity remain difficult to a number of factors are likely to contribute as below factors: The first factor that has limited the impacts of digital transformation is the state of diffusion of digital technologies across the economy. When, many firms now have across to broadband networks, the use of more advanced digital tools and application with firms still differs greatly across countries. Moreover, these are important differences between rapid technological change, advanced technologies are initially only adopted by some leading firms and then only later diffuse to all firms as the technologies because more established new business models grow, such as applying digital and (AI) technological combine method to raise productivity growth is caused and costs fall. Consequently, these is large demand between what can be automated from a technical point of view and what may already be implemented by frontier firms and what is actually being achieve to raise productivity growth aim. So, (AI) and digital transformative technology influence future raising productivity growth or improving service aim achievement for many manufacturing and service industry demand.The second factor indicator that the available evidence suggests that the wide-spread benefits of digitalization productivity are not enough. Firms expect to help strengthen investment ( in tangible and intangible assets), e.g. (AI) technology. The same time, there are now starting to experience labor shortages, e.g. in certain technical occupations, such as data scientists. Due to the technological change is fast and growing demand for productivity growth has been increasing. SO, it will influence future (AI) robotic learning system and digital technological combination to be applied to manufacturing and service industries' needs to be raised. Due to many firms expect to find methods to raise productivity growth in order to reduce production costs.However, (AI) and digital technological development can cause multiple forms of disruption, from shifts in demand for workforce skills to changes in market structure, the need for new business models, new patterns of trade and investment. The (AI) and digital potentially transformative technologies can create new inventions, e.g. from quantum computing and advanced energy storage to new forms of 3D printing, big data analytics and neuro-technologies. These new product creative industries must lead the new product manufacturers to expect to learn how to apply (AI) and digital technology to raise productivity growth when their manufacturing processes. IN fact, (AI) is the ability of learning machine and system to acquire and apply knowledge and carry out intelligent behavior. Early efforts to develop (AI) centered on defining rules that software could use to perform a tack, such systems would work in speech recognition, (AI) skill. Increase in computational power, new statistical methods and advances in big data, have brought major breakthroughs to the field of (AI), especially in " vertical " (AI) like automated vehicles as opposed to " general". (AI) with machine learning algorithms that identify complex patterns in large data sets. Software applications can perform tasks and simultaneously learn how to improve productive performance.