• International Journal of Technology (IJTech)
  • Vol 11, No 1 (2020)

Managing Artificial Intelligence Technology for Added Value

Managing Artificial Intelligence Technology for Added Value

Title: Managing Artificial Intelligence Technology for Added Value
Mohammed Ali Berawi

Corresponding email:


Cite this article as:
Berawi, M.A., 2020. Managing Artificial Intelligence Technology for Added Value. International Journal of Technology. Volume 11(1), pp. 1-4

1,256
Downloads
Mohammed Ali Berawi Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Email to Corresponding Author

Abstract
Managing Artificial Intelligence Technology for Added Value

Many industrial sectors are in the middle of a digital transformation that has emerged from the advancement of information and data technology, enhancing the use of computers and automation with smart and autonomous systems powered by data and machine learning. This revolution has been broadly adopted in industry by initiating the use of digital technologies, sensor systems, intelligent machines, and smart material in its processes.

Some examples of industrial innovation are the invention of artificial intelligence (AI), the deployment of the Internet of Things (IoT)/Internet of Services (IoS), 3D printing/additive manufacturing, machine learning, and the use of Big Data. These have enables the digitization, automation, or integration of service and product value chains. Implementing digitization and automation is believed to help construction transform into a technology-driven industry and keep pace with other industries. 


AI Technology Impact

    Many industries, from product manufacturing and construction projects to business services, are now extensively using AI to facilitate industrial automation . AI has become an industry, with more investment and new technologies and applications being produced. It is also creating benefits for other industries by improving performance, enhancing efficiencies, and offering new and extended markets—the digital economy. 

    As technology progresses, the nature of work in organizations, social relations and interaction, and individual lifestyles are rapidly changing. AI is making  organizations provide better customer service and products, changed with the impact of robotics and automation. Automation has already reduced the number of human workers doing repetitive work and increased work in creative industries.

    AI facilitates  decision-making, creates integrating  systems, and simplifies complex mechanisms though automation. For example, a computer-aided design system that uses 3D modelling in project management or design helps increase product or project efficiency and effectiveness and improves communication and collaboration between stakeholders, while the availability of information from sensor networks in the application of the IoT plays an important role in augmenting and improving the quality of decision-making. 3D printing technology is also seen as an innovative strategy with the potential to revolutionize industry, since it is projected to effectively save time, reduce costs, and help protect the environment by generating less material waste. Further, smart 3D printing can be used to teleport an object from one place to another. A mobile compact 3D printing machine can produce items to meet everyday needs. The use of blockchain as a group of people sharing data with trust enhances transaction transparency in the blockchain network. Furthermore, machine learning as an artificial approach is used to solve problems such as face and speech recognition, online fraud detection, and automatic language translation.  Public transportation services are incorporating AI technology to create self-driving cars, trains, and planes. AI technology is also expected to help us create artificial lifeforms, personal assistants such as Echo and Alexa and human-like robots capable of complex interactions like Valkyrie and Sophia . AI systems are also greatly influencing our communication and interaction. Machine learning models will help us understand context and meaning for and in various languages. 

    Given the many benefits of technology in project—product—service deliveries, I argue that the value of tomorrow’s product or service will not much depend on production cost but rather the intellectual properties involved in designing and creating and product or service.