Intelligent transformation is the process of deriving better business and societal outcomes by leveraging smart devices, big data, artificial intelligence, and cloud technologies. Intelligent transformation can facilitate firms in gaining recognition from external investors, thereby enhancing their market image and attracting larger consumers who are more eager to collaborate. Conversely, intelligent transformation can foster the development of more interactive and multidimensional value-creation models while optimizing the conventional organizational model.[1]
Process
editIntelligent transformation takes place where devices and data center infrastructure work together to create end-to-end solutions.[2] It addresses the needs of a customer and improves the performance of individual vertical industries.[2] This takes place by leveraging big data analytics, machine learning, cloud computing, edge computing, and artificial intelligence.[3]
Intelligent transformation typically involves three capabilities. On the front end, there needs to be smart devices, or sensors and modules in the field to generate the information to be analyzed, a process called Smart Internet of Things (SIoT).[4][5] On the back-end, data center infrastructure processes the information and through algorithms, generate patterns and insights. This is called smart infrastructure. The final is called smart vertical and takes place once the data for specific use cases to be addressed.[3]
The more use cases a vendor is able to address, the more quickly that it will likely become the leading provider of intelligent solutions to a particular industry.[3]
Use cases and industry recognition
editThere are multiple uses cases for smart manufacturing.[6] In the healthcare industry, intelligent transformation can help to develop the next generation of radiology tools and help surgeons create more precise analytics for pathology images.[7] For example, advanced machine learning methods developed can achieve more accurate demand forecast in certain scenarios.
Predix Asset Performance Management from General Electric is designed to optimize the performance of assets. Its goal is to increase reliability and availability and also minimize costs.[8]
Microsoft incorporates intelligent transformation in its Surface Hub 2 digital whiteboard for smart office by integrating hardware and software solutions together.[9] Features developed through intelligent transformation include a 4K camera for Skype, 4 screen tilling, and incorporation of collaboration tools such as Windows, Office, and Skype.[10]
Intelligent transformation is used by Lenovo in various products such as smart speakers, smart watches and smart displays which use various AI technology.[11] Smart devices would include Smart PC Yoga S940 by Lenovo which uses AI technologies to detect user attention and protect work privacy by automatically adjusting the display background.[3] Smart infrastructure would include ThinkAgile Software Defined Infrastructure which is optimized for a variety of workloads and designed to provide more efficient resource allocation to support business growth.[3] An example of vertical use case would include DaystAR for remote monitoring of airline maintenance process, which has been applied to manufacturing and aviation.[3]
Intelligent transformation is also used by LiveTiles to create employee and customer-facing chatbots powered by Microsoft natural language.[12] Amazon Go is another example and uses computer vision, sensor fusion and deep learning to detect when products are taken off the shelf and then places them in a "virtual shopping cart" for checkout.[13]
See also
editReferences
edit- ^ Mao et al (2023) Intelligent Transformation and Customer Concentration, Journal of Organizational and End User Computing, 35(2), 1-15
- ^ a b Cabral, Alvin R. (8 November 2018). "Be customer-centric to drive digital change". Khaleej Times. Retrieved 7 February 2019.
- ^ a b c d e f Rogala, Jesse (29 November 2018). "Lenovo's Intelligent Transformation". Fortune. Retrieved 7 February 2019.
- ^ Teixeira, Fenando A.; Machado, Gustavo V.; Pereira, Fernando M. Q.; Wong, Hao Chi; Nogueira, Jose M. S.; Oliveira, Leonardo B. (13 April 2015). "SIoT". Proceedings of the 14th International Conference on Information Processing in Sensor Networks. pp. 310–321. doi:10.1145/2737095.2737097. ISBN 9781450334754. S2CID 1343903. Retrieved 7 February 2019.
- ^ Panigrahi, Bijaya Ketan (2018). Smart Innovations in Communication and Computational Sciences. Springer. ISBN 9789811089718. Retrieved 7 February 2019.
- ^ Zhou, Ji; Peigen, Li; Yanhong, Zhou; Wang, Baicun; Zang, Jiyuan; Meng, Liu (February 2018). "Toward New-Generation Intelligent Manufacturing". Engineering. 4 (1): 11–20. Bibcode:2018Engin...4...11Z. doi:10.1016/j.eng.2018.01.002.
- ^ Madabhushi, Anant; Lee, George (15 August 2015). "Image analysis and machine learning in digital pathology: Challenges and opportunities". Med Image Anal. 33: 170–175. doi:10.1016/j.media.2016.06.037. PMC 5556681. PMID 27423409.
- ^ "GE Announces New Industrial IoT Software Business". Forbes. 14 December 2018. Retrieved 7 February 2019.
- ^ Warren, Tom (24 September 2018). "Microsoft demonstrates Surface Hub 2 and its rotating display". The Verge. Retrieved 7 February 2019.
- ^ Moorhead, Patrick (2 October 2018). "New Microsoft Surface Hub 2 Sets The High Bar For Workspaces". Forbes. Retrieved 7 February 2019.
- ^ Miller, Michael J. (20 June 2017). "Lenovo Shows New Servers, Tiny Workstation, & Bendable "Concept"". PC World. Retrieved 7 February 2019.
- ^ Gibson, Rebecca (10 July 2019). "How AI is driving a new era of intelligent transformation". Technology Record. Retrieved 7 February 2019.
- ^ Burgess, Matt (22 January 2018). "The technology behind Amazon's surveillance-heavy Go store". Wired. Retrieved 7 February 2019.