Pillar 4:
Tech
Deploying emerging technologies seamlessly and at scale
Pillar 4:
Tech
Deploying emerging technologies seamlessly and at scale
The Hybrid Cloud Leaders are putting emerging technology at the heart of their hybrid cloud strategies: 75% say that their hybrid cloud environment facilitates the use of emerging tech, compared with just 38% of Followers.
The Hybrid Cloud Leaders are mastering emerging tech
Q. How easy or difficult is it to adopt the following in your hybrid cloud environment? (Those answering ‘easy’ or ‘very easy’)
The Hybrid Cloud Leaders are putting emerging technology at the heart of their hybrid cloud strategies: 75% say that their hybrid cloud environment facilitates the use of emerging tech, compared with just 38% of Followers.
The Hybrid Cloud Leaders are mastering emerging tech
Q. How easy or difficult is it to adopt the following in your hybrid cloud environment? (Those answering ‘easy’ or ‘very easy’)
The data suggests that some technologies, such as blockchain and edge computing, are straightforward for all companies to implement. But the Hybrid Cloud Leaders are excelling at implementing technologies across the board.
Miao Song, Global Chief Information Officer at GLP, says embedding emerging technology in the business is a positive step.
“In the end, whether it’s AI, machine learning, RPA or blockchain, the technology has to solve the business challenges,” she says. “For example, a pharma company uses AI machine learning to analyze their data, and also to run clinical trials.”
Tetsuya li, Deputy Head of Infrastructure and Solution Sales Unit, Global Solution Business at Fujitsu, says his company is experimenting with emerging technology in the cloud.
“On our part, we are trying to develop supercomputing and would like to bring it closer to cloud,” he says. “We are migrating supercomputer technology onto the cloud, and Fujitsu has experts who are skilled in this. We also have people who have strong skills in developing the cloud. They have been releasing products and services in these respective areas. We would like to merge these groups to enable the creation of new products and services.”
“When we get data back from our tires through the internet of things, it eventually gets back into an application in Bridgestone that is heavy in AI and machine learning, called Tirematics. That’s where complex proprietary algorithms live, and they make predictions on preventative maintenance based on the miles driven and what we know about the tire and where it’s located from a climate perspective.”
Tom Corridon, Vice President of Cloud and Infrastructure, Bridgestone Americas