Businesses are struggling with numerous variables to determine what their stance should be
regarding artificial intelligence (AI) applications that deliver new insights using deep learning.
The business opportunities are exceptionally promising. Not acting could potentially be a
business disaster as competitors gain a wealth of previously unavailable data to grow their
customer base. Most organizations are aware of the challenge, and their lines of business
(LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
IDC believes that this emerging environment is to date still highly undefined, even as
businesses must make critical decisions. Should businesses develop in-house or use VARs,
systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some
hybrid form? Can they use existing infrastructure, or do AI applications and deep learning
require new servers with new capabilities? We believe that many of these questions can be
Businesses are struggling with numerous variables to determine what their stance should be
regarding artificial intelligence (AI) applications that deliver new insights using deep learning.
The business opportunities are exceptionally promising. Not acting could potentially be a
business disaster as competitors gain a wealth of previously unavailable data to grow their
customer base. Most organizations are aware of the challenge, and their lines of business
(LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
IDC believes that this emerging environment is to date still highly undefined, even as
businesses must make critical decisions. Should businesses develop in-house or use VARs,
systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some
hybrid form? Can they use existing infrastructure, or do AI applications and deep learning
require new servers with new capabilities? We believe that many of these questions can be
