May 21, 2018 | Written by: Roman Tuma, Vice President, Asia Pacific - IBM Cloud and Martin Chee, Vice President, Analytics, Asia Pacific IBM Global Markets - Cloud Sales
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Forward-looking enterprises should be on the road to AI.
Companies across the globe are looking to AI as a catalyst to transform their businesses and reinvent themselves as intelligent enterprises. To gain more insight around how companies are planning on using AI, the IBM Global C-suite Study program conducted a global survey of more than 3,000 C-level executives across 20 industries.
The findings revealed that of those surveyed:
- Only 11 percent of organizations are taking a strategic approach to enabling their enterprise with AI technologies.
- More than half of top executives believe that AI will give them a competitive advantage by improving customer experience and personalization.
- Around 40 percent of organizations are very likely to invest in cloud-based technologies to complement their AI outlook.
- The study also found that another 40 percent of organizations who participated in the study are pushing ahead with AI.
Though AI is rapidly making inroads into the world of business and disrupting existing models and processes, many enterprises across the globe still struggle to use AI strategically and align it with their business to drive meaningful outcomes.
Scaling the AI ladder
To build and execute an effective AI strategy, IBM is helping enterprises make use of its data-driven AI implementation approach called the AI ladder, which consists of foundational technologies available to enterprises of all sizes.
These foundational technologies — hybrid data management, unified governance and integration, and data science and business analytics — create the rungs required to move up the ladder. They help build an effective data strategy by aggregating data from multiple sources.
But what if your enterprise has data scattered across multiple infrastructures or clouds?
Managing multicloud environments
To respond to the changing needs of business and find cost efficiencies, we find that enterprises are progressively managing their computing needs by running their data and applications on multiple clouds. While this new topology has benefits, it also makes it challenging for businesses to mine their data, apply analytics and derive intelligent insights. It likewise slows down the process for organizations to become fully AI enabled.
IBM introduced its private cloud offering last year with a view to ease this problem. IBM Cloud Private software is designed to help companies unlock value from their technology investments in core data and applications and extends cloud-native tools across public and private cloud. It is designed to deliver a single platform located behind an organization’s firewall. Organizations can leverage an on-premises software portfolio or integrate next-generation data and software optimized for cloud.
Built on open source frameworks such as containers, Kubernetes and Cloud Foundry, IBM Cloud Private offers capabilities that can help improve flexibility, control and security while speeding up integration with public clouds. Plus, cloud management solutions are included so users can govern multicloud infrastructures and applications.
Increasing data insights with IBM Cloud Private for Data
To bring users closer to their AI destinations, IBM recently introduced IBM Cloud Private for Data, an integrated data science, data engineering and app-building platform designed to help companies uncover previously hidden insights from their data. The platform is also designed to enable users to build and use event-driven applications capable of analyzing the torrents of data from Internet of Things (IoT) sensors, online commerce, mobile devices and more.
IBM Cloud Private for Data is designed to provide seamless access to data on-premises and across clouds, behind the safety of a firewall, with data ingestion rates of up to 250 billion events per day.
Built on the IBM Cloud Private platform, Cloud Private for Data is an application layer deployed on the Kubernetes open source container software and can be deployed in minutes. Using microservices, it forms a truly integrated environment for data science and application development.
With its multicloud management capabilities, IBM Cloud Private positions users to optimize management of applications and data across multiple infrastructures, thus helping to put users a step ahead in their AI journey.
The road to AI is becoming a reality for a lot of organizations who are venturing into it, not only to help them gain competitive advantage, but also to emerge as the truly cognitive enterprises of tomorrow.
Learn more about IBM Cloud Private.