Many companies are focusing on advancements in the field of generative AI. This state-of-the-art technology leveraging sophisticated algorithms and machine learning, creates new content and insights to foster innovation and solve complex issues. It can produce realistic text, images, audio, video, and synthetic data for AI model training. Its applications span from content creation and data augmentation to drug discovery and personalized learning. As businesses generate more data, having a robust computing environment becomes essential. That’s why hybrid cloud solutions have become popular among companies as they seamlessly work among public and private clouds while keeping some data on premises, facilitating the sharing of data and applications. This creates a well-coordinated environment that enables data and application portability.
I’ve been exploring, in partnership with IBM, how different technological advancements come together to propel businesses toward new heights in their transformation journey. In this article I want to highlight the power that emerges across industries when hybrid cloud and generative AI converge.
In today’s business landscape many organizations prioritize incorporating technology to boost efficiency and provide exceptional customer experiences. That’s why we’ve seen over the last year an increase in the adoption of generative AI models by companies of all sizes across multiple industries. However, implementing these models brings challenges such as data management, scalability, governance, security, and transparency.
The integration of cloud technology with AI models offers advantages for businesses. These benefits include the creation of an environment for handling significant amounts of data required to train and implement generative AI models. This approach ensures that generative AI models can be trained and used in a setting that safeguards data and intellectual property. Moreover, it enables a resilient environment while leveraging AI for strategic planning and decision making.
By combining the use of AI with the implementation of a cloud, enterprises can not only embrace cutting edge technologies, but also effectively maximize their potential capabilities.
IBM’s Watsonx serves as an example illustrating how this combination empowers businesses. It is an AI and data platform that facilitates businesses in scaling up their utilization of AI by leveraging their data from anywhere it is stored using the cloud’s capability as well as leveraging data stored on premises.
Recently I had the opportunity to engage in a discussion on this topic with Nick Otto, head of strategic global partnerships at IBM. According to Nick, “Businesses really want and need secure, flexible infrastructure to run AI workloads wherever they need them.” This explains why companies are seeking solutions that seamlessly integrate AI with cloud technology.
One of the advantages of combining cloud and AI technologies is enhanced data security and privacy. The hybrid cloud model strategically distributes data across public clouds ensuring a blend of private storage security and public scalability. In addition, AI strengthens this framework by enabling automation of data management and predictive security protocols which helps protect against potential breaches and unauthorized access. These technologies work together to not only provide protection for an organization’s data but to also prioritize governance and privacy concerns.
Recognizing the potential of these technologies empowers businesses to effectively optimize their benefits. However, it’s important to approach the deployment of AI and hybrid cloud solutions with caution rather than rushing into a deployment for the sake of speed. It’s best to evaluate how these technologies align with long-term organizational needs and leverage their advantages accordingly.
For information, on the convergence of AI and hybrid cloud technology, visit IBM’s blog to gain further insights into their approach.
By Ronald van Loon
