In less than a year, generative AI has become a top strategic priority for companies around the world. As industries adopt generative AI for customer service, coding, automation, and many other business cases, users are realizing that this innovative technology requires vast amounts of data, vast computing power, advanced security architectures, and We recognize the need for rapid scalability with the proven benefits of hybrid cloud. Additionally, businesses need the transformative power of hybrid cloud to accelerate generative AI, support sustainability, and upskill their workforces.
New data from IBM examining the relationship between generative AI and hybrid cloud adoption reveals some interesting takeaways about the impact of cloud transformation on modernization efforts:
– Approximately 68 percent of hybrid cloud adopters have already established formal organization-wide policies to guide their approach to generative AI, increasing the link between generative AI and hybrid cloud adoption and integration. It is becoming clear that what is happening.
– However, many of the obstacles that once slowed hybrid cloud adoption are preventing full implementation of generative AI. Cybersecurity and privacy remain key challenges for data and information confidentiality in driving the implementation of generative AI.
For example, 45% of executives working on cloud initiatives are concerned about cybersecurity and the confidentiality of data and information when implementing generative AI. An additional 61% of these cloud leaders highlighted security or compliance concerns as a reason for migrating certain workloads from the public cloud to private clouds or on-premises data centers.
Generative AI is new, but it’s not the only element companies are considering for their cloud agendas. A robust cloud infrastructure is also essential for managing sustainability efforts across an organization and its broader ecosystem. In fact, more than a third (36%) of global leaders who use the cloud to manage internal or third-party sustainability goals say technology has the biggest impact on their company’s sustainability strategy. says.
To address the challenges slowing Gen AI adoption, the actions proposed to accelerate adoption include:
1. Adopt an organization-wide strategy to develop and deploy generative AI and align it with enterprise-level AI and digital transformation.
2. If necessary, move sensitive workloads from the public cloud to a private cloud or on-premises to address security or compliance issues.
3. Address the cybersecurity concerns that hinder generative AI and the benefits this technology brings to threat detection and automation.
– Hybrid cloud is essential to deploy generative AI and help companies achieve their sustainability goals, but having enough employees with the necessary cloud skills continues to hinder progress . On average, 58% of global decision makers say cloud skills remain a major challenge, indicating the need for further upskilling efforts. This will enable more employees to use and benefit from hybrid cloud and generative AI tools and technologies.
As concerns grow over the cloud skills shortage, IBM research highlights the following courses of action:
1. Use hybrid cloud to deploy, track, and manage your internal, as well as partner and third-party, sustainability goals.
2. Expand hybrid cloud and generative AI upskilling to enable more employees to use these transformational technologies more effectively.
3. Future-proof your organization by integrating generative AI into your workflows and applications.