Nutanix has announced the findings of its seventh annual Enterprise Cloud Index (ECI) survey and research report, which measures global enterprise progress with cloud adoption. This year’s report sheds light on Generative Artificial Intelligence (GenAI) adoption, investment priorities, and benefits along with key challenges organizations face to meet the demands of these emerging workloads.
As GenAI application adoption and implementation move at a blazing pace, the ECI uncovered that while the majority of organizations have already implemented a GenAI strategy, implementation targets vary significantly. Organizations are eager to leverage GenAI for productivity, automation, and innovation, but they also face critical hurdles in the form of data security, compliance, and IT infrastructure modernization. Further, 90% of respondents expect their IT costs to rise due to GenAI and modern application implementation. But promisingly, 70% of organizations expect to make a return on their investment from GenAI projects over the next two to three years.
“Many organizations have reached an inflection point with GenAI implementation and deployment,” said Lee Caswell, SVP, Product and Solutions Marketing at Nutanix. “This year’s ECI revealed key trends that we’re hearing from customers as well, including challenges with scaling GenAI workloads from development to production, new requirements GenAI creates for data governance, privacy, and visibility, and integration with existing IT infrastructure. To successfully unlock ROI with GenAI projects, organizations need to take a holistic approach to modernizing applications and infrastructure and embrace containerization.”
Key findings from this year’s report include:
- Application containerization is the new infrastructure standard. Nearly 90% of organizations report that at least some of their applications are now containerized, and this number is expected to grow with the rapid adoption of new application workloads like GenAI. Simply put, 94% of respondents agree that their organization benefits from adopting cloud native applications/containers. This approach to infrastructure and application development should be considered the gold standard for delivering seamless, secure access to data across hybrid and multicloud environments.
- GenAI application adoption and implementation continue at a rapid pace. Over 80% of organizations have already implemented a GenAI strategy with only 2% of organizations admitting that they have not started planning their GenAI strategy. That said, implementation targets vary significantly. Most organizations believe GenAI solutions will help improve their organization’s levels of productivity, automation, and efficiency. Meanwhile, real-world GenAI use cases gravitate towards customer support and experience solutions today. However, organizations aspire to apply GenAI solutions to cybersecurity and data protection workloads in the near future.
- GenAI adoption will challenge traditional norms for data security and privacy. 95% of respondents agree that GenAI is changing their organization’s priorities, with security and privacy being a primary concern. Over 90% of organizations say data privacy is a priority for their organization when implementing GenAI solutions. Clearly, organizations understand that security and privacy are critical components of GenAI success. However, a staggering 95% of respondents still believe their organization could be doing more to secure its GenAI models and applications. Security and privacy will remain a major challenge for organizations as they seek to justify the use of emerging, GenAI-based solutions and ensure that they adhere to traditional security norms, as well as new requirements for data governance, privacy, and visibility.
- Infrastructure modernization to support GenAI at scale. Running cloud native applications at enterprise scale requires an infrastructure that can support the necessary requirements including security, data integrity and resilience. Emerging GenAI applications are no exception to this rule. Almost all respondents (98%) face challenges when it comes to scaling GenAI workloads from development to production. In fact, the #1 challenge organizations face when scaling GenAI workloads from development into production is integration with existing IT infrastructure. As a result, IT Infrastructure was chosen as the #1 area of investment needed to support GenAI.
- GenAI solution adoption requires changes to technology and people. 52% of respondents say their organization needs to invest in IT training to support GenAI. Similarly, 48% of respondents believe their organization needs to hire new IT talent to support GenAI. There is no denying organizations face acute skills shortages and competition for GenAI-related talent. The good news? Many teams will embrace the challenge to adopt AI-related competencies and skills organically, as part of normal work. This year’s survey shows that 53% of respondents believe advancements in GenAI will provide them with an opportunity to become an AI expert.
