In just one year, Generative Artificial Intelligence (genAI) has completely upended the worldview of how technology will influence our lives. Enterprises are racing to understand how genAI, and AI more broadly, can transform their businesses. Some organizations are just beginning to explore AI opportunities, while others are testing specific AI applications and use cases. . A few are further along but not yet ready for full-scale AI adoption.
No matter where organizations are in their journeys, all share common concerns about how best to get started quickly, securely and efficiently while retaining control of their data and models. It was hearing these concerns from customers that inspired Nutanix to release GPT-in-a-boxTM , our full-stack software-defined AI-ready platform with services designed to simplify and jump-start your initiatives from edge to core.
We recently commissioned the Nutanix State of Enterprise AI Report, a global research study of 650 IT, DevOps, and Platform Engineering decision makers, to provide more insights into Enterprise decision-making around AI. The results provide a holistic view into how enterprises are approaching AI technology strategy and adoption, as well as how future plans will affect IT spending and budgeting.
The findings provide a birds-eye view into Enterprise planning with the following key takeaways:
1. Simplify AI with AI-Ready Infrastructure
Enterprises have quickly embraced the idea that AI, including genAI, will be a critical competitive differentiator directly influencing the future of their business, with 90% of respondents expressing that their organization places a high emphasis on prioritizing AI. However, most organizations do not have the IT infrastructure they need to support their goals. 91% of respondents agree their organization’s IT infrastructure needs to be improved to more easily support and scale AI workloads and 84% are planning significant investments in AI-capable infrastructure.
As IT leaders plan for investments in infrastructure to support AI initiatives, it will be essential to do so with a platform that reduces deployment and operational complexity. Nutanix Cloud Platform simplifies the deployment and management of IT infrastructure, allowing infrastructure teams to provide cloud-like operations while meeting the self-service needs of the data science and development teams who will build, tune and leverage AI models.
2. Secure AI with private-cloud fine-tuning
Data is at the core of AI, and having secure, reliable access to data across data center, cloud, and edge environments is essential. In fact, 90% of survey respondents listed security and reliability as important considerations in their AI strategy. These are also the top reasons many IT leaders plan to invest to upgrade their infrastructure. 53% of respondents mentioned data security as a key driver of AI application and infrastructure upgrades, while 52% listed infrastructure resilience and uptime, and 51% noting infrastructure management at scale. Data governance and privacy also become top priorities.
Security and resilience are built into the core of Nutanix Cloud Platform. Our hardened software platform features data-at-rest encryption, network microsegmentation, automated remediation and full suite of enterprise data services. In addition, our self-healing platform with integrated snapshots and replication, protects data from hardware failures to total site outages.
3. Accelerate AI success with pre-trained models
The majority of surveyed organizations indicate they leverage existing, pre-trained AI models for their AI applications. By contrast, only 10% plan to build their own AI models. Why is this? It may in part be due to the prevailing skills gap many enterprises are experiencing when recruiting AI talent. It might also be driven by a need to invest wisely and efficiently in AI. By leveraging existing, pre-trained large language models (LLMs)—which organizations can then adapt to their own needs by fine-tuning with proprietary data—companies can accelerate their AI strategies and avoid the huge investment that comes with training LLMs.
Nutanix GPT-in-a-box was designed to help enterprises move quickly and efficiently in their AI journeys. It offers support for a curated set of LLMs including Llama2, Falcon and MPT. Plus, it features integrated Files and Objects storage so you can fine-tune and run your choice of GPT models. And because it is built on Nutanix Cloud Platform, it features automation, dynamic resource allocation and allows for infrastructure consolidation to reduce costs.
4. Liberate AI models for hybrid Multicloud reach
Data is the lifeblood of AI applications, and with it comes a need to improve the transfer of data between cloud, data center, and edge environments to support AI data initiatives—a priority for more than half of respondents. The expansion of AI technologies, coupled with growing demands for speed and scalability, means edge strategies and core infrastructure deployments are poised to take the center stage of IT modernization. This is why 83% of respondents indicated they plan to increase investment in edge strategy to support their AI initiatives.
Because Nutanix Cloud Platform provides a common platform with a single control plane, it simplifies remote management and movement of AI models and data to the edge and back to the core or cloud. This means you can build, tune and deploy models where you like, preserving privacy and control on your own infrastructure while ensuring operational efficiency.
We’re in a new era where success is defined by maximizing AI’s potential. However, most of today’s infrastructures weren’t designed to handle the unique management and security needs of AI apps, especially as you move your AI workloads across different environments. Our view is clear: To accelerate your AI initiatives, you must maintain control of your data, privacy, and models. Nutanix has built the ideal platform for your AI success, one that allows you to run AI anywhere your business needs it on your infrastructure, from core to edge.
To learn more or read the full report visit Nutanix.com/AI.
© 2023 Nutanix, Inc. All rights reserved. Nutanix, the Nutanix logo and all Nutanix product, feature and service names mentioned herein are registered trademarks or trademarks of Nutanix, Inc. in the United States and other countries. Other brand names mentioned herein are for identification purposes only and may be the trademarks of their respective holder(s). This post may contain links to external websites that are not part of Nutanix.com. Nutanix does not control these sites and disclaims all responsibility for the content or accuracy of any external site. Our decision to link to an external site should not be considered an endorsement of any content on such a site. Certain information contained in this post may relate to or be based on studies, publications, surveys and other data obtained from third-party sources and our own internal estimates and research. While we believe these third-party studies, publications, surveys and other data are reliable as of the date of this post, they have not independently verified, and we make no representation as to the adequacy, fairness, accuracy, or completeness of any information obtained from third-party sources.
This post may contain express and implied forward-looking statements, which are not historical facts and are instead based on our current expectations, estimates and beliefs. The accuracy of such statements involves risks and uncertainties and depends upon future events, including those that may be beyond our control, and actual results may differ materially and adversely from those anticipated or implied by such statements. Any forward-looking statements included herein speak only as of the date hereof and, except as required by law, we assume no obligation to update or otherwise revise any of such forward-looking statements to reflect subsequent events or circumstances