Nutanix’s State of Enterprise AI Report reveals insights into global AI strategy and adoption. Key findings for EMEA show a strong inclination towards AI with a notable skills-gap in generative AI delaying adoption.
Data security, scale, and management emerge as top challenges. Interestingly, cost ranks low in AI decision-making, with over 90% of respondents expecting an increase in IT costs and cloud spending due to AI applications.
The report underscores a growing demand for data governance and data mobility across different IT environments, pointing towards the need for a platform to manage apps and data across clouds.
- EMEA organisations consider AI a priority, but are hindered by a skills gap in generative AI and prompt engineering.
- Data security, scalability, and management are identified as top challenges for EMEA organisations implementing AI.
- EMEA organisations prioritize infrastructure modernisation and data security over cost when making AI-related decisions.
Why AI is Top Priority for Enterprises
According to a recent study, the strategic importance of Artificial Intelligence (AI) in the enterprise world is no longer up for debate. The Nutanix State of Enterprise AI Report offers an in-depth look into how businesses are approaching AI technology, its adoption, and future impacts on IT expenditure and budgets.
The Impact of Generative AI
Generative Artificial Intelligence (genAI) has, in a short span of time, drastically altered our perception of the role technology plays in our lives. Sammy Zoghlami, SVP EMEA at Nutanix, shared that while businesses are still figuring out how genAI can benefit them, the majority see it as a priority.
“In just one year, Generative Artificial Intelligence (genAI) has completely upended the worldview of how technology will influence our lives and Enterprises are racing to understand how it can benefit their businesses,” said Sammy Zoghlami, SVP EMEA at Nutanix.
EMEA’s AI Adoption and Challenges
Despite the enthusiasm for AI, organisations in the EMEA region are facing challenges. A significant factor slowing down AI adoption is the lack of necessary skills, particularly in genAI and prompt engineering, and a need for more data scientists.
Moreover, the report reveals that more than 90% of EMEA respondents believe that data security, reliability, and disaster recovery are crucial elements of their AI strategy. The top challenge that EMEA organisations are anticipating in the next couple of years is managing and supporting AI workloads at scale.
AI Investment and Infrastructure Modernisation
Interestingly, cost does not seem to be the main concern for EMEA organisations when it comes to running AI workloads. Instead, the focus is on infrastructure modernisation and data security. Despite cost ranking low as a consideration, over 90% of EMEA respondents agree that their IT costs and cloud spending will likely increase due to AI applications.
Final Thoughts
The Nutanix study makes it abundantly clear that AI is a top priority for businesses. Despite the challenges ahead, like the skills gap and the need for improved data security and management, companies are willing to invest. It’s an exciting time as we witness how businesses navigate the implementation of AI and how this translates into enhanced business processes and outcomes.
FAQ
Q: What is the Nutanix State of Enterprise AI Report?
A: The Nutanix State of Enterprise AI Report is a global research study that provides insights into how enterprises are approaching AI technology strategy and adoption, as well as how future plans will affect IT spending and budgeting.
Q: What are the key findings for EMEA organizations?
A: The key findings for EMEA organizations include:
– EMEA organizations prioritize AI, with 90% of respondents considering it a priority for their organization.
– The top two AI solutions deployed by EMEA organizations are virtual assistants/customer support bots and a mix of generative AI solutions.
– EMEA organizations face a skills gap in generative AI and prompt engineering skills, as well as a need for more data scientists and data science skills to support their AI initiatives.
– EMEA organizations consider AI data security, scale, and management as top challenges, with managing AI workloads at scale being the number one challenge.
– Infrastructure modernization and data security are the main considerations for EMEA organizations, with cost ranking as the lowest priority.
Q: What challenges do EMEA organizations face in implementing AI solutions?
A: EMEA organizations face challenges in implementing AI solutions, including a skills gap in generative AI and prompt engineering skills, as well as a need for more data scientists and data science skills. They also have concerns about AI data security, scale, and management, with managing AI workloads at scale being the top challenge.
Q: What are the top considerations for EMEA organizations in their AI strategy?
A: The top considerations for EMEA organizations in their AI strategy are security, reliability, and disaster recovery. They also prioritize managing and supporting AI workloads at scale. Additionally, EMEA organizations recognize the importance of AI data governance and the need to better understand and track data sources, age, and other data qualities.
Q: Is cost a major concern for EMEA organizations in running AI workloads?
A: No, cost is not a major concern for EMEA organizations in running AI workloads. It ranked as the third-lowest consideration for EMEA organizations. However, over 90% of EMEA respondents expect that their IT costs and cloud spending will increase due to AI applications.
Q: What was the methodology used for the Nutanix State of Enterprise AI Report?
A: The report is based on a global research study conducted by Vanson Bourne on behalf of Nutanix. The study surveyed 650 IT, DevOps, and Platform Engineering decision makers between July and September 2023. The respondents spanned multiple industries, business sizes, and regions including the Americas, Europe, Middle East, Africa, and the Asia-Pacific-Japan region.
