The almost limitless potential of AI continues to create vast opportunities for unleashing new value for almost every organization. Nearly half (44%) of respondents to recent research from Enterprise Strategy Group, now part of Omdia, said AI, data science and machine learning have become significantly more important to their organization’s future over the past two years. Additionally, 29% of respondents said that supporting generative AI initiatives would be one of the most important initiatives to justify IT investments in 2025.¹

Yet, deploying AI at scale also presents unprecedented challenges to IT organizations charged with building an infrastructure that is capable of fully taking advantage of AI. New technology initiatives such as AI are already viewed as compounding an already-complex IT environment, with almost half of respondents (47%) reporting that they are experiencing a problematic shortage of AI and machine learning skills.²

Moreover, many organizations are finding plenty of devils in the details of running AI at scale. While a great deal of the focus around AI was necessarily concentrated on the compute environment, this is now expanding to incorporate the broader data environment.

Data is increasingly viewed as the lifeblood of any AI initiative—the one aspect that can make the difference between success and failure. Getting the data aspect right at scale presents numerous substantial challenges across the broader data environment. A recent Enterprise Strategy Group research study found that data management and/or data quality issues were the second most frequently cited challenge associated with implanting AI, behind overall cost issues (see Figure 1).³ Concerns over data privacy, protecting IP, and security were also frequently cited, along with integration issues and the need to modernize infrastructure.

Many organizations on their AI journeys are, therefore, concluding that modernizing the infrastructure—right down to the storage environment—may be a necessary step to fully take advantage of AI.

Figure 1. Top Challenges With Implementing AI

Source: Enterprise Strategy Group, now part of Omdia

^1. Source: Enterprise Strategy Group Research Report, 2025 Technology Spending Intentions Survey, December 2024.

^2. Ibid.

^3. Source: Enterprise Strategy Group Research Report, Navigating Build-versus-buy Dynamics for Enterprise-ready AI, January 2025.