Empowering Data

Empowering the data and AI-ready enterprise

The artificial intelligence (AI) revolution is here, and there’s no turning back. Leading enterprises are harnessing the evolution of AI to build new products, digital experiences, and automations to bolster operational efficiencies. AI requires the right data-first strategy, but data is both the challenge and the opportunity to fuel AI innovation. Against this backdrop, Digital Realty commissioned the second edition of the Global Data Insights Survey.

The IT landscape faces infrastructure complexities as new technologies disrupt business as usual. With data as the engine for innovation, all respondents ranked unlocking data insights as their top priority and finding the right data infrastructure solutions as their number one challenge.

Key findings

executing a formal data strategy to guide IT infrastructure investments

prioritize sufficient investments in data systems, infrastructure, and analytics

analyze and draw insights from data

localize workloads closer to data and users for successful AI strategies

It’s not just strategy, real work is in play. Preparing data and actively training AI models as part of a business strategy are key, as are monetizing and actively deploying trained AI models.

AI is nearly universally considered the key to unlocking new business value. However, reaching that goal is not possible without reimagining infrastructure, so data and users are adjacent to storage and processing. This enables organizations to capitalize on Data Gravity for positive business outcomes.

Data’s exponential growth changes where data is processed, stored, and located, underscoring the need for a future-poised data capacity strategy. Data Gravity results in data increasingly being distributed across multiple locations, including on-premises sites and in the cloud. The distributed footprint makes it difficult to manage, govern, and secure data effectively, raising potential compliance challenges and business risks.

A formal data location strategy is essential to mitigating these challenges. This requires investment in infrastructure, data storage, and interconnection technology – all to support localizing workloads closer to data.

are channeling investments for analyzing and drawing insights from data

Data Gravity refers to the idea that data has mass. As that mass grows, it becomes increasingly difficult to move or replicate. Data Gravity is the attractive force caused by enterprise data creation and exchange, drawing from applications, servers, and other sources. As a data set grows, it attracts applications and services, creating a virtuous cycle of more data creation.

Data-first strategies advance AI innovation

Data is pervasive and growing

Data drives the business agenda

Data localization matters more than ever

79%

53%

37%

52%

$100M – $1B+

2,254

questions

respondents

countries

industries

company size by revenue

About the research

Understand how IT leaders are evolving their data strategies

Present insights into how IT leaders can capitalize on the business value of data and AI

Provide a window into AI-mature practices that give enterprises a leg up in this fast-changing landscape

Objectives

Data growth attracts applications and services

Figure 1: Patented Data Gravity formula, McCrory & Bishop, Digital Realty

Data-first strategies

Data Gravity: A growing challenge and opportunity

The bottom line

Data is pervasive

and growing

Data localization

matters more than ever

Data drives

the business agenda

have a formal data strategy that is actively executed

have monetized and actively use trained AI models

will make significant new AI investments

18%

56%

“You must convert data from an afterthought to the forefront of the infrastructure discussion.”

Tony Bishop Senior Vice President, Enterprise Platform & Solutions, Digital Realty

plan to stay the course on budgets

24%

The bottom line

52%

65% and 56%

45%

say the lack of sufficient investment in infrastructure is the main challenge in drawing insights from data

respectively, have solved for data storage and interconnection issues

focus on specialized infrastructure needed to support AI workloads

see localizing workloads closer to data and users as a key tenet of successful AI strategies

New points of data generation, including the surge of AI activity combined with ongoing security and compliance requirements, have intensified data creation and processing at distributed locations. “If you don’t have the right data where you need it, then your AI strategy is broken before it starts,” says Dan Eline, vice president, Platform Solutions at Digital Realty. “Data must be in the right place where AI can ingest it and create more data in a forever perpetuating cycle.”

With data as the fuel that powers AI models and AI-enabled insights, it’s critical that the right data be readily available in a steady state for AI processing closest to where it resides.

The bottom line

said they are adding one to five additional points of presence in the next two years

tie data location strategy to AI road maps

enlist between 11 and 20 data centers

Localizing infrastructure is expected to increase substantially within the next two years:

Enterprises are growing their IT footprint:

67%

45%

57%

30%

73%

Everywhere you look, data and AI are at the epicenter of business. Businesses that effectively execute data and AI strategies are well positioned to achieve better business outcomes. Investment in AI/ML is the most critical element for achieving data-driven insights, according to 43% of the survey respondents. Enterprises are taking a multifaceted approach to infuse AI into workloads and operations to create strategic advantage. Across the board, companies have high hopes for AI when it’s aligned with business strategy to improve innovation, customer-centricity, and operational excellence. “There’s long been a desire to monetize data and align data with business, but there hasn’t been a clear and obvious path to do that until AI,” says Dan Eline, vice president, Platform Solutions, Digital Realty. “AI creates the alignment that previously didn’t exist, while unlocking budget and justifying movement.”

As companies navigate the AI journey, there is a need for core building blocks to ensure sustained success. Among them: data-ready IT architectures that are well suited to the needs of the data economy, informed data strategies that align with core business goals, and formal data management and governance frameworks to get data in shape for AI-enabled operations.

The bottom line

enlist data center providers that emphasize global coverage, capacity, and direct connectivity across major metro areas on a single data center platform.

41%

43%

said investing in AI and machine language (ML) is key to achieving data-driven insights from data

67%

of respondents will use AI insights to improve customer experiences and create new products or services

advance AI innovation

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