Four Steps for Turning Data Clutter into Competitive Power: Your Sovereign AI and Data Blueprint

Remember the rise of the Internet of the 1990s or the mobile revolution of the 2000s? During those earlier waves of digital innovation, data was an emerging resource. The Web was relatively small—by 1998, there were only about 2.4 million websites compared to over 1.5 billion today, and most data was text-based, which meant that companies relied heavily on structured data from internal databases. Even with the first iPhones in 2007, devices had restricted connectivity and the data available for businesses to analyze was fragmented and less sophisticated.

Fast forward to today, and we find ourselves at a new pivotal moment in digital transformation—but now, enterprises are drowning in data. IDC estimates 90% of enterprise data is unstructured, making it a sea of information scattered across outdated systems, different cloud platforms, and global data centers. Without the right tools to harness and structure it, this data glut becomes just as problematic as a shortage.

To stay competitive in today’s dynamic business landscape, enterprises need an effective way to understand their data, leverage it for AI applications, and maintain its sovereignty across borders. This requires comprehensive observability, agile infrastructure, and a paradigm shift in which data is regarded as an intelligent platform for success.

Let’s take a closer look at how this technology empowers enterprises by enabling AI projects and maintaining data sovereignty.

How You Make Sense of Your Digital Sprawl Is Key

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Centralized data management and observability act as the unifier for organizations to extract insights from their data, while keeping their systems running at peak performance. Senior executives responsible for mission-critical workloads reported that full estate observability boosts the ability to integrate AI into these workloads, enhancing value creation by over 20%. Consider Spotify, which analyzes data from 456 million active users to deliver personalized playlists in real-time. Centralized observability allows it to track user behaviors and preferences the moment they happen, turning data chaos into curated experiences.

This visibility and direct oversight of your data supports sovereignty. For example, imagine 10 different currencies inside a wallet, each only valid in its own country. Without a way to exchange this money, it’s not very valuable since each bill can only be used in its respective country. Centralized management and observability are akin to an exchange system in this example. They create a common denominator between the currencies (i.e. data from different locations) so the money can be spent (i.e. the full value of data is realized). This is especially critical for AI workloads, which require a massive amount of data from different sources to operate.

Postgres facilitates this by integrating seamlessly across on-premise and cloud environments, enabling a unified data management layer. With built-in extensions providing real-time performance insights, enterprises can optimize AI workloads continuously. This matters because Gartner reports that poor data quality costs organizations an average of $12.9 million annually, often due to disjointed systems and a lack of visibility.

Enabling Sovereign and Secure Data Anytime, Anywhere

At any given time, consumers have visibility into data that is sovereign to them: their bank account balances, mortgage payments, recent purchases, streaming habits, and more. This data is accessible anytime, anywhere, and it is also secure. Ideally, this same principle would apply to a business’ data too. But oftentimes, this visibility (and therefore any potential valuable insights) isn’t possible due to data being locked away in different clouds, geographies, and locations on-premises.

Postgres addresses this challenge with features like role-based access control, encrypted connections, and built-in auditing, ensuring data remains secure and compliant across environments. Its data replication and synchronization capabilities make cross-border data accessibility possible, allowing companies like Airbnb to navigate data regulations across multiple countries while still providing seamless user experiences.

Making Real-Time Value Creation a Reality

The ability to act on data in real-time isn’t just beneficial—it’s a necessity in today’s fast-paced world. Accenture reports that companies able to leverage real-time data are 2.5 times more likely to outperform competitors. Consider Uber, which adjusts its pricing dynamically based on real-time factors like demand, traffic, and weather conditions. This near-instant capability drives business success by aligning offerings with evolving customer needs.

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Companies stand a lot to gain by giving frontline employees the ability to make informed, real-time decisions. But in order to do so, they need a near-instant understanding of customer data. This means the data needs to flow seamlessly across domains so that real-time models can provide timely information to help workers make impactful decisions.

Postgres supports such complex transactions and near real-time analytics, making it an ideal choice for enterprises that need to deliver instant value. Its extensibility lets businesses integrate AI models directly within the database, enabling personalized experiences at scale.

Support AI As a Core Data Platform Capability

The success of AI initiatives depends on the ability to access, govern, and process at scale. Therefore, the success of an enterprise’s AI initiatives hinges on its ability to access its data anywhere, anytime—while maintaining compliance. These new demands require a governance framework that operates across environments—from on-premise to private and public clouds—while maintaining flexibility and compliance every step of the way. Companies like Netflix, which handles billions of daily data events, rely on sophisticated data architectures to support AI-driven recommendations.

McKinsey notes that AI-driven companies achieve profit margins that are 5 to 10 percentage points higher than industry peers, underscoring the importance of a robust AI-ready data platform.

The Path Forward: Data Sovereignty Meets AI

The world’s most successful companies—Amazon, Meta, Netflix, Tesla—understand that data and AI are inextricably linked. To keep pace, enterprises need to shift from viewing data as a byproduct to treading it as the cornerstone of their AI strategy. A sovereign AI and data platform can unlock this potential, modernizing infrastructure while driving business growth. Postgres is not just a tool in this transformation; it’s the catalyst that makes data work for you.

About the author: Jozef de Vries is Chief Product Engineering Officer at EDB. de Vries leads product development for EDB across the on-premise and cloud portfolios. Prior to joining EDB, he spent nearly 15 years at IBM across a number of roles. Most recently he built and led the IBM Cloud Database development organization via organic growth, mergers, and acquisitions.