AI and data sovereignty in Postgres: An answer to the datacenter energy crisis
A billion AI agents walk into a power grid
By The Register
As AI systems become more powerful, the pressure is shifting from software alone to the data centres, databases and energy infrastructure needed to run them.
The growth of artificial intelligence is putting new pressure on the data centres, power grids and database systems that sit behind modern technology.
A partner article published by The Register, contributed by EDB, argues that businesses will need to think more carefully about where their data sits, how AI workloads are managed and how much energy those systems consume.
The piece focuses on PostgreSQL, data sovereignty and the rising energy demands linked to AI systems. Its central argument is that companies may be able to reduce waste by keeping more control over their data layer, rather than relying entirely on large cloud platforms.
For readers in Cheshire, the wider issue is not only technical. AI tools are increasingly being used by businesses, councils, schools, public services and media organisations. Behind every chatbot, automated system or AI search tool is infrastructure that requires electricity, cooling and storage.
That matters because data centre expansion is becoming a bigger part of the debate around energy use, planning and long-term infrastructure.
The Register article says the global build-out of data centres has become harder to ignore, with local communities in different parts of the world weighing the economic benefits of new facilities against concerns about power demand, infrastructure pressure and local disruption.
The same debate is now relevant in the UK, where AI growth has raised questions about whether the country has enough energy capacity and grid infrastructure to support the next wave of digital services.
Businesses are also facing a more practical question: how can they use AI without creating unnecessary cost, complexity or energy demand?
One answer being promoted by EDB is greater control over the data layer. In simple terms, that means businesses knowing where their data is stored, how it is processed and which systems are responsible for running AI tasks.
The article argues that PostgreSQL-based systems can play a role because many organisations already use Postgres as part of their data infrastructure.
It also points to data sovereignty, which means keeping control over data across cloud platforms, private systems and on-premises infrastructure.
That can be important for organisations dealing with sensitive information, regulated sectors or public services where data location and governance matter.
However, readers should note that the article is partner content and reflects the view of EDB, a company with a commercial interest in Postgres-based data platforms.
The broader issue is still important. As AI becomes more common, the cost of running it will not only be measured in software subscriptions. It will also be measured in electricity use, cooling requirements, cloud bills and infrastructure planning.
For smaller businesses, the practical lesson is to avoid adopting AI tools without understanding the systems behind them.
That means asking where data is stored, whether information is being used to train external systems, what the ongoing cost will be, and whether the tool genuinely improves productivity.
AI may become part of everyday business life, but the infrastructure behind it is becoming one of the biggest questions in technology.