BREAKING LIVE All breaking →
News

A2A raises investment plan to $27 billion amid data centre demand

by UCapital MediaUCapital News newsroom1 min read
A2A raises investment plan to $27 billion amid data centre demand

Italian multi-utility company A2A, which operates in energy and waste management, announced it has raised its total projected investments for 2024–2035 to €23 billion ($27 billion), with €1.6 billion earmarked for developing and managing data centres.


The updated business plan increases projected investments by €1 billion and slightly adjusts financial targets for the latter part of the strategy period. A2A also confirmed a minimum annual dividend growth of 4%. Shares fell 7% amid cautious financial forecasts, while Milan’s blue-chip index (.FTMIB) rose.


CEO Renato Mazzoncini said A2A aims to become both a power supplier and a data centre developer. In the most optimistic scenario, electricity demand for Italian data centres could rise to 42 TWh by 2035 from 3 TWh this year. The company is also considering European expansion but has no plans to acquire a stake in rival Edison.

A2AInvestmentsItaly
DISCLOSURE

UCapital Asset Management LLP or group companies may have commercial relationships with the companies mentioned. This content is not financial advice.

✦ Ask the AI about this article

Sign up for free to ask the AI about this article.

The macro picture, read by the AI agents

Growth, inflation and rates across the major economies, with the impact on your business.

Start the macro analysis →

AI use policy. UCapital AI supports the newsroom with news analysis, summaries, market reactions, translations and the generation of cards and charts. AI-generated or AI-assisted content is labelled in the byline (AI Desk, a named AI profile marked «AI», or joint byline) and is reviewed by editors before publication. News received via API feeds from third-party providers is attributed to the original source. AI can make mistakes: report any inaccuracies to the newsroom. Users’ personal data is not used to train the models.