Senator Alex Antic (Liberal-SA) said that Australia's push to become an artificial intelligence data centre hub could significantly increase electricity costs.
The warning highlights a potential conflict between national technological ambitions and the stability of consumer utility prices. Because AI-driven data centres require immense amounts of energy and water to operate, they may place unsustainable pressure on existing national infrastructure.
Antic said the issue is not receiving sufficient scrutiny from policymakers. He specifically noted the impact on resources, stating, "I don’t think it’s getting enough attention. They use a lot of power, so what are they going to do to our power prices, and they use a lot of water…" [1].
This concern over infrastructure strain is supported by broader projections regarding the cost of energy. One study suggests that electricity bills could rise as much as 57% by 2030 due to the expansion of data centres [2].
Data centres utilize high-density computing clusters that generate extreme heat, requiring constant cooling systems. These systems often rely on large volumes of water, and consistent, high-voltage electricity. In regions like South Australia, where the energy grid is undergoing significant transitions, the addition of industrial-scale AI hubs could create volatility in the wholesale electricity market.
Critics of the current approach said that without a comprehensive plan to integrate new power generation, the growth of the AI sector may come at the expense of the average household's monthly budget. The tension remains between the economic promise of AI investment and the practical limits of the current power grid.
“"I don’t think it’s getting enough attention."”
The intersection of AI growth and energy policy creates a critical bottleneck for Australia. If the government prioritizes data centre investment without simultaneous upgrades to energy production and water management, the resulting surge in demand could lead to higher utility costs for residents and potential instability in the power grid.





