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Manila Times Business

AI's Hidden Problem Isn't Chips. It's Electricity.

Legendary Economist explains the power required to keep scaling AI may be the constraint that finally breaks the boom Baltimore, MD, Aug. 02, 2026 (GLOBE NEWSWIRE) -- The AI boom is usually framed as a race for faster chips and bigger models. Jim Rickards says the real limit is far more physical, and far harder to engineer around: raw electrical power. In a new presentation, the former advisor to the CIA and the Pentagon argues that the energy required to keep AI growing may be the wall the enti

Context & Analysis

Electricity is the quiet bottleneck behind the AI race because model training and inference are continuous, compute-intensive workloads that turn data centers into large power consumers. For Philippine readers, this reframes AI from a purely software or chip story into an infrastructure issue with local consequences. Cloud platforms, banks, retailers, logistics firms, and business process service providers will increasingly measure AI adoption not just by model quality but by the reliability and cost of the energy behind it.

The Philippines already faces familiar strain on its power system: uneven grid capacity, generation exposed to typhoons and seasonal weather, and a push to add cleaner sources while keeping electricity affordable. If data centers expand here, they may compete with commercial and industrial users for firm power during peak periods unless new transmission, storage, or renewable projects keep pace. That matters because AI-dependent operations—customer service automation, credit scoring, inventory forecasting, real-time analytics—can become less attractive if latency spikes, outages interrupt services, or cloud pricing rises to reflect energy costs.

At the same time, the constraint creates opportunities. Companies that pair AI with energy management can use predictive models to cut waste, optimize equipment, and smooth peak demand. Developers of data centers may look toward renewable power purchase agreements, co-location near efficient grid nodes, or storage-backed facilities. Regulators such as the Energy Regulatory Commission and Department of Energy will likely weigh how to classify large digital infrastructure: whether it receives priority treatment, transparent tariffs, or incentives tied to local employment and clean energy use.

What to watch next is not just which AI models dominate, but where power comes from. Look for signals in corporate disclosures about cloud spend, data-center localization plans, and energy procurement. Also monitor policy moves on transmission investment, renewable interconnection, and data-center regulation. For Philippine businesses, the practical takeaway is simple: AI strategy now includes an energy strategy.

Analysis by IJE Software — original commentary on the story above.

This is an excerpt. Read the full article at the original source:

Source: manilatimes.net

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