Balancing AI cost efficiency with data sovereignty

AI cost efficiency and data sovereignty are at odds, forcing a rethink of enterprise risk frameworks for global organisations.

For over a year, the generative AI narrative focused on a race for capability, often measuring success by parameter counts and flawed benchmark scores. Boardroom conversations, however, are undergoing a necessary correction.

While the allure of low-cost, high-performance models offers a tempting path to rapid innovation, the hidden liabilities associated with data residency and state influence are forcing a reassessment of vendor selection. China-based AI laboratory DeepSeek recently became a focal point for this industry-wide debate.

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