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AI adoption across GCCs is clearly moving from experimentation to execution. Our latest AIM Research survey of šŸ­šŸ¬šŸ¬+ š—šš—–š—– š—¹š—²š—®š—±š—²š—æš˜€ shows that more than half of GCCs have already integrated AI into operational workflows. But the bigger story is not just adoption. It is the gap between ambition and readiness. š—žš—²š˜† š˜€š—¶š—“š—»š—®š—¹š˜€ š—³š—æš—¼š—ŗ š˜š—µš—² š˜€š˜‚š—æš˜ƒš—²š˜†: šŸ±šŸ²% of GCCs have AI in production šŸÆšŸ¬% have a strong AI data foundation šŸ²šŸ­% formally measure AI value šŸ²šŸµ% have formal or advanced AI skilling initiatives šŸ²šŸ²% have leadership representation at the global table or executive level š—§š—µš—² š—ŗš—¼š˜€š˜ š—¶š—ŗš—½š—¼š—æš˜š—®š—»š˜ š˜š—®š—øš—²š—®š˜„š—®š˜†: GCCs are no longer just delivery engines. They are increasingly becoming strategic capability hubs, owning products, platforms, AI initiatives, and transformation priorities. However, the data also highlights a clear challenge. While AI adoption is accelerating, data readiness, governance, measurement discipline, and decision rights still need to catch up. š—™š—¼š—æ š—šš—–š—– š—¹š—²š—®š—±š—²š—æš˜€, š˜š—µš—² š—»š—²š˜…š˜ š—½š—µš—®š˜€š—² š—¼š—³ š—”š—œ š—ŗš—®š˜š˜‚š—æš—¶š˜š˜† š˜„š—¶š—¹š—¹ š—±š—²š—½š—²š—»š—± š—¼š—» š˜š—µš—æš—²š—² š—½š—æš—¶š—¼š—æš—¶š˜š—¶š—²š˜€: 1.Building AI-ready data foundations 2.Moving from isolated AI wins to scaled enterprise impact 3.Strengthening governance, talent, and strategic autonomy The GCCs that solve these gaps will be better positioned to move from AI-enabled operations to AI-native value creation. #GCC #AI #ArtificialIntelligence #AIMResearch #GlobalCapabilityCenters #DigitalTransformation #Leadership #AIAdoption #DataReadiness

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