Digital twins have become indispensable tools across industries. Powered by AI, these virtual constructs mirror physical systems in complex manufacturing facilities, supply chains, and operational workflows. By continuously monitoring their physical counterparts and feeding back recommendations, digital twins allow us to predict maintenance needs, optimize production schedules, and prevent disruptions before they occur.

Yet, for all their power, digital twins have largely remained confined to a particular domain: structured, operational decisions with desired outcomes. Could companies also use these digital constructs to tackle unstructured strategic challenges, such as market-entry decisions and long-term planning?

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