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  "documentTitle": "2025 The new rules of Platform Strategy in the age of agentic AI",
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      "text": "Task classification\n\nWe evaluated 332 intermediate-level tasks representing the activities of the workforce, applying both machine learning and human coding.\n\nEach task was examined across four criteria:\n\n+ Language-intensive: natural, mathematical or computational language tasks relevant to LLMs.\n\n+ Interpersonal interaction: real-time human-to-human exchange, physical or virtual.\n\n+ Proactive vs. routine: whether tasks require solving unstructured problems versus following defined rules.\n\n+ Human sign-off: whether tasks require compliance or oversight driven by law, ethics or social conventions.",
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      "text": "Work activities mapping\n\nTo assign tasks more precisely, we used O*NET Online’s taxonomy of 30+ work activities (for example, communicating with others, thinking creatively, performing physical activities).\n\nCategory grouping\n\n+ Platform tasks: language- or process-intensive and routine, without human sign-off.\n\n+ Agentic tasks: language-intensive, proactive or interpersonal, but not requiring human sign-off.\n\n+ Human-only tasks: physical, sign-off-driven or requiring high-stakes judgment.",
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      "text": "Aggregation\n\nWe used U.S. Bureau of Labor Statistics data on occupational employment and hours worked to weight task frequencies. We then estimated what proportion of work time can be handled by platforms, agents or humans, all of which we aggregated to enterprise functions.",
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