AI for Real-World Productivity

Analyze how artificial intelligence creates value in practical, resource-constrained environments such as agriculture, education, and public services. Use examples like crop optimization, process monitoring, and decision support to explain why some AI projects deliver measurable gains while others stall. Then identify the data, talent, governance, and cost conditions needed for AI adoption to produce durable productivity improvements rather than isolated pilots.