A 2026 Productside survey of more than 250 product professionals found that roughly four in five product managers use AI regularly, but only about one in four have a clear strategy behind that use. According to the article, AI strategy for a PM is a business judgment skill built on model judgment, data readiness, metrics, and risk management, not a coding skill, and PMs without this skill risk losing decision-making influence to engineering and data teams as AI-dependent features grow. Many PMs were never formally trained in machine learning, and AI systems behave differently from traditional software: outputs can be probabilistic, performance can vary across inputs, and results depend heavily on data quality. For a product manager, AI strategy means deciding where AI creates measurable value, what data and model capabilities a feature needs, what risks need control, and how success gets measured. Companies invest in AI expecting a measurable return, whether through cost reduction, faster workflows, or new revenue, and unit economics matter because AI features carry inference, infrastructure, a