Day: September 2, 2026

Career path transition from traditional PM to AI product manager
Career Development

AI PM Transition: A Guide for Traditional Product Managers

The rapid rise of artificial intelligence is fundamentally shifting the Product Management landscape, but traditional PMs don’t need to become software engineers to stay relevant. Instead, transitioning to an AI Product Manager requires a cognitive shift from deterministic to probabilistic thinking. This article explores the growing market demand for AI skills, highlights three critical blind spots PMs must avoid (determinism bias, metric myopia, and ethics), and provides a practical three-stage roadmap.

AI Didn't Take Their Jobs. It Blew Up Their Job Descriptions
Enterprise Transformation

AI Workflow Redesign: Why Enterprise AI is an Identity Crisis

While millions of organizations are rushing to deploy AI tools, most are falling into the “deployment trap”—layering new technology over outdated workflows. This article argues that successful AI integration is not a technology upgrade, but a fundamental organizational reinvention. By exploring the real reasons companies resist restructuring and highlighting three proven patterns of AI workflow redesign (flattening, role bifurcation, and internal deployment), this piece provides a strategic blueprint for leaders.

Your Team Is More Productive Than Ever. So Why Aren't AI ROI Moving?
AI & Business Strategy

AI ROI: 4 Management Choices to Turn Productivity Into Profit

Despite massive enterprise investments, many firms report no financial impact from AI. The problem isn’t a technology failure; it’s a management failure. While AI creates productivity, profit remains a deliberate decision. This article explores the modern “Solow Paradox” and outlines four concrete management choices—from redesigning workflows to demanding P&L ownership—that separate companies converting AI productivity into durable profit from those stuck with flat margins and vanity metrics.