Topic
Artificial Intelligence (AI) & Machine Learning (ML)
AI and ML are no longer just buzzwords or hypotheticals; they are now practical tools shaping the way modern products are built and experienced. At their core, these technologies are about enabling systems to learn from data and make decisions with minimal human intervention. For product managers, this means knowing when to leverage AI/ML to solve real problems, deliver more personalised experiences, and unlock smarter automation. A solid grasp of the fundamentals helps you work effectively with technical teams, identify impactful use cases, and ensure these solutions support your product strategy.
Product managers' role in making AI/ML systems more relevant
Shubhojeet Sarkar
How to actually prove AI agent ROI
Lisa Murkin
The Hidden UX of AI - How to build trustworthy AI products: Nina Olding at INDUSTRY 2025
Louron Pratt
AI fired the org chart — everyone is product now
James Effarah
Why enterprise AI pilots fail and how product leaders can finally scale them
Enterprise AI succeeds only when it fits workflows and earns trust. Explore the reasons pilots fail and how PMs can turn prototypes into scalable, high-ROI products.
Raman Rai
Product management for Agentic AI: When to build agents and how to do it well
Shruti Tiwari
The biggest misconceptions about AI adoption in product management: Nacho Bassino
Louron Pratt
Get future-ready with your product practice and deliver results
Mike Belsito
Before you add AI, consider these three fundamentals
In the following article, Amanda Holtstrom, of Millicent March, examines the rationale that should be considered by product leaders before disrupting existing product roadmaps to incorporate AI technologies into existing products and portfolios.
Amanda Holtstrom
Avoiding bias and building better hiring tools with AI
Iryna Havryliuk
From first click to Aha: How AI is rewriting user onboarding - Nichole Mace at INDUSTRY 2025 (Pendo)
Louron Pratt
Your AI problems might actually be team problems
Albert Lie