TL;DR: AI Adoption Issues Sound Familiar to Agile Practitioners
If you have spent the last twenty years arguing that velocity is not value, that adoption is not impact, that an Agile transformation is not a Jira migration, the Stanford AI Index 2026 will read like déjà vu: The technology is new. The failure mode, the AI spending trap, is not.
The many organizations that have adopted AI but cannot show an EBIT impact are the same organizations that adopted Scrum without learning empiricism, adopted DevOps without changing how they fund teams, and adopted product management without giving anyone product authority.
The economic data is the evidence. The interpretation is what you, the agile practitioner, already know.
Without a decision system, every task you delegate to AI is a gamble on your credibility and your place in your organization’s product model. AI4Agile’s A3 Framework addresses this with three categories: what to delegate, what to supervise, and what to keep human.
The Agile Manifesto followed Luther’s Reformation arc: radical simplicity hardened into scaling frameworks, transformation programs, and debates about what counts as “real Agile.” Learn to recognize when you’re inside the orthodoxy and how to practice the principles without the apparatus.
by Stefan Wolpers|FeaturedAgile and ScrumAgile Transition
TL; DR: Why the Brand Failed While the Ideas Won
Your LinkedIn feed is full of it: Agile is dead. They’re right. And, at the same time, they’re entirely wrong.
The word is dead. The brand is almost toxic in many circles; check the usual subreddits. But the principles? They’re spreading faster than ever. They just dropped the name that became synonymous with consultants, certifications, transformation failures, and the enforcement of rituals.
You all know organizations that loudly rejected “Agile” and now quietly practice its core ideas more effectively than any companies running certified transformation programs. The brand failed. The ideas won.
What if your organization’s “Agility” dysfunction isn’t an implementation problem but a missing-conditions problem that switching to, say, a product operating model cannot solve? This article identifies the success factors for agility that are absent in your organization. It gives you concrete Monday-morning actions to test what’s actually possible within your sphere of influence to drive change, because agility matters.
Organizations seem to fail their AI transformation using the same patterns that killed their Agile transformations: Performing demos instead of solving problems, buying tools before identifying needs, celebrating pilots that can’t scale, and measuring activity instead of outcomes.
These aren’t technology failures; they are organizational patterns of performing change instead of actually changing. Your advantage isn’t AI expertise; it’s pattern recognition from surviving Agile. Use it to spot theater, demand real problems before tools, insist on integration from day one, and measure actual value delivered.
