
A 5,000-person rollout put training, executive support and employee champions behind a startling adoption figure. The harder question is what happened after people started using it.
Across 15,000 monthly database tickets, Pythian says AI agents prepare the first runbook before an engineer steps in. Its reported gains reveal a workflow built around people, training and continuous upkeep.

Slab and Helpjuice can both receive your documentation, but they reduce disruption in different ways. The safer choice depends on who will rebuild structure, permissions and habits after the files arrive.
Alignment theatre is the term Hanadi Usman, a PMO director with more than 15 years in enterprise transformation, uses for the gap between what teams say in the steering committee and what they admit in the corridor afterward. The dashboards are green, the sponsors nod, the minutes record consensus, and the program bleeds quietly for six more weeks. Her argument: the fix is not a better reporting framework but psychological safety built into governance design, so surfacing the real picture is safer than protecting the performed one.

Sushanth Raman, founder and CEO of San Francisco-based supply chain AI company Pallet, delivers a conference keynote tackling the central paradox of the enterprise AI boom: despite a projected $2.5 trillion in AI spending in 2026, an MIT study finds 95% of enterprise AI pilots fail. Raman argues the failures stem not from weak frontier models but from messy real-world deployments, uncaptured tribal knowledge, legacy integrations, and poor change management. He offers a three-part framework for evaluating AI vendors, explains why building in-house is harder than it looks, and presents three case studies (Lineage, Prism Logistics, and Mallory Alexander) where Pallet drove millions in savings and 99%+ accuracy on tasks like customs filing.