Why Most AI Adoption Stalls
Most AI adoption does not fail because the models are inaccessible. It stalls because organizations stop at access and never design an operating model around use.
Research & Analysis
Analytical reports, operational frameworks, and research notes from WBA's independent practice.
AI Consumption Is an Operations Problem, Not Just a Prompting Problem
Prompting matters, but once AI touches real business work the larger challenge is operational: permissions, review, cost, logging, and repeatability.
From Epistemic Debt to Epistemic Instrumentation: MCP as a Business Pattern
Organizations often keep sounding confident long after they stop knowing. MCP — implemented with safety tiers, structured errors, and audit-grade logging — can be a practical step toward epistemic instrumentation.