Introduction
The AI landscape in 2026 has evolved significantly from where it stood just two years ago. Industry observers who predicted consolidation have been proven right in some areas, while entirely new categories have emerged that nobody saw coming.
Key Findings
Our analysis across multiple dimensions reveals patterns that contradict much of the conventional wisdom shared at conferences and in vendor marketing materials. The reality on the ground often diverges sharply from the narrative.
What This Means for Practitioners
Those building and deploying AI systems today face a different set of challenges than their counterparts did in 2024. The tooling has matured, but the complexity of integration and the expectations placed on these systems have grown proportionally.
