Everything on AI Strategy & Readiness

Context engineering is the critical differentiator for AI success. 65% of organizations lack dependable data quality, and AI performance depends on granular context about policies, libraries, and standards.

Impact: Without high-quality data and context injection, AI will produce hallucinated or inefficient code. Investing in data hygiene and context pipelines is a prerequisite for scalable AI adoption.

— from 2026 Engineering Benchmark: AI Adoption vs. Impact Gap · Dev Interrupted· Mar 24, 2026