Engineering Leaders Must Prove AI Impact on Outcomes
CFOs are demanding evidence that AI spending translates into measurable business results, not just activity metrics. While AI can speed up individual coding tasks, those gains often do not scale to system‑level productivity. Leaders are urged to redirect the time saved by AI into quality improvement, technical debt reduction, and high‑friction initiatives such as legacy migrations and security remediation. Leveraging engineering intelligence platforms provides the data needed to link AI usage with throughput, quality, and customer‑visible outcomes, enabling executives to answer hard budget questions with numbers instead of anecdotes.