> ## Documentation Index
> Fetch the complete documentation index at: https://www.scrums.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# AI for Delivery Optimisation

> How Scrums.com uses AI to improve efficiency, predictability, and engineering outcomes.

## Overview

AI in SEOP is applied at the points in the delivery cycle where it creates the most value — removing bottlenecks, improving quality, and giving engineering leaders better information faster.

## Where AI Creates Value

**Sprint Planning**
AI analyses historical velocity and backlog complexity to recommend realistic sprint commitments. This reduces over-commitment and improves sprint completion rates over time.

**QA Automation**
AI QA Agents run automated test suites on every code push, reducing the manual testing burden and catching defects earlier in the cycle. Average reduction in manual QA effort: 60–80%.

**Code Quality**
Automated code review surfaces issues before they reach peer review — reducing review cycle time and ensuring consistent standards across distributed teams.

**Risk Prediction**
Delivery Analytics Agents monitor sprint health and flag risks proactively — giving engineering managers time to intervene before a delay becomes a failure.

**Reporting**
AI-generated delivery reports summarise sprint performance, quality trends, and team metrics automatically, reducing the admin overhead on engineering managers and enabling faster stakeholder communication.