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executive-cdo skill

/skills/executive-cdo

This skill helps define data strategy, governance, and AI/ML direction to empower data-driven decision making across the organization.

npx playbooks add skill shaul1991/shaul-agents-plugin --skill executive-cdo

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
556 B
---
name: executive-cdo
description: Executive CDO Agent. 데이터 전략, 데이터 거버넌스, AI/ML 전략을 담당합니다.
allowed-tools: Read, Write, Edit, Bash, Grep, Glob, WebSearch
---

# Executive CDO Agent

## 역할
데이터 전략을 수립하고 데이터 기반 의사결정을 리드합니다.

## 담당 업무
- 데이터 전략
- 데이터 거버넌스
- AI/ML 전략
- 데이터 조직

## 트리거 키워드
데이터 전략, 데이터 거버넌스, AI 전략, CDO

## 산출물 위치
- 데이터 전략: `docs/data-strategy/`

Overview

This skill is an Executive CDO Agent that designs data strategy, establishes governance, and aligns AI/ML initiatives with business goals. It acts as a virtual Chief Data Officer to guide organizational data practices, organizational structure, and decision-making. The agent produces actionable artifacts such as strategic roadmaps, governance frameworks, and AI adoption plans.

How this skill works

The agent analyzes existing data maturity, business objectives, and technical capabilities to produce a prioritized data strategy and governance model. It outlines roles, policies, and metrics for data quality, privacy, and compliance while recommending organizational changes to support data-driven decisions. For AI/ML it defines use case prioritization, model lifecycle governance, and deployment pathways that integrate with enterprise systems.

When to use it

  • Preparing a company-wide data strategy or roadmap
  • Establishing or improving data governance and privacy practices
  • Designing AI/ML adoption and operationalization plans
  • Restructuring data teams or defining CDO responsibilities
  • Aligning data initiatives with executive business objectives

Best practices

  • Start with business outcomes: map data initiatives to measurable KPIs
  • Assess current maturity: inventory data assets, tools, and skills before prescribing solutions
  • Define clear roles and accountability for data stewardship and model ownership
  • Prioritize high-impact, low-complexity AI/ML pilots to prove value early
  • Embed governance into workflows: automate lineage, access controls, and quality checks

Example use cases

  • Create a 12-month enterprise data strategy that links to revenue and cost KPIs
  • Design a data governance framework including policies, stewards, and control gates
  • Build an AI adoption roadmap with prioritized pilots, resource plans, and success metrics
  • Recommend a target data org structure and role descriptions for scaling analytics
  • Draft model governance processes for validation, monitoring, and bias mitigation

FAQ

What deliverables does the agent produce?

Typical outputs include a data strategy roadmap, governance framework, role definitions, AI adoption plan, and prioritized use case list.

How does it handle regulatory and privacy requirements?

It incorporates compliance checkpoints into governance, recommends privacy-preserving controls, and maps requirements to policy and technical controls.