Overview
- Skill Key
- 1kalin/afrexai-ai-spend-audit
- Author
- 1kalin
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/1kalin/afrexai-ai-spend-audit
- Latest Commit SHA
- 3a6ee8c500cc6f125c205c8fa08b40f34c1adf05
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 Afrexai Ai Spend Audit 技能。 若已安装,则直接安装 Afrexai Ai Spend Audit 技能。
# AI Spend Audit Audit your company's AI spending — find waste, measure ROI, and right-size your tool stack. ## When to Use - Quarterly AI budget reviews - Before renewing AI tool subscriptions - When AI spend exceeds 3% of revenue without clear ROI - Evaluating build vs buy decisions for AI capabilities ## The Framework ### Step 1: Inventory Every AI Line Item Map all AI spending across these categories: | Category | Examples | Typical Waste | |----------|----------|---------------| | **Foundation Models** | OpenAI, Anthropic, Google API keys | 40-60% (unused capacity, wrong model tier) | | **SaaS with AI** | Salesforce Einstein, HubSpot AI, Notion AI | 30-50% (features enabled but unused) | | **Custom Development** | Internal ML teams, fine-tuning, RAG pipelines | 25-45% (duplicate efforts, over-engineering) | | **Infrastructure** | GPU instances, vector DBs, embedding compute | 35-55% (over-provisioned, always-on dev instances) | | **Data & Training** | Labeling services, training data, synthetic data | 20-40% (one-time costs recurring unnecessarily) | ### Step 2: Score Each Tool (0-100) **Usage Score (0-30)** - 0: Nobody uses it - 10: <25% of licensed users active - 20: 25-75% active - 30: >75% active, daily use **ROI Score (0-40)** - 0: No measurable business impact - 10: Saves time but no revenue/cost link - 20: Measurable cost reduction (<2x spend) - 30: Clear ROI (2-5x spend) - 40: High ROI (>5x spend) **Replaceability Score (0-30)** - 0: Commodity (10+ alternatives at lower cost) - 10: Some alternatives exist - 20: Few alternatives, moderate switching cost - 30: Irreplaceable, deep integration **Action Thresholds:** - Score 0-30: **CUT** — cancel immediately - Score 31-50: **REVIEW** — renegotiate or find alternative - Score 51-70: **OPTIMIZE** — right-size tier/usage - Score 71-100: **KEEP** — monitor quarterly ### Step 3: Model Cost Optimization For every API-based AI tool, check: 1. **Model Selection**: Are you using GPT-4 where GPT-3.5 suff...
# AI Spend Audit Score every AI tool in your stack (0-100), identify waste, right-size model tiers, and consolidate vendors. Includes 2026 benchmarks by company size, 90-day action plan template, and red flag checklist. 52% of companies now run AI as a core business strategy. Most of them are overspending by 25-50%. ## What's Inside - 5-category spend inventory framework - Scoring system (Usage + ROI + Replaceability) - Model cost optimization checklist (caching, batching, tier downgrades) - Vendor consolidation mapping - Company size benchmarks ($2K-$1M+/month) - Industry-specific adjustments for 6 verticals - Board-ready audit report template ## Quick Start Install this skill, then ask your agent: "Run an AI spend audit on our current tool stack" ## Links - [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — Find your biggest automation ROI - [Context Packs](https://afrexai-cto.github.io/context-packs/) — Industry-specific AI operations packs ($47) - [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — Configure your AI agent stack in minutes
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