bambu-studio-ai
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AI Spend Audit
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install 1kalin/afrexai-ai-spend-auditInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Audit your company's AI spending — find waste, measure ROI, and right-size your tool stack.
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) |
Usage Score (0-30)
ROI Score (0-40)
Replaceability Score (0-30)
Action Thresholds:
For every API-based AI tool, check:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
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%.
Install this skill, then ask your agent: "Run an AI spend audit on our current tool stack"
# 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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