Skill: 1kalin/afrexai-ai-readiness (version 1.0.0)

# AI Readiness Assessment Run a structured AI readiness audit for any organization. Scores 8 dimensions, identifies gaps, produces a prioritized 90-day action plan with budget ranges. ## When to Use - Before investing in AI/automation tools - Board or leadership requesting AI strategy - Evaluating build vs buy decisions - Annual technology planning ## How It Works Score each dimension 1-5 (1=not started, 5=optimized): ### 1. Data Infrastructure (Weight: 3x) - [ ] Centralized data warehouse or lakehouse operational - [ ] Data quality monitoring automated (freshness, completeness, accuracy) - [ ] API-first architecture for core systems - [ ] Data governance policy documented and enforced - [ ] PII/PHI classification and access controls active **Score 1:** Spreadsheets and siloed databases **Score 3:** Warehouse exists, some pipelines automated **Score 5:** Real-time streaming, quality >99%, full lineage ### 2. Process Documentation (Weight: 2x) - [ ] Top 20 revenue-impacting processes mapped end-to-end - [ ] Decision trees documented for each process - [ ] Exception handling paths defined - [ ] Time-per-task benchmarks established - [ ] Process owners assigned **Score 1:** Tribal knowledge, nothing written down **Score 3:** Major processes documented, some outdated **Score 5:** Living documentation, updated quarterly, covers 80%+ of operations ### 3. Technical Talent (Weight: 2x) - [ ] At least 1 person understands ML/AI concepts at implementation level - [ ] Engineering team comfortable with APIs and integrations - [ ] DevOps/infrastructure person can deploy and monitor services - [ ] Data analyst can query and interpret model outputs - [ ] Security team understands AI-specific attack surfaces **Score 1:** No technical staff beyond basic IT **Score 3:** Good engineering team, AI knowledge is theoretical **Score 5:** Dedicated AI/ML engineer, cross-functional AI literacy program ### 4. Budget & ROI Framework (Weight: 2x) - [ ] AI budget allocated (not pulled from "innovation" slush fund) - [ ] ROI measurement criteria defined before project starts - [ ] Kill criteria established (when to stop a failing project) - [ ] Total cost of ownership model includes maintenance, retraining, monitoring - [ ] Benchmarks set against current manual process costs **Budget Reality by Company Size:** | Company Size | Year 1 Investment | Expected ROI Timeline | |---|---|---| | 15-50 employees | $24K-$80K | 4-8 months | | 50-200 employees | $80K-$300K | 3-6 months | | 200-1000 employees | $300K-$1.2M | 6-12 months | | 1000+ employees | $1.2M-$5M+ | 8-18 months | ### 5. Change Management (Weight: 1.5x) - [ ] Executive sponsor identified and actively involved - [ ] Communication plan for affected teams drafted - [ ] Training budget allocated - [ ] Pilot team identified (volunteers, not voluntolds) - [ ] Success metrics shared openly with organization **Score 1:** Leadership says "just do AI" with no plan **Score 3:** Exec sponsor exists, some team buy-in **Score 5:** Change management playbook active, regular town halls, feedback loops ### 6. Security & Compliance (Weight: 2.5x) - [ ] AI-specific data handling policy written - [ ] Vendor security assessment process includes AI criteria - [ ] Model output logging and audit trail planned - [ ] Regulatory requirements mapped (GDPR, HIPAA, SOX, SOC 2, EU AI Act) - [ ] Incident response plan covers AI failures **Score 1:** No AI-specific security considerations **Score 3:** General security strong, AI gaps identified **Score 5:** AI governance framework active, regular audits, compliance automated ### 7. Integration Readiness (Weight: 1.5x) - [ ] Core systems have APIs (CRM, ERP, HRIS, etc.) - [ ] Authentication/authorization supports service accounts - [ ] Webhook or event-driven architecture available - [ ] Test/staging environment mirrors production - [ ] Rollback procedures documented **Score 1:** Legacy systems, no APIs, manual data entry **Score 3:** Major systems have APIs, some manual bridges **Score 5:** API-first architecture, event-driven, CI/CD for integrations ### 8. Strategic Alignment (Weight: 1x) - [ ] AI initiatives map to specific business objectives (not "innovation") - [ ] 3-year technology roadmap includes AI milestones - [ ] Competitive landscape analysis includes AI adoption by rivals - [ ] Board/leadership educated on AI capabilities and limitations - [ ] Failure tolerance defined (acceptable experiment failure rate) **Score 1:** AI is a buzzword, no concrete strategy **Score 3:** Strategy exists, loosely connected to business goals **Score 5:** AI embedded in strategic plan, quarterly reviews, competitive moat building ## Scoring **Weighted Total = Sum of (Score × Weight) / Max Possible × 100** | Range | Rating | Recommendation | |---|---|---| | 0-25 | 🔴 Not Ready | Fix foundations first. 6-12 months of groundwork before AI projects. | | 26-50 | 🟡 Early Stage | Pick ONE high-impact, low-risk pilot. Build muscle. | | 51-75 | 🟢 Ready | Deploy 2-3 agents in validated use cases. Scale what works. | | 76-100 | 🔵 Advanced | Multi-agent deployment, autonomous operations, competitive moat. | ## 90-Day Action Plan Template **Days 1-30: Foundation** - Complete this assessment with honest scores - Document top 5 processes by time spent × error rate - Audit data infrastructure gaps - Set budget and kill criteria **Days 31-60: Pilot** - Select highest-scoring use case (high data readiness + clear ROI) - Deploy single agent or automation - Measure daily: time saved, error rate, cost - Weekly review with stakeholders **Days 61-90: Scale or Kill** - If pilot ROI > 2x: plan 2 more deployments - If pilot ROI < 1x: diagnose root cause, pivot or kill - Document learnings regardless of outcome - Update 3-year roadmap based on reality ## 7 Assessment Mistakes 1. **Scoring yourself too high** — External validation beats internal optimism 2. **Ignoring data quality** — AI on bad data = faster wrong answers 3. **Skipping change management** — Technical success + team rejection = failure 4. **No kill criteria** — Zombie projects drain budget and credibility 5. **Buying before understanding** — Tool purchases before process documentation = shelfware 6. **Ignoring security until audit** — Retrofitting AI security costs 3-5x more than building it in 7. **Comparing to tech companies** — Your readiness bar is YOUR industry, not Silicon Valley ## Industry Benchmarks (2026) | Industry | Avg Score | Top Quartile | First AI Win | |---|---|---|---| | Fintech | 62 | 78+ | Fraud detection, KYC | | Healthcare | 41 | 58+ | Clinical documentation, scheduling | | Legal | 38 | 52+ | Contract review, research | | Construction | 29 | 44+ | Safety monitoring, estimation | | Ecommerce | 58 | 74+ | Personalization, inventory | | SaaS | 65 | 82+ | Support, onboarding, churn prediction | | Real Estate | 35 | 48+ | Lead scoring, valuation | | Recruitment | 45 | 62+ | Screening, outreach | | Manufacturing | 42 | 56+ | QC, predictive maintenance | | Professional Services | 48 | 64+ | Proposal generation, time tracking | --- **Get your industry-specific context pack ($47) →** https://afrexai-cto.github.io/context-packs/ **Calculate your AI revenue leak →** https://afrexai-cto.github.io/ai-revenue-calculator/ **Set up your first AI agent →** https://afrexai-cto.github.io/agent-setup/ **Bundles:** Pick 3 for $97 | All 10 for $197 | Everything Pack $247

path: README.md
content: # AI Readiness Assessment

Score your organization across 8 weighted dimensions. Get a clear readiness rating and a prioritized 90-day action plan — not a vague "you need AI" pitch.

## What It Does

- **8-dimension scoring** — Data, Process, Talent, Budget, Change Management, Security, Integration, Strategy
- **Weighted formula** — Security and data count more than buzzword alignment
- **Budget reality tables** — By company size, with actual ROI timelines
- **90-day action plan** — Foundation → Pilot → Scale or Kill
- **Industry benchmarks** — Know where you stand vs your sector (2026 data)
- **7 assessment mistakes** — Skip the expensive lessons others already learned

## Who It's For

CTOs, VPs of Engineering, COOs, and anyone who got asked "what's our AI strategy?" in a board meeting.

Works for 15-person startups through 1000+ enterprises.

## Quick Start

Tell your agent: "Run the AI readiness assessment for our company"

It'll walk through each dimension, score you, and produce the action plan.

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**Industry context packs ($47):** https://afrexai-cto.github.io/context-packs/

**AI Revenue Calculator (free):** https://afrexai-cto.github.io/ai-revenue-calculator/

**Agent Setup Wizard (free):** https://afrexai-cto.github.io/agent-setup/

Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI agent context for businesses that ship.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)