Building Your First AI Team: A Founders Guide

# Building Your First AI Team: A Founder's Guide

The biggest mistake founders make? Trying to build AI teams like traditional tech teams.

## Why Traditional Hiring Fails for AI

AI teams require a unique blend of skills:
- Technical expertise in ML/AI
- Business acumen to drive ROI
- Change management skills

## The Lean AI Team Structure

### Phase 1: The AI Champion (Month 1-3)
**1 person**: AI-focused product manager or technical lead
- **Responsibilities**: Strategy, vendor evaluation, pilot projects
- **Budget**: $120K-180K annually

### Phase 2: The Core Team (Month 4-8)
**3 people**: Champion + AI Engineer + Data Analyst
- **AI Engineer**: Builds and implements solutions
- **Data Analyst**: Ensures data quality and insights
- **Total Budget**: $350K-450K annually

### Phase 3: The Scale Team (Month 9+)
**5+ people**: Add specialists based on your focus areas

## Hiring Strategy

### What to Look For
- **AI Engineer**: Python, ML frameworks, cloud platforms
- **Data Skills**: SQL, data pipelines, analytics
- **Business Sense**: Can translate AI capabilities to business value

### Where to Find Talent
1. **Bootcamp graduates** (often overlooked, high ROI)
2. **Career switchers** from traditional software
3. **Consultants** ready to go in-house

## Budget Planning

- **Year 1**: $200K-400K (lean team)
- **Year 2**: $500K-800K (core team)
- **Year 3**: $1M+ (scale team)

## Common Mistakes to Avoid

- Hiring PhDs for business problems
- Over-engineering initial solutions
- Neglecting change management

Your first AI hire should solve business problems, not win research awards.