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Building Your AI Team.

You don't need to hire a data science army. You need the right people in the right structure with the right budget. This lab gives you the blueprint.

After this lab you'll know

  • Which AI roles actually matter and what to pay for them
  • When to upskill internally vs. hire externally
  • Three proven team structures for AI initiatives
  • How to build a realistic AI budget from scratch

You're not competing with Google for talent. You don't need to.

The AI talent war narrative is overblown for most organizations. Yes, top ML researchers command $500K+ salaries and go to frontier labs. But implementing AI in your business doesn't require frontier research. It requires people who understand your business problems and know how to apply existing AI tools to solve them.

That's a fundamentally different hiring profile. And it's one you can actually compete for.

Six AI roles, ranked by when you need them.

1. AI Champion (Hire first)

$120-180K | Internal promotion or external hire

A senior leader who owns the AI strategy. Not necessarily technical. Must understand business operations, change management, and vendor evaluation. Often your best ops or strategy person with AI curiosity.

2. AI/ML Engineer

$150-250K | External hire

Builds and maintains AI integrations. Connects APIs, fine-tunes models, builds data pipelines. You need this role when you move from buying AI tools to building custom AI workflows.

3. Data Engineer

$130-200K | External hire

Gets your data AI-ready. Cleans, structures, and pipelines data from across your organization. Without this role, your AI tools starve. Garbage in, garbage out remains the #1 AI failure mode.

4. Prompt Engineer / AI Analyst

$80-140K | Internal upskill or external hire

Designs and optimizes AI prompts, workflows, and use cases for business teams. This is often your most tech-savvy analyst or operations person who learns prompt engineering and AI tool configuration.

5. AI Ethics / Governance Lead

$130-180K | External hire (often fractional)

Ensures AI use complies with regulations, company values, and risk tolerance. Critical in healthcare, finance, and any regulated industry. Can start as a fractional or consulting role.

6. Change Management Lead

$110-160K | Internal promotion

Manages the human side of AI adoption. Training, communication, resistance management. Frequently overlooked. The organizations that skip this role have 3x higher AI project failure rates.

The minimum viable AI team: An AI Champion + a Prompt Engineer + a fractional Data Engineer. Total cost: $250-350K/year. This gets you started with SaaS AI tools, basic custom workflows, and clean data. Scale from there based on results.
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