Sandra charges $5,000 for an AI assessment and $3,500/month for ongoing setup work. Seven retainer clients. $34,500-39,500/month. She works 30-35 hours a week. No employees, no office. Just deep knowledge of AI tools and the ability to help businesses actually use them.
The Service Model
Phase 1: AI Assessment ($5,000 one-time)
Sandra spends 2-3 days with a client company:
- Audits all business processes for AI automation potential
- Identifies the top 3-5 opportunities ranked by ROI
- Estimates cost savings and setup timeline
- Delivers a detailed roadmap document
That assessment is worth $5,000 because it gives the company an actual plan with dollar figures. Most businesses know they "should use AI" but are completely lost on where to begin.
Phase 2: Setup Retainer ($3,500/month)
After the assessment, Sandra helps set up:
- Selects and configures AI tools (ChatGPT, Claude, Make.com, custom solutions)
- Trains staff on new workflows
- Monitors adoption and optimizes processes
- Reports on ROI monthly
Most clients stay 6-12 months. Some have been with her for 18+ months as new AI capabilities emerge.
The Income Breakdown
| Revenue Source | Monthly |
|---|---|
| 7 retainer clients × $3,500 | $24,500 |
| 1-2 new assessments × $5,000 | $5,000-10,000 |
| Ad-hoc training workshops | $2,000-5,000 |
| Total | $31,500-39,500 |
Annual income: approximately $400,000-475,000. Working 30-35 hours per week. No employees.
How She Became an AI Consultant
Sandra's background: 8 years as a marketing director at a mid-size company. When ChatGPT launched, she became her company's unofficial AI champion — testing tools, creating workflows, training colleagues.
Month 1-2: Left corporate. Offered free AI assessments to 3 businesses she knew personally. All three became paying retainer clients.
Month 3-4: Those 3 clients referred her to 4 more businesses. She raised prices from $2,000/month to $3,500/month.
Month 5-8: Maxed out at 7 clients. Started a waitlist. Added one-time assessment and training workshop revenue streams.
Total time from corporate job to $34K/month: 8 months.
What the Job Actually Looks Like
It is not coding. It is not building AI models. It is translating business problems into AI solutions:
- "Our customer support team is drowning" → Deploy Tidio AI chatbot, train on company FAQ, integrate with CRM
- "We spend 20 hours/week on reporting" → Build Make.com automation that pulls data from multiple sources into auto-generated reports
- "Our salespeople waste time on unqualified leads" → Set up AI lead scoring in HubSpot, create automated outreach sequences
- "We need content but can't afford writers" → Create AI content workflow with brand guidelines, templates, and quality review process
The value is knowing which solution fits which problem. Not the technical setup itself.
Pricing Strategy
Sandra's pricing follows a simple formula: charge 10-20% of the value you create.
If an AI setup saves a company $200,000/year in labor costs, a $42,000 annual retainer ($3,500/month) is a 5:1 ROI for the client. Easy to justify.
The key: do not charge by the hour. Charge by value. A 2-hour assessment that identifies $500,000 in AI opportunities is worth $5,000 — not $300.
Who Can Replicate This
You do not need a tech background. You need:
- Deep knowledge of AI tools — spend 100 hours testing ChatGPT, Claude, Make.com, Zapier, and industry-specific AI tools
- Business process understanding — experience working in or with businesses
- Communication skills — the ability to explain AI value in business terms, not tech jargon
- Sales ability — willingness to do assessments, present findings, and close retainers
The market is massive. 58% of businesses use AI but most do it poorly. 92% plan to increase AI investment. Every company needs someone who can bridge the gap between "we should use AI" and "here is exactly how."
The Rundown
$34K-39K/month. Solo. Seven clients. No coding, no employees, no investors. Sandra's entire business rests on one skill: helping companies turn AI from a buzzword into dollars they can measure. With 75% of companies still in early AI adoption, demand for this is only heading one direction.
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