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AI Consulting Proposal Template

Every company wants AI in 2026 but few know what they actually need. Your job as consultant is to clarify the use case, kill bad ideas, and ship something measurable. The proposal must educate without being preachy.

What to include in your ai consulting proposal template

  • Use case discovery and prioritization
  • Build vs buy vs fine-tune analysis
  • Model selection (OpenAI vs Anthropic vs open source)
  • Cost projections (token usage, infrastructure)
  • Data security and compliance review
  • Prompt engineering and evaluation framework
  • Integration scope (existing tools, APIs)
  • Ongoing monitoring and prompt iteration

How to price it

AI consulting: $5K-$25K (initial assessment + roadmap), $25K-$150K (proof of concept + measurement), $150K+ (production deployment). Hourly: $300-$800/hr. Avoid hourly for novices — they don't understand the value.

Common mistakes to avoid

  • Promising 'AI will do X' without measuring baseline
  • Including ongoing token costs in your fee (variable, unbounded)
  • Skipping the eval framework (you can't iterate without it)
  • Vague success criteria — clients claim AI 'didn't work'
  • Not addressing data privacy upfront (legal blocker)

Sample template content

Here's an example of what a complete proposal looks like for this niche. Use it as a starting point — you'll fill in your own details when you create one.

Scope of Work

Customer support AI assistant for [Client]: Phase 1 — Discovery (week 1): • Audit existing support tickets (volume, top 10 categories) • Define success metrics (deflection rate, CSAT impact) • Data security and PII handling review Phase 2 — PoC (weeks 2-4): • RAG setup over knowledge base • Prompt design and few-shot examples • Integration with help desk (Zendesk/Intercom) • Eval suite (50 representative tickets) • Deflection rate baseline measurement Phase 3 — Iteration (weeks 5-7): • A/B test prompt variations • Improve weak categories • Stakeholder review and approval Phase 4 — Production (weeks 8-9): • Production deployment with kill switch • Monitoring dashboard • Team training • 30-day post-launch hypercare

Sample Line Items

DescriptionQtyTotal
Phase 1 — Discovery1$7,000.00
Phase 2 — PoC build1$18,000.00
Phase 3 — Iteration1$12,000.00
Phase 4 — Production launch1$9,000.00
Total$46,000.00

Sample timeline: 9 weeks

Terms & Conditions

Engagement fee: 30% on signing, 30% at PoC end, 25% at production launch, 15% at end of hypercare. LLM API costs (OpenAI/Anthropic) billed direct to client. We do not pay these. We target 30%+ deflection rate. If not achieved by end of iteration phase, additional weeks at $250/hr or scope adjusted with credit. Client retains all prompts, evals, and code. Consultant retains right to use methodology in future engagements.

Frequently asked questions

ā–ø Should I include API token costs in my fee?

No. Token costs are variable and can spike. Pass through to client at cost. Set up your own consultancy account for development and bill separately.

ā–ø Build, buy, or fine-tune?

Buy (existing tools) for 70% of use cases. RAG over existing models for 25%. Fine-tuning for the last 5% where you have unique data + scale to justify.

ā–ø How do I handle hallucinations?

Eval framework + RAG + temperature controls + 'I don't know' fallbacks. Build evals BEFORE prompting. Set acceptable error rate explicitly with client.

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