Below is a concise, practical cost comparison for AI marketing consulting services (data and ranges checked as of Oct 1, 2025). I show common pricing models, typical price bands by supplier type, major cost drivers, example budgets by company size, and quick selection tips.

Key pricing models

• Hourly: billed for time worked. Good for short tasks or discovery.
• Project / fixed-fee: single price for defined deliverables. Good for scoped implementations.
• Monthly retainer: ongoing advisory/support (fixed hours or deliverables per month).
• Value-based / outcome pricing: fee tied to measured results (revenue share, % of savings, bonuses). Increasingly common for AI work.

Typical price ranges (U.S., 2024–2025 market benchmarks)

• Freelancers / independent consultants: $75–$250+/hour; small fixed projects $2k–$30k. (Freelancer marketplaces commonly show mid-to-high ranges around $40–$150/hr for marketing automation; AI specialists trend higher.) (Upwork.com)
• Boutique AI specialists / small agencies: $150–$450+/hour; project work often $25k–$150k depending on scope. Retainers typically $5k–$25k/month. (Leanware.co)
• Mid‑to‑large digital agencies with AI practices: $200–$500/hr; enterprise projects $50k–$250k+. Monthly retainers commonly $10k–$50k+. (digitalagencynetwork.com)
• Big 4 / strategy firms (enterprise AI strategy & transformation): $350–$500+/hour or multi‑hundred‑thousand dollar engagements for enterprise transformations. (Leanware.co)
• Value-based deals: can vary widely — typical ranges reported are fees equal to 10–40% of incremental gains or structured bonuses; these depend on measurability and attribution capabilities. (Leanware.co)

Major cost drivers (what raises or lowers price)

• Scope complexity: custom model training, LLM fine‑tuning, integration with CRM/analytics, and cross-channel automation increase costs. (digitalagencynetwork.com)
• Data prep and quality: cleaning, labeling, and data pipelines often represent a large one‑time cost ($10k–$90k+ for nontrivial datasets). (digitalagencynetwork.com)
• Team composition: inclusion of data engineers, ML engineers, prompt engineers, and product managers raises rates vs. single strategist. (Leanware.co)
• API / usage costs: token consumption for LLMs, vector DB hosting, and cloud compute add ongoing costs; some consultants pass these through or estimate separately. (digitalagencynetwork.com)
• Industry/regulatory complexity: healthcare, finance, and other regulated industries command premium pricing for compliance and auditability. (AgentiveAIQ.com)

Example budgets by company size (typical engagements)

• Small business / startup (proof-of-concept, marketing AI add-ons): $5k–$30k one‑time; or $2k–$7k/month retainer for light ongoing support. (RecurPost.com)
• Mid‑market (multi-channel automation, personalization, simple model integration): $30k–$150k project or $5k–$20k/month retainer. (Leanware.co)
• Enterprise (end‑to‑end platform integration, custom models, governance): $150k–$1M+ depending on scale, plus monthly operating costs and API/infra spend. Big‑firm strategy retains often $15k–$50k+/month during rollout. (Leanware.co)

How to compare proposals (practical checklist)

• Deliverables & scope: get a clear SOW that lists outputs, milestones, timelines, and acceptance criteria.
• Pricing components: ensure separation of consulting fees, software/API usage, and infrastructure (e.g., token, vector DB, hosting).
• Outcomes & metrics: if considering value‑based pricing, require agreed KPIs, measurement windows, and attribution methods.
• Team and hours: ask who will do the work and a time estimate (not just a headline price).
• Maintenance & ownership: clarify who owns trained models, data, and IP, and who handles ongoing monitoring and drift.
• SLAs & security: include response times, backup/rollover plans, and data protection clauses for PII.
• References & case studies: request examples with measurable results in your industry or similar use cases.

Negotiation levers and cost-saving ideas

• Start with a scoped pilot (4–8 weeks) to validate value before committing to large projects.
• Mix fixed-fee pilots + value-based rollout to align incentives.
• Use prebuilt connectors and low‑code tools where possible to lower engineering effort.
• Push consultants to estimate API/inference costs separately and propose optimizations (caching, smaller models for low‑risk tasks).
• Consider offshore or mixed teams for implementation work while keeping strategy/localization onshore.

Quick recommendation (for most buyers)

• If you need strategy and roadmap only: hire a senior independent consultant or boutique for a short fixed engagement ($10k–$50k).
• If you need implementation and integration at scale: plan for a boutique or agency engagement ($50k–$250k+) or an enterprise program with a larger firm if governance and change management are required.
• Require pilot metrics and cap project phases so you can stop or scale based on measured ROI.

Sources (selected market references and pricing studies used above)

• Upwork marketplace rates and marketing automation consultant ranges (marketplace median hourly data). (Upwork.com)
• Leanware “How Much Does an AI Consultant Cost in 2025?” — consultant tiers, retainers, and value-pricing notes. (Leanware.co)
• Digital Agency Network — AI agency pricing guide: data prep, retainers, API/infra cost drivers, and agency ranges. (digitalagencynetwork.com)
• Freelance/mid‑market rate guides and practical monthly-retainer benchmarks. (RecurPost.com)

If you want, I can:

• Build a one‑page cost-comparison template you can send to 3 potential vendors (line items, assumptions, and scoring).
• Estimate a tailored budget if you tell me your company size, primary AI marketing use case (e.g., generative content, personalization, marketing automation), and whether you need integrations (CRM, data warehouse, CDP).