AI consulting engagements for a $20M company range from $5,000 to $200,000.
The range is not arbitrary. It reflects a specific spectrum: from a strategy session that produces a document to a fully embedded engagement that produces a running AI-native operation.
Most $5M–$25M non-tech companies should be spending between $30,000 and $80,000 to reach stable Phase 2 AI adoption, depending on company size and engagement structure.
This article gives a specific breakdown of the AI consulting market by engagement type, the deliverable each type produces, and the realistic cost range for a $10M–$25M non-tech company.
It also includes the calculation that tells you whether the investment is justified based on what it produces.
The four AI consulting engagement types: what each costs and what each produces
Engagement Type 1: Strategy assessment and roadmap
What it is: a 4–8 week engagement that assesses the company’s current AI maturity, identifies the highest-value AI opportunities, and produces a strategy document and roadmap.
What it produces: a document. Specifically, an AI maturity assessment, an AI strategy recommendation, a prioritised roadmap of AI initiatives, and a presentation to the leadership team.
What it does not produce: a context pack, trained team members, documented workflows, a running AI system, or a named AI system owner.
Typical cost range for a $10M–$25M company: $8,000–$25,000.
When it is the right engagement: the company has strong internal AI capability and needs strategic direction. The primary gap is “what should we do?” rather than “how do we build it?”
When it is not the right engagement: when the company needs a running AI system, not a plan for one.
When the internal capability to execute the plan does not exist — which describes most $5M–$25M non-tech companies — a strategy document is not a foundation. It is a to-do list with no one to do it.
Engagement Type 2: Phase 1 AI Foundations build
What it is: a 3–5 week engagement that builds the AI Foundations the company lacks, context pack, voice guide, decision rules, workflow documentation, and loaded shared workspace.
What it produces: a functioning foundation. Specifically:
- A complete context pack loaded into the shared workspace
- Workflow specification documents for three to five core workflows
- A shared workspace configured and tested
- A training session for the founder and ops lead on how to use and maintain the foundation
What it does not produce: a trained team (that is Phase 2), automated workflows (Phase 3), or ongoing maintenance (requires the AI system owner the company names).
Typical cost range: $15,000–$40,000.
When it is the right engagement: when the company has team members who are AI-fluent enough to self-train on the documented workflows, or when the company wants to complete Phase 1 independently before deciding whether to engage for Phase 2.
Engagement Type 3: Phase 1 + Phase 2 embedded engagement
What it is: an 8–14 week engagement that builds the foundations (Phase 1) and trains every AI-using team member on their role-specific workflows (Phase 2).
This is the most complete single-engagement investment for a company moving from ad hoc AI use to consistent team adoption.
What it produces: a running AI system with a trained team. Specifically:
- Complete AI Foundations, context pack, voice guide, decision rules, workflow library
- Every AI-using team member trained on their role-specific workflows using real current work
- Adoption tracking installed and running
- A named AI system owner trained on the maintenance cadence
- Blended acceptance rate above 75% across the trained workflows by engagement end
Typical cost range for a $10M–$25M company: $30,000–$80,000.
When it is the right engagement: when the company needs the full Phase 1 and Phase 2 foundation and does not have the internal AI capability to build it independently. This is the correct first engagement for most $5M–$25M non-tech companies.
Engagement Type 4: Multi-phase embedded engagement (Phase 1 through Phase 4)
What it is: an ongoing embedded engagement, typically structured as a retainer after an initial project phase, that covers Phase 1 foundations through Phase 4 connected agent operations.
What it produces: the complete path to AI-native operations over 12–18 months.
Typical cost range: an initial Phase 1+2 engagement ($30,000–$80,000) followed by a monthly retainer of $8,000–$15,000 for Phase 3 and Phase 4 work. Total investment over 18 months: $80,000–$200,000.
When it is the right engagement: when the company is committed to reaching AI-native operations and wants a sustained embedded partner for the full journey.
Quick comparison
| Engagement type | Duration | Cost range | Primary deliverable |
|---|---|---|---|
| Strategy assessment | 4–8 weeks | $8,000–$25,000 | Strategy document + roadmap |
| Phase 1 Foundations | 3–5 weeks | $15,000–$40,000 | Context pack + workflow docs + loaded workspace |
| Phase 1 + Phase 2 | 8–14 weeks | $30,000–$80,000 | Running AI system + trained team |
| Multi-phase embedded | 12–18 months | $80,000–$200,000 | AI-native operations |
What drives the price within each engagement type
Factor 1: Company complexity
Larger teams with more distinct role types require more Phase 2 training sessions. A 10-person company with two distinct AI-using role types requires two role-specific training sets. A 25-person company with six distinct role types requires six.
Effect on cost: each additional distinct role type typically adds $1,500–$3,000 to a Phase 1+2 engagement.
Factor 2: Context pack complexity
Companies with more distinct client archetypes, more complex competitive positioning, or more diverse service lines require more context pack depth.
A company with two clearly defined archetypes and a narrow service line produces a context pack in 4–5 hours. A company with five archetypes and multiple service lines requires 8–10 hours.
Effect on cost: a more complex context pack adds $2,000–$5,000 to the Phase 1 engagement.
Factor 3: Tool integration complexity
Phase 3 automation workflows that connect to standard tools (HubSpot, QuickBooks, Asana) use native integrations and take 2–4 hours each. Connections to customised or legacy systems, a proprietary ERP, a heavily customised CRM, may take 8–20 hours each.
Effect on cost: non-standard integrations add $3,000–$8,000 per complex integration.
Factor 4: Project vs retainer model
Project engagements (Phase 1 and Phase 2) are priced at a fixed fee because the scope is defined.
Retainer engagements (Phase 3 and Phase 4 work) are priced at a monthly rate because the scope evolves as the company’s AI system develops.
Retainer rates for embedded AI partners at the $10M–$25M level typically run $8,000–$15,000/month.
The ROI calculation: how to know if the investment is justified
The ROI calculation for an AI consulting engagement has three inputs: the time recovery estimate, the team time value, and the engagement cost. The breakeven tells the founder how long the engagement must produce value before the investment is recovered.
Step 1: Estimate weekly hours recovered
For each workflow the engagement will build:
(runs per week) × (minutes per manual run) × 60% reduction ÷ 60 = hours recovered per week
Example for a Phase 1+2 engagement targeting five core workflows:
| Workflow | Runs/week | Manual time | Hours recovered/week |
|---|---|---|---|
| Proposal draft | 3 | 90 min | 2.7 hrs |
| Client status update | 8 | 30 min | 2.4 hrs |
| Pipeline summary | 1 | 60 min | 0.6 hrs |
| Meeting action items | 10 | 20 min | 2.0 hrs |
| Invoice exception summary | 5 | 25 min | 1.25 hrs |
| Total | 9 hrs/week |
Step 2: Calculate the weekly value of recovered time
Weekly hours recovered × team time value ($75/hour for mid-market professional or operational roles):
9 hours × $75 = $675/week
Step 3: Calculate the breakeven
Engagement cost ÷ weekly value of recovered time = weeks to breakeven.
$45,000 engagement cost ÷ $675/week = 67 weeks to breakeven
At $100/hour time value: 45 weeks.
The breakeven targets
| Breakeven | Signal |
|---|---|
| Under 26 weeks (6 months) | Strong investment |
| 26–52 weeks (6–12 months) | Justified investment |
| 52–78 weeks (12–18 months) | Borderline — review workflow selection |
| Over 78 weeks | Scope or workflow selection problem |
Most well-scoped Phase 1+2 engagements break even in 8–18 months, depending on team size and workflow volume.
An engagement that cannot be expressed as a breakeven timeline is not an investment — it is an expense.
What the ROI calculation does not capture
Three effects that are real but harder to quantify:
- The compounding improvement loop raises recovery over time, month 12 output quality is higher than month 1, which means time savings grow
- Client output quality improvements may produce revenue effects that exceed the time recovery value
- Competitive positioning effects, the AI-adopting company gaining capacity and proposal quality that wins business the non-adopting company loses
The pricing red flags: what to watch for in an AI consulting engagement proposal
Red flag 1: Phase 1+2 pricing for a strategy assessment deliverable
The engagement is priced at $40,000–$80,000 but the proposed deliverables are a maturity assessment, a strategy document, and a roadmap presentation.
The test: ask for a list of specific documents and running systems that will exist at the end of the engagement. If the list is primarily documents rather than a running context pack and a trained team, the pricing does not reflect what is being delivered.
Red flag 2: Tool vendor fees embedded in consulting fees
Some consulting firms mark up tool subscriptions or receive referral fees from the tools they recommend. Claude Teams, Make, and Zapier have fixed retail prices.
A consulting firm that prices these as part of the engagement fee is adding margin to commodity software purchases.
The test: ask whether the engagement fee includes software subscription costs or whether those are purchased directly by the company. A transparent firm directs the company to purchase software directly.
Red flag 3: No specific acceptance rate or adoption metric in the engagement scope
An engagement that describes success in vague terms, “the team will be more productive with AI,” “you will have a strong AI foundation”, rather than specific metrics is not committing to measurable outcomes.
The test: ask “what specific metrics will we measure at the end of the engagement to assess whether it succeeded?” A firm that cannot answer with specific numbers — acceptance rate above 75% on deployed workflows, adoption tracking showing consistent usage for four weeks — is not scoped around operational outcomes.
Red flag 4: No handover condition in the engagement scope
An engagement that specifies an end date but not an end state can technically complete without the AI system being operational.
The test: ask “what condition does the AI system have to be in before this engagement concludes?” A firm that describes a specific system state is scoped around operational delivery. A firm that describes a date and a deliverable list is not.
Common questions on AI consulting costs
”What is included in a typical AI consulting engagement fee?”
For a Phase 1+2 embedded engagement, the fee covers: the structured founder interview and context pack build, voice guide and decision rules documentation, and workflow specification documents for three to five core workflows.
It also covers: shared workspace configuration and loading, role-specific training sessions for every AI-using team member, adoption tracking setup, and AI system owner training and handover.
What is not included: the tool subscriptions (Claude Teams, Make, Zapier), the company purchases these directly at retail prices.
”Should I pay a flat fee or a retainer?”
Flat fee for Phase 1 and Phase 2, the scope is defined and the deliverables are specific.
Retainer for Phase 3 and Phase 4, the scope evolves as the AI system develops and the work cannot be fully specified in advance.
The risk with flat-fee-for-everything: a Phase 3 or Phase 4 engagement sold at a flat fee often has an implicit scope limit that means the work stops before the system reaches the intended operating state.
”How does AI consulting pricing compare to traditional management consulting?”
Traditional management consulting at the same company size runs $15,000–$50,000 per week at top-tier firms. AI consulting at the embedded engagement level runs $30,000–$80,000 for an 8–14 week engagement, roughly $4,000–$8,000 per week.
The important difference: traditional management consulting produces strategy. Embedded AI consulting produces a running operational system. The deliverable types are different, which makes the price comparison somewhat misleading.
”What if my company is smaller than $10M: does pricing change significantly?”
For a $3M–$8M company, Phase 1+2 pricing typically runs $20,000–$45,000, lower because the team is smaller (fewer training sessions), the context pack is simpler (fewer client archetypes, narrower service lines), and the workflow library is shorter.
The breakeven arithmetic is roughly the same because the team’s workflow volume is also proportionally lower.
Want a specific scope and cost estimate for your company: based on your team size, your target workflows, and where you are starting from?
AI consulting for a $20M company costs $30,000–$80,000 for the Phase 1 and Phase 2 engagement that produces a trained team and a running AI system. The investment breaks even in 8–18 months.
The red flags, advisory deliverables at embedded prices, embedded tool costs, vague success metrics, and no handover condition, are specific and detectable before commitment.
The company that understands what each engagement type produces will not overpay for a document or underpay for a system that never gets built.
Path one: run the ROI calculation on your candidate workflows today. Use the table format above. If the breakeven is under 52 weeks at a $75/hour time value, the Phase 1+2 engagement is a justified investment.
Path two: get a specific estimate. Phos AI Labs scoping conversations produce a specific Phase 1+2 scope, a workflow inventory, a timeline estimate, and a cost range based on the company’s actual situation, not a generic pricing page. We have run 400+ AI engagements. Clients include Zapier, Coca-Cola, Medtronic, Dataiku, and American Express. Thirty minutes, no deck. Start here.