AI for Companies Doing $10M to $50M
This is the segment the market serves worst: too large for off-the-shelf tools, too small for a Big Four engagement.
The gap in the market
A company doing $10M to $50M has real operational complexity and real budget, but not the scale to justify an enterprise consulting engagement. The large firms price in the hundreds of thousands, which is hard to defend against a mid-single-digit EBITDA margin. The tool vendors sell software, which nobody has time to configure.
So the work stays manual. It gets absorbed by capable people who are already busy, which is exactly why it is invisible on any report. Nobody is recording the hours, because everyone assumes this is simply how the business runs.
Trapped capital is a balance sheet problem, not a technology one
Consider a workflow consuming 20 hours a week. That is 1,040 hours a year. At a fully loaded $35 an hour that is $36,400, and if the work sits with someone whose time is billed or whose attention drives revenue, the real figure is higher. Across four or five workflows it is not unusual to find between $200,000 and $500,000 a year.
That number is capital, and it is trapped. It is not on the balance sheet, it does not appear in the P&L as a line item, and it compounds against you every year it stays manual. Framed that way, the question stops being whether AI is interesting and becomes whether the trapped capital is worth releasing.
Where it hides, by department
| Department | The manual work that persists | The measurable cost |
|---|---|---|
| Sales | Quote preparation and CRM hygiene | Hours per rep per week, multiplied by reps |
| Operations | Order, job or file handoffs between systems | Rework and cycle time, not just labour |
| Finance | Invoice matching, chasing and reconciliation | Days sales outstanding and write-offs |
| Service | Ticket routing and repeat questions | Response time and repeat contact rate |
How to start without a large engagement
Start with the assessment, not the build. The Strategic AI Assessment costs $1,999 and produces a costed ranking of the workflows in the business, each scored on hours consumed, error rate and automation safety. It is deliberately small, because the way to fail at this is to spend six figures before you know which workflow to touch.
The build follows only where the numbers justify it. Most engagements run around $10,000 a month for the integration and infrastructure work, and the recurring maintenance after that is a fraction of it. The assessment exists to make the build self-evident rather than sold.
Frequently Asked Questions
- What does an AI transformation cost for a mid-sized company?
- A readiness assessment is typically quoted between $10,000 and $25,000 by the market, and ongoing fractional AI leadership between $2,500 and $25,000 per month. Practical AI Institute prices the assessment at $1,999 and core integration work at around $10,000 per month, which sits mid-band on the retainer and well below the market on the diagnostic.
- How do I calculate whether AI is worth it for my business?
- Multiply the hours a workflow consumes each week by the fully loaded hourly rate, then by 52 weeks. That gives the annual cost of leaving it manual. Compare that against the price of automating it. Workflows that consume 20 hours a week are commonly worth $26,000 to $78,000 a year depending on whose time it is.
- Why not just hire an AI consultant on a retainer?
- Many retainers sell advice rather than a working system. The useful split is a small fixed-price diagnostic that produces numbers, followed by build work paid for against those numbers. If a proposal cannot show which workflow it will change and what that workflow currently costs, the proposal is a placeholder.
- Is a $10M to $50M company too small for serious AI work?
- It is the opposite. This segment has enough operational complexity for the returns to be large and enough decision speed to implement quickly, which is why it often moves faster than enterprise projects of the same ambition. What it lacks is a supplier willing to sell at its scale, which is the gap Practical AI Institute exists to fill.