
Benchmarking Your AI Maturity: A Guide for Companies of Your Size
TL;DR
- •AI maturity is measured by the number of working automations your employees own, not by investment size.
- •For a company up to 20 people, 3-5 operational automations are sufficient to be considered at a foundational level.
- •Benchmark yourself against companies of similar size and task types, rather than generic success rates.
Many founders sense their competitors are already leveraging AI, while their own teams are unsure where to begin. This often leads to doubts: Do we have enough resources? Are we falling behind? And how can we objectively assess our current stage of AI maturity?
What Constitutes a Foundational AI Maturity Level?
Definition: AI maturity is a state where a company has at least three self-developed, operational automations that execute agreed-upon scenarios using real data and tools. Definition: A benchmark is a set of indicators that allow you to compare your status with typical results of companies of similar size and industry. Definition: A working automation is a tool that processes a task according to predefined logic, using your data and systems, without human intervention.
For a small firm (up to 20 people), the foundational level means having three working automations for priority tasks, which you define yourselves. If you have fewer, you're still in the exploration phase; if more, you're moving into expansion.
How to Measure AI Maturity in Your Company?
Assessment involves a clear plan, broken down into weeks.
Week 1 – Diagnostics
- Book a free 30-minute diagnostic consultation (your first step).
- Complete the "5 Tasks That Consume the Most Working Hours" questionnaire for each key employee.
- Together with leadership, select 3 priority tasks for automation.
Week 2 – Training Kick-off
- Begin the corporate intensive: 4 live sessions, 2 hours each, over 2 weeks (for up to 20 people).
- At the first session, gain access to the recorded video course and technical specification templates.
- Each participant launches their first micro-automation in the browser by the second session.
Weeks 3–4 – Practice and Implementation
- In the final sessions, develop automations for the 3 selected tasks, using AI to generate the code.
- Document the written criteria for "working" (scenario, data, tools) before launch.
- Receive the first month of support for created automations at no extra charge.
By the end of the intensive, you should have at least 3 working automations — this is our guarantee: if not, we refund your money.
Benchmarks by Company Size
| Company Size | AI Maturity Benchmark (working automations) | Tasks Most Frequently Automated First |
|---|---|---|
| 5–10 people | 1–2 | Document templates, simple notifications |
| 10–20 people | 3–5 | Proposal generation, call transcription, meeting analysis |
| 20–50 people | 5–8 | Workload planning, inventory and procurement, project reporting |
| 50+ people | 8+ | Cross-departmental workflows, demand forecasting, CRM/ERP integration |
These figures are not rigid rules, but rather guidelines founders use to understand if their team is moving quickly enough from experimentation to systematic AI utilization.
How to Benchmark Yourself?
Check if you meet the following criteria: ✅ You've identified 3–5 priority tasks that consume the most time. ✅ Key employees are trained to describe logic in words, with AI writing the code. ✅ Each participant has at least one working automation they use daily. ✅ Automations operate on your data and within your tools, without reliance on third-party services. ✅ You have written, agreed-upon criteria for "working" for each automation. ✅ The first month of support is included in the program cost, with no additional payments.
If most points are met, your AI maturity level corresponds to the foundational level for your size. If not, focus on one or two tasks and repeat the cycle.
How this works on our side: The corporate intensive for key personnel includes 4 live sessions, 2 hours each, over 2 weeks, for up to 20 employees from one company. The company chooses 3 priority tasks, and by the end of the program, they have at least 3 working automations — with a money-back guarantee. https://course.aiadvisoryboard.me/corporate?utm_source=blog&utm_medium=article_body&utm_campaign=corporate
FAQ
Do I need to be a programmer to create automations? No. Participants describe the business logic in words, and AI generates the code. Only a clear task definition is needed.
Will company data remain secure after creating automations? Automations are performed on your data and within your tools. We do not require transferring information to third-party servers, and the code and created tools remain your property.
If we have fewer than 20 people, should we still opt for the full group? Yes. The cost is fixed — 99,999 UAH for a group of up to 20 people. With fewer participants, the per-person cost is higher, but you still receive the same: video course, technical specification templates, chat with an instructor, and the first month of support.
Can we expand the number of automations after the intensive? Yes. Even after the course, you can independently create new automations using the skills and templates you've acquired. We do not impose restrictions on quantity or complexity.
How can I be sure that an automation truly "works"? Before starting, you verbally define the scenario, data, and tools that should be involved. After implementation, you verify that the tool obtains the expected result without intervention. This is the criterion fixed in the contract.
Conclusion
Assess AI maturity by real results — the number of working automations, not by expenses or buzzwords. Start with a free diagnostic, choose three priority tasks, and complete the corporate intensive to gain at least three working solutions with a money-back guarantee. Make your first move tomorrow: sign up for a 30-minute diagnostic consultation via the link in our blog.
Frequently Asked Questions

Implements AI agents in companies and teaches founders and their teams to work with them — through courses and corporate programs.
This article was prepared with AI assistance, based on Yaroslav Maxymovych's methodology and materials. Spotted an inaccuracy — let us know via the form below.
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