RA LAB · KAZAKHSTAN & CENTRAL ASIA · RU / EN
AI pilot: test the value before you scale.
We choose one workflow where AI could make a difference. We compare it with the current approach, account for quality, time and costs, and decide whether the solution is worth developing.
Discuss your challenge →- Your challenge
- Your team spends time on manual work. You need to understand where AI can help.
- What we will do
- We will compare one AI use case with the current workflow on quality, time and costs.
- What you will get
- Test results and a recommendation to continue, change or stop.
When a pilot fits your business
A pilot fits when there is a workflow, an owner and examples available for testing. We start with one use case: a customer reply, follow-up offer, product selection, partner support or work on payments.
If the challenge is unclear, we start with Point A analysis.
What you will have
Pilot brief: the problem, users, workflow boundaries, owner and intended outcome.
Test plan: a baseline, test tasks, quality criteria, effort and human review rules.
Conclusion: observations, errors and limitations, with a decision on the next experiment. Sales growth or savings are not guaranteed: the pilot tests a hypothesis.
Data, access and boundaries
An initial discussion needs only a workflow description, without customer databases, passwords or trade secrets. Use anonymised or synthetic examples where possible.
Before using working data, agree on its scope, lawful basis, storage, access, deletion and permitted AI providers. A WhatsApp message does not itself authorise using company data in AI.
Stages and timing
1. Challenge. We clarify the workflow, owner and usefulness criterion.
2. Test design. We agree the data, baseline, use case and quality controls.
3. Limited test. We compare AI-assisted work with the current approach and record observations and errors.
4. Decision. We review the results and choose the next step. We agree timing, price and scope after defining the pilot boundaries.
How we decide to continue or stop
Before the test, we agree what will count as a useful result and which errors are unacceptable. Afterwards, we compare quality, speed, human review effort and risks. If evidence is insufficient, we state the uncertainty and define a further test.
Example working artifact
Use case: AI drafts a reply to an inbound request; a team member reviews and sends it.
The brief records: request type, permitted sources, prohibited promises, completeness criteria, preparation time and corrections. This illustrates a pilot structure; it is not a reported client result.
Before we start
What do we need to start?
One workflow, its owner, available examples and a baseline metric, such as time to prepare a reply. Agree on boundaries and data handling first.
What is the difference between 21 and 90 days?
Around 21 days is a planning guide for a bounded use-case test. Around 90 days is a guide for a business pilot that includes workflow implementation and an economic assessment. These are different scopes; exact timing depends on the problem and data.
How do we measure value?
We compare with the current workflow on quality, time, cost and human effort. We choose a business metric before the test. Revenue growth cannot be attributed to AI without an appropriate comparison.
Which industry problems can we test?
In retail, test bundle selection and product-recommendation accuracy. In B2B, test reply drafting from approved materials. In services and travel, check itinerary or proposal completeness. These are illustrative hypotheses, not claims of a ready product or achieved impact.
Approach and practical materials
About Marina Rakhimzhanova → · GRI and GRI AI in plain language →
Let’s discuss your problem
Describe the workflow you want to improve and what is difficult today. A general description without sensitive data is enough. A draft opens in WhatsApp; you choose whether to send it.
Discuss your challenge →