How to choose an AI partner: ten questions worth asking.

What should you look for in an AI partner?

An AI partner is the company that helps you decide where AI belongs in your business and then designs, builds, connects and supports it. The right one is judged less by the model or the demo it shows you and more by how it works: how it diagnoses, what it commits to in writing, how it keeps people in control, and whether it stays after launch.

Demos are easy to make impressive. A demo usually runs on clean sample data, with no exceptions, no approvals and no older systems to connect. Your business has all three. The ten questions below move the conversation from what AI can do in general to what this partner will do in your company.

The NIST AI Risk Management Framework ↗ (opens in a new tab), a voluntary framework from the US National Institute of Standards and Technology, makes the same point from the risk side. One of its governance outcomes is that policies and procedures are in place to address the AI risks and benefits that come from third-party software, data and other supply chain issues. Choosing a partner is part of that work, not a separate purchasing step.

How to use the ten questions

1. Ask every candidate the same ten questions, ideally in writing, so the answers can be compared side by side.
2. Listen for specifics: named steps, named deliverables and the people who will actually do the work.
3. Notice what is left out. A question that gets a vague answer twice has been answered.
4. Treat a red flag as a reason for a follow-up question, not automatically as a reason to walk away.

Does the partner start from your business or from its product?

The first three questions test whether an AI partner starts from your business. A partner that understands your processes before it proposes anything is far more likely to build something your people will actually use.

Will the system work inside your company, and can you trust it?

Questions four to six test whether an AI partner can build something that works inside your company rather than beside it, with people in control and evidence that it works.

The NIST AI Risk Management Framework organises this work into four functions: Govern, Map, Measure and Manage. One of its measurement outcomes is that the functionality and behaviour of an AI system are monitored in production. A partner who can explain testing and monitoring in those terms is describing a practice, not making a promise.

What happens to your data, and what will you own?

Questions seven and eight cover what AI proposals most often leave vague: what happens to your data, and what you keep if the relationship ends. In the EU, the first of them has a legal side, set out in the Greece and EU checks below.

Will your people be ready, and will the partner stay?

The last two questions decide whether an AI system is still useful a year after launch: whether your people know how to work with it, and whether someone is still there to keep it working.

Training by role is a service in its own right: see how Aurelith runs AI training for teams.

What should you check when choosing an AI partner in Greece or the EU?

Choosing an AI partner in Greece, or anywhere in the EU, adds three practical checks to the ten questions: the language your people work in, the General Data Protection Regulation (GDPR), and AI literacy under the EU AI Act.

How does Aurelith answer these questions?

Aurelith answers the ten questions here with what it states publicly about how it works, and leaves out what it does not publish.

1. 01

   Where AI pays off

   Aurelith starts with an analysis of your business: your processes, the tools you use and how your people work. A proposal comes only after that analysis, and the first conversation is free.

2. 02

   The proposal

   A written proposal sets out the service level, scope, deliverables, timeline and investment, and it is agreed before implementation begins. There is no public price list.

3. 03

   Working together

   Aurelith builds together with your team, and works in Greek and English.

4. 04

   Your systems

   Aurelith’s AI agents and automations connect to the tools your company already uses, such as email, documents, CRM and ERP.

5. 05

   Approval

   Aurelith designs approval-first automation: AI prepares and moves the work, and a person approves every decision that matters before anything irreversible happens. In Company Brain, AI agents earn autonomy under human authority.

6. 06

   Proof that it works

   Every build is put to work with you: tested in real conditions, refined, and with your team guided through it. Company Brain is adopted through a Founding Design Partnership, with three to five agreed success measures and shadow operation before controlled assistance.

7. 07

   Your data

   Each automation and agent reads and writes only what its job needs, in the systems you approve, and data handling is part of the scope agreed in the written proposal, before implementation.

8. 09

   Training

   Role-based team training is part of Level 01, AI Consulting & Enablement, alongside leadership alignment and a prioritised AI roadmap.

9. 10

   After launch

   Support has no end date.

Aurelith does not publish a standard answer to question 08 (ownership and exit). Put it to Aurelith in the first conversation, exactly as you would to any other partner. How Company Brain decides what AI agents may do on their own is set out in its autonomy ladder.