The short answer
We use AI like any powerful tool: to do routine work faster, so more time goes into judgment, testing and communication. It makes our people faster but makes no decisions about your systems. An accountable person reviews every AI-assisted output before it reaches you or your environment, and client data stays under our privacy commitments. You get the speed and a team that answers for the result.
Where AI helps us deliver faster
Analysis
Summarizing logs, vendor documentation and configuration exports so engineers spot what looks wrong.
Documentation
Draft runbooks, handover notes, diagram descriptions and user guides, checked against the real environment.
Code
Boilerplate, tests and refactoring options in software, ERP and integration work, reviewed before merging.
Routine support
Draft replies, knowledge articles and instructions for common requests, confirmed by a technician for your setup.
Preparation
Discovery notes into draft proposals, roadmaps or test plans the consultant rewrites and signs off.
AI shortens the first draft. The finished work is ours.
Our rules for using AI
- People accountableAI drafts, never approves; whoever delivers the work reviewed it and answers for it.
- Review and testAI-suggested changes reviewed, tested outside production where possible, recorded and reversible.
- Protect client dataHandled under our privacy commitments; de-identified or sample data wherever it does the job.
- VerifyAI can be confidently wrong; we check documentation, your environment and test results.
- Be openAsk how AI was used and we will say plainly; we follow your AI policy.
Responsible-AI guidance, including the NIST AI Risk Management Framework, rests on the same principle: accountability for outcomes stays with the organization and its people, not with an automated system. Our privacy policy covers client data.
Why we prefer de-identified data
Sending sensitive corporate or personal data to a public AI tool is a well-known risk, and the FTC's privacy and security guidance is a useful reminder that the organization holding the data remains responsible for it. We treat that risk seriously.
Rather talk it through? If you want the speed of AI-assisted delivery with a team that stays accountable, tell us about your project and we will show you how we would approach it. Talk to a Promatics specialist
"If you use AI, why not just use it ourselves?"
Fair question. For learning and first drafts, you should. A professional gives you everything around the draft:
| An AI tool gives you | Promatics gives you |
|---|---|
| A general answer | An answer checked against your systems, contracts and risks |
| Instructions | The work done, tested and documented |
| No memory of your environment | A team that knows your history |
| No responsibility for the result | A service agreement and people who own the outcome |
| Help when you ask | 24/7 monitoring and support for managed-service clients |
Helping you use AI the same way
Want faster document handling, smarter workflows or better use of ERP or CRM data? Our AI solutions and intelligent automation follow the same rules: a real problem, people deciding, personal information protected, results measured. See where AI genuinely helps back-office automation.
AI tools plus an internal generalist suit simple environments at low cost. Bring in a professional team when changes touch shared systems, security or personal information, when work must be done and tested rather than described, or when you need someone accountable outside business hours.
Questions to ask any provider about AI
- Which parts of your work use AI tools, and which do not?
- Who reviews AI-assisted output before it reaches us or our systems?
- How is our data protected when AI tools are used?
- Can we restrict AI use on our data when policy requires it?
- How are AI-suggested changes tested and documented?
- Who is accountable if AI-assisted work turns out to be wrong?
We answer all six for any engagement (how we work), and the AI we build for clients meets the same standards: see AI Solutions for consulting, Microsoft Copilot, custom assistants, agents, automation and governance.
Sources and further reading
Product capabilities and guidance change. These are the primary sources this article relies on, checked on the review date above.
- Artificial Intelligence Risk Management Framework (AI RMF), National Institute of Standards and Technology (NIST)
- Privacy and security guidance for businesses, Federal Trade Commission
- Data security guidance for businesses, Federal Trade Commission
This article is general information, not legal, accounting or security advice for your specific situation. Examples are hypothetical unless stated otherwise.