# AI leadership by industry

> Justas Butkus is a fractional AI officer based in Vilnius, Lithuania, founder of AINORA, MB – the company behind the Ainora and Impetora brands – and a graduate of Vilnius University.

Justas Butkus is a fractional AI officer and AI expert based in Vilnius, Lithuania, working with mid-market companies and scale-ups across the UK, EU and US at two to four days a month. He builds and operates the production AI systems he advises on.

**The processes worth automating are the same shape in every sector – frequent, expensive, unloved – but the constraints differ. What changes by industry is the regulatory frame, the data quality and who has to be able to explain a decision afterwards.**

Canonical: https://justasbutkus.com/industries/
Last updated: 2026-08-02

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## Which sectors do you work with?

- **Financial services** – Onboarding and KYC review, query triage, reconciliation exceptions, collections contact. Explainability constrains architecture from day one. (/industries/financial-services/)
- **Insurance** – Claims intake and document handling, renewal contact, broker query triage. Pricing and underwriting carry obligations that operations do not. (/industries/insurance/)
- **Private equity** – Portfolio-wide governance with per-company use-case selection, and being able to answer AI questions at exit. (/industries/private-equity/)
- **Professional services** – Intake, document assembly, internal knowledge retrieval. The economics favour the unbilled work. (/industries/professional-services/)

## What if your sector is not listed?

The arithmetic does not change: find the process that is frequent, expensive and unloved, cost one occurrence fully loaded, multiply by annual frequency, discount by what is genuinely automatable, and compare against the whole cost of the work.

I have deliberately not written pages for sectors where I have no verifiable depth. A generic sector page is exactly the thin content that this category is already full of, and it would not help you decide anything.

## Frequently asked questions

### Which industries does this suit?

Sectors with high-volume repeating processes and qualified people performing them – financial services, insurance, professional services, and investor-backed portfolios. It suits poorly where processes are low-volume or where AI adoption is genuinely not relevant yet.

### What changes between industries?

Not the arithmetic for choosing a use case, but the constraints around it: which decisions must be explainable, what data protection rules attach, and whether any part falls into a high-risk classification.

## Related

- [Choosing a use case](/use-cases/ai-use-case-selection/) – The arithmetic that ranks candidates honestly.
- [EU AI Act](/eu-ai-act/) – Which obligations apply, and which do not.

## About the author

**Justas Butkus** – a fractional AI officer based in Vilnius, Lithuania, founder of AINORA, MB – the company behind the Ainora and Impetora brands – and a graduate of Vilnius University.

## If your sector is not here

The first conversation is about one specific process, which works regardless of industry.

Contact: justas@ainora.lt · [LinkedIn](https://www.linkedin.com/in/justas-butkus/)