# AI leadership for private equity portfolios

> 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 an AI expert and fractional AI officer 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, rather than only advising on them.

**Portfolio companies get AI mandates from investors more often than from customers, and the mandate usually arrives without a method. The value concentrates in a small number of operational processes per company, and almost never in the same place twice.**

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

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## Where does AI actually pay for itself in private equity?

The processes worth automating in any sector share three properties: they repeat constantly, they consume qualified people, and nobody enjoys them. In this sector that usually means:

- **Shared-service functions** – finance, HR and customer support, where the same process runs across several holdings.
- **Sales and lead handling** – speed of response is measurable and usually poor.
- **Reporting and data consolidation** – manual assembly every month, every company.
- **Customer support volume** – the first place headcount scales with revenue.
- **Diligence readiness** – being able to answer AI governance questions at exit.

None of these are exciting. That is the point – the value comes from volume, not sophistication, and the exciting use case is usually the one that fails.

## What makes this sector different

- **A portfolio-wide AI mandate usually underperforms** a per-company diagnosis, because the expensive repeating process differs by business model even within one sector.
- **Diligence now asks AI questions.** Buyers and insurers increasingly ask what AI is in use, who approved it and what data passed through it. A holding that cannot answer takes a discount.
- **Shadow AI is a portfolio-level risk.** Unapproved tool use is near-universal and concentrates the exposure at fund level.

## How an engagement here typically runs

1. **Inventory what is already running** – Including the unapproved tools. In regulated environments this is usually the most uncomfortable and most valuable step.
2. **Map the repeating processes against cost** – Frequency multiplied by fully loaded cost per occurrence. The ranking usually surprises people.
3. **Establish governance proportionate to the risk** – Who approves what, what happens when a system is wrong, and how a decision is reconstructed months later.
4. **Ship the unglamorous one first** – Prove the pipeline end to end before attempting the ambitious thing.

## Frequently asked questions

### Should AI strategy be set at fund level or company level?

Governance and diligence readiness benefit from a fund-level standard. Use-case selection does not: the expensive repeating process differs by business model, so a portfolio-wide mandate tends to produce activity rather than results.

### What do buyers ask about AI in diligence?

What is in use, who approved it, what data passed through it, and who is accountable when a system produces a wrong answer. Holdings that cannot answer tend to take a discount rather than lose the deal.

### What is the fastest value in a portfolio company?

Usually the highest-frequency operational process rather than anything customer-facing. Frequency multiplied by fully loaded cost per occurrence ranks candidates faster than any workshop.

## Related

- [The role](/fractional-ai-officer/) – What accountable AI leadership covers.
- [Why pilots stall](/ai-implementation/) – The three causes, and which is yours.
- [EU AI Act obligations](/eu-ai-act/voice-agent-disclosure/) – What actually applies, and what is market convention.

## 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 this describes your operation

The useful first conversation is about one specific process rather than about AI in general.

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