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Last year, every portco needed an AI story.

This year, AI needs to be driving EBITDA results you can measure.

Talas works with private equity and growth equity firms and their portfolio companies. We find the AI opportunities most likely to move EBITDA in each company, help the team capture them and measure what changed.

Has AI moved EBITDA in your portfolio yet? Could you measure it if it had?

You're probably fielding questions from LPs about how the firm and its companies are using AI. But the things that drive your returns haven't changed: revenue growth, margins, debt paydown, strategic acquisitions and the exit multiple. AI only matters to the extent that it moves one of them.

The question has changed from “are you using AI?” to “what did it return?”.

A year ago, having an AI strategy was enough. Now boards and LPs want to see what it produced. That doesn't come from adding more tools. It comes from changing how a team actually does its work.

If you've pointed an AI agent at your portfolio data, you've seen its limits.

The numbers exist, but they're spread across board decks, monthly packages and emails, and each company defines them a little differently. Before you can apply AI to your portfolio, that data has to be in one place, on one set of definitions.

Financial engineering can't carry returns anymore. Operational value creation has to.

For most of the last decade, rising multiples and low rates delivered a large share of the return. With higher rates, more of it has to come from running the company better, by growing revenue and expanding margin.

See where AI can move EBITDA in your portfolio.

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