AI is moving fast in finance. But some environments are more ready for it than others. Private equity is at the top of that list, and the tools being built right now reflect that.

In this edition, I look at why PE investment teams are particularly well-positioned to benefit from AI today, what the recent Claude plugin launch signals about where the technology is heading, and how to think about the right tool for the right workflow. The free section covers the landscape. The paid section gets into the specifics: a task-by-task tool mapping and a detailed breakdown of three different approaches to AI-assisted IC memo drafting, because the right approach depends entirely on how your team works.

I've been building and testing Claude workflows across finance teams for the past two years. Most teams that have Claude deployed are getting maybe 20% of the value they could be getting. Not because Claude isn't capable. Because nobody showed them how.

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PE has been on my radar for a while, but it moved to the top of the list this month for a reason. Over the past few weeks, I have had more than a dozen conversations with executives from PE firms, and something has shifted. A year ago, these conversations were exploratory. Now they are operational. Firms are asking which tools to use, how to govern them, and how to train their teams. That timing lines up with Anthropic's PE plugin release, and I do not think it is a coincidence.

Private equity runs on a structural contradiction. The firms managing the largest, most complex portfolios often have the leanest teams. A managing director overseeing a billion-dollar portfolio might have two analysts and a part-time CFO. That is not an oversight. It is the model.

That model is also exactly why PE is one of the most AI-ready environments in finance.

The workflows are high-stakes, time-compressed, and heavily structured. Deal screening follows a pattern. Due diligence follows a checklist. IC memos have a format. Portfolio reporting runs on a cycle. These are not loosely defined creative tasks. They are repeatable processes that happen under pressure, with limited people to execute them. That is a near-perfect description of where AI adds the most value.

Anthropic's labor market research, published in March 2026, puts some data behind this. Financial analysts rank among the most exposed occupations to AI, with business and finance tasks showing the highest theoretical AI coverage of any professional category. The report is not predicting layoffs. It describes which roles involve the kind of structured, knowledge-dense work that AI can already assist with meaningfully.

The February 2026 plugin release from Anthropic makes this concrete. Five prebuilt Claude plugins, each designed around a specific finance workflow: financial analysis, investment banking, equity research, private equity, and wealth management. A plugin is not just a chatbot. It is a preconfigured AI agent that understands your role, your typical data sources, and your standard outputs.

For a PE team, that means due diligence frameworks, IC memo structure, and KPI monitoring built in from the start, without configuring anything from scratch. The plugins are open-source on GitHub, so firms can adapt them to their own terminology and deal processes.

This is not a product update. It is a direction signal. Anthropic is investing in finance-specific AI infrastructure because that is where the workflow complexity and the willingness to pay both exist. If you are running a PE firm and this is not on your radar yet, it will be soon.

One important note: Wall Street Prep's 2026 benchmark found that Claude can hallucinate historical financial data subtly enough that subtotals look correct while individual line items are wrong. Use these tools with deliberate review checkpoints.

Efficiency is the obvious first layer: faster memos, faster research, faster reporting. Most firms will start there, and that alone justifies the investment.

But there is a second layer that most PE firms are not thinking about yet. AI has real potential in strategic decision-making: how you evaluate a market, how you pressure-test an investment thesis, how you think through a complex situation with incomplete information.

This is not about automating a task. It is about bringing better analysis to decisions that still require human judgment. The firms that figure out how to use AI at that level, not just as a productivity tool but as a thinking partner for high-stakes decisions, will have an edge that is harder to replicate than any efficiency gain.

The paid section gets into the how. If you are a subscriber, keep reading for a task-by-task tool mapping and three concrete approaches to IC memo drafting.

If you are not yet a subscriber, this is a good edition to upgrade on.

PE is one of the more interesting places to watch AI land right now. High stakes, lean teams, structured workflows, and a culture that moves fast when something works. The tools are ready. The question is whether the teams are.

If you are working through any of this in your own environment, I would love to hear what you are seeing. Just reply to this email and share your thoughts.

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Until next Tuesday, keep balancing!

Anna Tiomina
AI-Powered CFO