Private Equity

AI is changing how the best funds source, diligence, and decide.

We help private equity firms deploy AI across the investment process, from origination to exit, securely and with the rigor your deals demand. Led by Adrien Foucault, ex-McKinsey consultant and Harvard MBA.

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The Market Reality

Most funds are already using AI. Few are using it well.

Adoption has outpaced capability. The gap between experimentation and a secure, systematic deployment is where competitive advantage is now being won and lost.

86%

of M&A teams have integrated generative AI into their workflows

1 in 3

only one organization in three has moved AI beyond pilots to scale

67%

cite data security as the top barrier to AI adoption

up to 85%

productivity gains reported on due diligence tasks

Sources: Deloitte, "2025 Generative AI in M&A Survey" (October 2025, 1,000 US corporate and PE leaders); McKinsey, "The State of AI in 2025" (global); EY due diligence productivity benchmarking.

Across the Investment Process

Where AI creates leverage, stage by stage

AI does not replace investment judgment. It compresses the time between a thesis and the evidence to support it. Here is where it matters most across your deal lifecycle.

01 / ORIGINATION

See more of the market, earlier

Most funds see only a fraction of the relevant deals in their universe. AI widens the aperture, systematically mapping sectors, scoring targets against your criteria, and surfacing consolidation signals before a teaser ever circulates.

Map an entire sector, its segments, and its key players in hours rather than weeks
Identify targets by precise criteria: sector, size, geography, financial profile
Detect weak signals: management changes, growth dynamics, build-up opportunities
Structure a first build-up thesis from AI-assisted research

The Question Every Fund Asks First

AI you can use on sensitive deals, safely

In a fund, teams handle confidential documents, sensitive analysis, and material non-public information that cannot be shared without precaution. The first instinct, pasting an Information Memorandum into a consumer chatbot, is exactly the instinct that creates legal and reputational risk.

There is a second, equally concrete concern: the reliability of what AI produces. Models can invent figures or distort a source. On an investment analysis, an undetected error has real consequences. Regulators, including the SEC in its recent examination priorities, are now scrutinizing how investment advisers govern AI use.

We treat this as a first-order design problem, not a footnote. Every deployment we lead is built around which tools are safe for which data, and how teams verify output before relying on it. This is where a senior, advisory-led partner differs from a generic training vendor.

How we build for confidentiality

Tool boundaries. Which tools are approved for which data, and a clear line between enterprise and consumer tools.
MNPI and data classification. A practical framework for what can be used, where, and with what controls.
Human-in-the-loop validation. Verification discipline built into the workflow, so output is checked before it informs a decision.
Governance. Clear policies on who can use what, on which deals, aligned with your compliance obligations.

How We Help Funds

Two ways to work with us

Some funds need a strategic partner to deploy AI across the firm. Others need their investment teams fluent and productive. Most need both. We meet you where you are.

Advisory & Implementation

Deploy AI across the fund

For funds ready to move beyond ad hoc experimentation toward a secure, systematic deployment. We can act as your embedded AI experts.

Partner BriefingHALF-DAYA working session for your partnership or investment team to align on what AI changes for the fund, with sector-specific examples.
AI Audit5 TO 10 DAYSA diagnostic of where AI creates the most leverage across your investment process, delivered as a written report with a prioritized roadmap.
Advisory & Implementation ProjectCUSTOM SCOPE, DEFINED TOGETHERWe embed with your teams to design governance, select and deploy tools, and build durable capability. Scoped to your fund's specific situation.

Capability Building

Make your investment team fluent

For funds that want their investment professionals genuinely productive with AI, on the work they actually do, not on generic examples.

Investment Team WorkshopsHANDS-ONWorking sessions where analysts and associates apply AI to real PE use cases: dataroom review, IM analysis, memo drafting, IC preparation.
Leadership SessionsFOR SENIOR TEAM MEMBERSTailored to Partners and Directors who need to understand what AI changes about the fund without getting lost in the technology.
Prompt Library & Workflow TemplatesTUNED TO YOUR PROCESSA practical toolkit built around your fund's actual deal workflow, so the capability outlasts the engagement.

Why Spaik

Built for finance, led by a practitioner

Finance depth, not generic AI

We teach AI applied to finance at HEC Paris, to the M2 students who go on to careers in funds and banks. We understand the investment process and the language of a deal, not just the technology.

Senior, practitioner-led

Spaik is led by Adrien Foucault: ex-McKinsey consultant, Harvard MBA, advisor to leading professional services firms, and a regular contributor on AI strategy in Les Echos. This is tested judgment, not secondhand theory.

Built for confidentiality

We design AI adoption around the data security, MNPI, and governance requirements that funds actually face. Security is the starting point of every engagement, not an afterthought.

Selected Clients & Institutions

PwCHEC ParisSciences PoESSECVinturaHoneycomb

1,500+

professionals trained across consulting and financial services

+56

Net Promoter Score on recent corporate AI programs

4.3/5

average participant rating across 2024 to 2026 cohorts

Common Questions

What funds ask us

Yes, provided it is done within a clear framework for confidentiality, verification, and tool selection. AI can synthesize documents, surface key indicators, flag inconsistencies, and structure a first reading. It accelerates and organizes the work, but it does not replace diligence conducted by your professionals. The critical question is which tools are appropriate for the data in question, which is exactly what we help you establish before any deal documents are involved.

It depends on the use case, the sensitivity of the data, and the deliverable. Enterprise versions of tools like ChatGPT, Claude, and Copilot offer materially different data handling than their consumer counterparts, and the distinction matters enormously for MNPI. Specialized platforms add deeper diligence and market-intelligence capabilities. Part of every engagement is establishing a clear, documented policy on which tools are approved for which data.

By building verification discipline into the workflow rather than trusting output by default. We train teams to treat AI as a first draft and a thinking partner, never as a source of record, and to check figures and claims against primary documents before they inform a decision. Research has shown that public models can omit a meaningful share of the important datapoints a human analyst would surface, so structured verification is non-negotiable on investment work.

A focused audit typically runs five to ten days and gives you a clear picture and a prioritized roadmap. A full deployment, including governance, tool rollout, and team capability building, is scoped to your fund's size and maturity, and usually unfolds over a few months. We deliberately start small, with a diagnostic, so you have clarity before committing to a larger transformation.

Yes, where there is a concrete use case that justifies it. In private equity, that often means agents for market research and screening, document-analysis agents that read an Information Memorandum and extract the key points, or monitoring and reporting agents across the portfolio. The goal is always an agent that is genuinely useful to the investment team, built around your documents, your criteria, your workflows, and your confidentiality constraints.

It depends on where you are. If your partners need to align on what AI means for the fund, start with a briefing. If you need a clear, evidence-based picture before committing budget, start with an audit. If you have already decided and need a partner to make it real, an advisory and implementation project is the right entry point. The first conversation is where we work that out together.

Let's Talk

This is not for every fund.

We work with a small number of funds that are serious about making AI part of their investment edge, where a senior partner is personally sponsoring the initiative rather than delegating it.

If your firm is ready to move past experimentation, let us talk.

Request a PE AI Audit Or email adrien@spaik.co directly

Spaik