Private equity firms are leaning into GenAI to accelerate deal sourcing, automate due diligence, and enhance portfolio operations. In 2023 alone, private equity (PE) firms poured over $2.18 billion into GenAI capabilities, doubling the previous year’s total. The technology promises real edge across the investment lifecycle.
But with that opportunity comes a direct question from LPs, auditors, and regulators: How are you protecting sensitive data inside AI workflows?
Most firms don’t have a satisfying answer. While they may issue internal guidance like “don’t input confidential data into public AI tools,” these rules are often unenforced and easy to bypass. In a world where time is money and AI tools are just a browser tab away, vague policy isn’t enough. PE firms need a way to actually enforce their AI policies in real time, without slowing down the business.
Here’s how leading private equity firms are rethinking AI governance—not as a compliance exercise, but as a foundation for secure innovation.
Step 1: Understand How Your Teams Actually Use AI
Investment teams, operations leads, and even compliance staff are increasingly experimenting with AI. They’re using GenAI to summarize memos, generate market landscapes, compare targets, and prep board materials. The appeal is obvious: less time formatting documents, more time making decisions.
Blocking these tools doesn’t make sense. Not only would it hinder productivity, but it would inevitably lead to a surge in Shadow IT. When AI tools are blocked outright, employees often find workarounds. They log into personal accounts or use free-tier tools that operate outside the enterprise's control.
For example, more than 60% of ChatGPT users use the free tiers. That means sensitive deal data, LP information, and proprietary models may be exposed to systems the firm has no oversight over.
In private equity, a single data leak can derail a deal, violate NDA obligations, or invite regulatory scrutiny. You can’t govern what you can’t see. But more importantly, you can’t protect what you can’t control.
Step 2: Inventory AI Tools and Use Cases Across the Firm
Before you can govern something, you need to know what exists. Most private equity firms lack an inventory of the AI tools in use across their organization, let alone at the portfolio level.
Start with an AI asset inventory. This means identifying:
- Sanctioned tools used within the firm (e.g. ChatGPT Enterprise, Copilot, custom LLM apps)
- Unapproved or “shadow” tools accessed by staff or portcos
- Key data flows where AI is being used for analysis, automation, or content creation
Firms operating across borders need to treat this seriously. The EU AI Act now mandates that companies document and risk-rank their AI usage.
Establish a governance committee that brings together legal, compliance, IT, and business stakeholders. This group should define acceptable use cases, review AI vendors, and determine how policies will be enforced.
Step 3: Draft an AI Policy That Matches Real-World Use
Generic AI usage policies don’t cut it in private equity. Most templates say things like “Don’t enter sensitive information into public AI tools.” But what counts as sensitive? Is anonymized financial data okay? Can GenAI summarize a CIM or draft a 100-day plan?
Policies must be specific. They should clearly state:
- Which tools are approved, and for what use cases
- Which versions of the tools can I use?
- Can I upload files?
- What data classifications are restricted from GenAI systems
- When and how teams can request access to new tools
- How GenAI output can be reviewed before being included in official materials
For example, it should be obvious to an associate that entering raw LP data into a free AI chatbot violates policy, while generating a summary of a public 10-K is permitted using a vetted tool. No ambiguity. No room for interpretation.
Investors are starting to ask direct questions. Telling them you have “guidelines” without enforcement doesn’t fly.
Step 4: Train Teams Continuously, Not Just Annually
Most employees aren’t trying to violate policy. They’re trying to move faster and make better decisions. But without training, even well-intentioned use can lead to breaches.
Too often, AI training is reduced to one-time check-the-box modules. But effective enablement requires ongoing, role-based instruction.
- Deal teams should understand when they can use AI for memo drafting, and where the boundaries are
- Portco operators need to know how to work with AI assistants when handling operational metrics or customer communications
- Legal and compliance should get guidance on how to assess new GenAI tools and handle vendor risk
The more teams understand what’s allowed (and what’s not) the less likely they are to go around policies. Training builds muscle memory, reduces mistakes, and creates a security-aware culture.
Step 5: Visibility Isn’t Enough. You Need Real Control.
Many firms assume that logging AI usage or reviewing network traffic is enough. It’s not.
Tools like CASBs and traditional DLP platforms might tell you someone accessed ChatGPT or tried uploading a file. But they can’t see what was typed into a prompt. They can’t parse whether an analyst pasted a sensitive term sheet or a public press release. And they can’t stop the action in real time.
You don’t need more logs. You need control.
Harmonic provides that control, at the exact point of risk: the browser. That’s where GenAI tools live. Harmonic sits in the browser and uses lightweight, AI-powered models to evaluate what’s being typed or pasted. If the content violates policy, it’s blocked immediately or redirected to an approved alternative.
This is prompt-level enforcement that traditional tools simply can’t deliver.
For example:
- If an analyst pastes a deal memo into a non-vetted GenAI tool, Harmonic blocks the upload before it leaves the browser.
- If a portco CFO uses a personal GPT account to analyze investor materials, Harmonic stops it and suggests an approved internal tool.
- If someone tries to send internal financials to an AI model hosted in a non-compliant region, Harmonic prevents it automatically.
This isn’t just visibility. It’s real-time protection that operates within workflows. And when employees know the firm has their back with safe AI usage, adoption goes up.
One customer reported a 300 percent increase in GenAI usage after deploying Harmonic. At the same time, sensitive data exposure dropped by 72 percent.
Final Thought: Control Is What Unlocks Innovation
As LP scrutiny increases and AI regulation accelerates, PE firms that can’t show real governance and enforcement will face harder capital raising conversations, increased insurance costs, and potential reputational damage.
A strong AI governance program does more than reduce risk. It enables the business.
When employees know they can use powerful tools safely, productivity increases. When compliance teams have actual enforcement, oversight improves. When CIOs can implement policy without breaking workflows, innovation scales.
Harmonic delivers the missing piece: real-time, enforceable control over GenAI use, right where it matters.
Because in private equity, protecting sensitive data isn’t a limitation. It’s how you win.
To learn more about how Harmonic Security can help your Private Equity firm with governing GenAI and enforcing effective AI usage policies, set up time with our team here.
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