We talk to a lot of funds. And there is a conversation that happens at least thrice every week.
A partner tells us, with total sincerity, that the fund is "already using AI quite heavily". Naturally, we ask what that looks like. There's usually a short pause.
Then someone smiles and admits what’s been happening.
One of the analysts has become very good at using ChatGPT. That analyst summarises CIMs, drafts meeting notes, cleans up investment memos and occasionally builds a market map before anyone else has finished their coffee. Everyone knows they're unusually productive. Nobody is entirely sure how they're doing it, and nobody has written any of it down.
Somewhere between those individual habits, the fund has convinced itself it has an AI strategy.
It doesn't.
The analyst isn't the problem. Quite the opposite. They spotted repetitive work, found better tools and quietly made themselves more effective.
The problem is mistaking one person's workflow for institutional capability.
Individual productivity isn't organisational capability
Most firms underestimate how much AI adoption is already happening. It rarely starts with an executive initiative.
It starts because an analyst decides reading a 120-page CIM is probably not the best use of a Tuesday afternoon. Over time, those personal workflows become surprisingly sophisticated.
Prompts get refined. Templates improve.
Useful shortcuts emerge. But almost none of it belongs to the fund.
It lives inside browser history, saved prompts and personal chat accounts.
When that analyst leaves, the workflow usually leaves with them.
That's not an AI strategy.
Three problems every fund eventually discovers
The productivity gains are real. The operational risks are too.
Confidential information leaves your environment
When investment documents are uploaded into personal AI accounts, confidential deal information leaves the systems your firm controls.
Many partners don't realise this is already happening because the process is informal rather than malicious.
Every analyst develops a different process
One analyst summarises every CIM one way. Another uses different prompts.
A third asks AI entirely different questions. The result isn't just inconsistency.
It's impossible to compare two investment analyses produced through completely different workflows.
The firm never learns
Perhaps the biggest problem is also the quietest.
Every useful prompt. Every refined workflow. Every lesson learned.
All of it belongs to individuals instead of becoming part of the firm's investment process.
Institutional knowledge never becomes institutional.
What a real AI strategy actually looks like
A genuine AI strategy has very little to do with buying another AI product.
It starts with standardising how the investment team works.
Every deal should move through the same secure workflow. Every conclusion should point back to evidence. Every opportunity should be evaluated against the fund's investment thesis using the same framework.
Knowledge should accumulate across deals rather than disappearing whenever someone changes jobs.
That's when AI stops being an individual productivity hack and starts becoming infrastructure.
Where most firms should start
Firms probably don't need another strategy workshop. They need a conversation with the analysts already using AI every day.
Find out what's working.
Understand which repetitive tasks they've already automated.
Then move those workflows into a secure environment the whole investment team can use consistently.
That's the point where AI becomes part of the firm's operating system rather than someone's favourite browser tab.
That's also the philosophy behind askRIA.
Instead of scattered prompts across personal accounts, the platform gives every deal a shared workspace where documents remain secure, analysis follows the fund's investment thesis, conclusions are linked back to evidence and knowledge stays with the firm instead of individual team members.
The investment firms creating the biggest advantage from AI aren't necessarily the ones talking about it most loudly.
They're usually the ones quietly turning individual productivity into repeatable systems.
Every firm already has someone experimenting.
The opportunity isn't finding them.
It's making sure the workflow they've built becomes everyone's workflow.
Keep reading
- the problem with using ChatGPT for Due Diligence
- The 10 AI Agents Every PE firms needs
- Best AI Due Diligence tools for your fund
*Ready to turn the browser-tab hack into a real workflow? Run your first deal free in askRIA and give your team one secure place to work.*
FAQ’s
- What does an AI strategy look like for a PE or VC fund?
A real AI strategy gives every investment professional access to the same secure workflow, evaluation framework and evidence base. It standardises analysis across deals instead of relying on individual analysts using consumer AI tools independently.
2. How are investment firms using AI today?
Most PE and VC firms use AI informally. Analysts often summarise CIMs, draft investment notes and research markets using general-purpose AI tools. While this improves individual productivity, it rarely becomes a shared investment workflow.
3. Is using ChatGPT for investment research a risk?
It can be. Uploading confidential investment documents into consumer AI tools may create security, confidentiality and governance concerns. It also makes analysis inconsistent across investment teams.
4. Why do firms struggle to scale AI adoption?
Most AI adoption starts organically with individual analysts rather than through structured workflows. Without shared processes, secure systems and institutional knowledge, productivity gains remain isolated instead of benefiting the entire firm.