A perspective from Annie Eissler, CMO, Altvia
Last month I wrote about what I heard at PEI’s IR Network meeting: I saw a room full of IR professionals working out, in real time, how to use AI without letting it do the thinking for them. A few weeks later I was back in the room, this time at another PEI IR Network meeting. The same core questions were on the agenda, but this time was different.
Last month’s conversation was mostly internal: how do we use AI? How do we not get it wrong? What will our LPs think if they find out? Last week, the conversation had shifted. LPs aren’t just forming opinions about AI use anymore. They’re asking directly how GPs are using it, and that means GPs have to think differently about their AI strategy.
Here’s what stood out.
Personalized LP communications are the clearest AI use case, and also the trickiest one
The most concrete idea I heard came from a conversation about turning deal memos into short, personalized notes for LPs, rather than generic updates. It’s a good use case: the raw material already exists, and AI is well-suited to reshaping it into something that reads like it was written for one person rather than a distribution list.
But the group was candid about where the line sits. There’s a real distinction between the low-hanging fruit (a quick capsule summary) and what would actually be meaningfully impactful. This almost always requires pulling data from a lot of different sources and takes real work to get right: IC summaries, LP meeting notes, and reporting all live behind different systems, often in different formats. Nobody in the room felt like they’d fully solved this. As one person put it, the real bottleneck is data quality: garbage in, garbage out. The hard part isn’t the AI, it’s getting information into a usable format in the first place. It’s a theme that came up again and again last week: technology is rarely the constraint. The underlying data infrastructure is.
Confidentiality is a harder line than it was six months ago
This came up more specifically at last week’s meeting. Sub docs and other sensitive materials can’t just get pushed into a general-purpose LLM. That’s not a compliance nicety; it’s a real operating constraint that shapes which tools a firm can actually use and how. It’s consistent with what Deloitte found in its 2025 GenAI in M&A Survey of 1,000 corporate and PE dealmakers: data security was the single most-cited barrier to GenAI adoption, ahead of every other concern. For private capital firms, where sub docs, LPA terms, and side letters are about as sensitive as documents get, that distinction isn’t theoretical.
At the same time, LPs want more from their GPs, not less. More data and more transparency. So GPs are stuck trying to do both at once: securely share more, but never make it feel like a bot did it. One comment from the room stuck with me: “Nobody wants their IR comms to read like ‘a bot.'” That’s the same reputational risk I wrote about in my last post, except now LPs are actually asking the question, not just wondering about it.
LPs are starting to ask GPs directly how AI is used in the firm
It’s no longer hypothetical that an LP might wonder about a GP’s AI adoption. LPs are now asking. The data backs this up: Private Equity International’s LP Perspectives 2026 Study found that nearly half of LPs surveyed are closely monitoring how their GPs adopt AI in investment and operational processes, and almost as many report mixed feelings about it, largely driven by risk concerns. The ILPA DDQ framework, which the majority of institutional LPs now use as a baseline for manager evaluation, continues to expand with each cycle, and it would be reasonable to expect AI governance to become a standard section, rather than an ad hoc follow-up question.
If your firm doesn’t yet have a clean, honest answer to “How do you use AI, and what guardrails are in place?” it’s time to build one. Not because someone will send it back with a red pen if you get it wrong, but because you should probably be able to answer that question clearly, regardless of who’s asking.
The fee conversation nobody wants to have, but needs to
If firms are getting more efficient because of AI, will LPs start asking why fees haven’t come down? It was framed as hypothetical, but it’s not disconnected from what’s actually happening in the market. Bain’s 2026 GP Outlook already points to real downward pressure on headline management fees, particularly at scale. A recent bfinance poll found that a large share of LPs report fee reductions for like-for-like private market strategies, with softer fundraising and disappointing distributions shifting real pricing power toward investors.
AI efficiency gains and fee pressure are two separate trends right now. But it’s not hard to see an LP putting them next to each other, and GPs should probably have a point of view before that question shows up in a meeting. The best response is to show where the efficiency actually goes: faster answers, better reporting, more time for the relationship itself. That’s a different story than “we cut costs and kept the fee the same.”
MCP servers came up, unprompted
Someone in the room made an offhand comment: if you already know what an MCP server is, you’re ahead of the curve. It’s a small signal, but it’s consistent with where the infrastructure conversation is heading. Most firms are still thinking about AI at the level of individual tools and prompts. Fewer are thinking about the underlying protocols that let those tools connect to a firm’s systems and data securely. That gap between “using an AI tool” and “having AI infrastructure” is expected to keep widening.
Where this leaves us
The first meeting focused on where and how IR teams should utilize AI. The second made it clear the conversation has moved past that. LPs are asking direct questions, fee dynamics are shifting underneath the AI conversation whether anyone planned for that or not, and the confidentiality line between what can and can’t touch a general-purpose LLM is getting firmer, not softer.
The through-line from both meetings hasn’t changed, though: the firms that feel most at ease are the ones with real infrastructure and clear answers, not the ones with the most impressive prompt. If anything, last week’s session raised the stakes on that point. An LP asking how you use AI in a DDQ isn’t looking for enthusiasm. They’re looking for governance.
