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A perspective from Annie Eissler, CMO, Altvia

I recently moderated a panel at PEI’s IR Network meeting in Chicago and spent the rest of the afternoon in roundtables and side conversations with IR professionals across the industry. While the official topic of my panel was AI and technology in IR workflows, AI ended up being the dominant theme in every panel and conversation throughout the day. 

What struck me most were the incredibly thoughtful conversations, insights, and concerns that were discussed throughout the day. The real conversation wasn’t whether AI matters, it was how teams are actually using it without letting the tool do the thinking for them.

Here are a few of my key takeaways from the day:

No definitive playbook yet, but significant experimentation 

What came across loud and clear was that teams are experimenting, comparing notes, running pilots, and making judgment calls in real time. But the pace of change in AI right now is often outrunning internal approval cycles, compliance reviews, and honestly, most people’s capacity to keep up.

Several attendees who felt optimistic and comfortable about their team’s AI usage had one thing in common: clear guidelines and guardrails in place. Some examples included:

• Building tools that can be deployed across the firm, as opposed to individual prompting.
• Specific processes that include where tech is used and where human review/touchpoints are along the way.
• Establishing a rule: AI used for operational leverage, but all communications need human eyes. 

LP attitudes on AI are mixed and that should shape how you use it

One of the more clarifying moments of the day came when LP attitudes on AI came up directly. The feedback was genuinely split. Some LPs say they don’t mind knowing AI is being used in the communications they receive, while others said they identify it in the first few words and move on. 

But here’s what was consistent across the IR side of the room: nobody wants their LP thinking “AI wrote this.” Not because AI can’t produce good output, but because the moment an LP feels like they’re on the receiving end of a template, the relationship takes a hit. 

However, I urge teams not to fall into the trap of trying to hide that AI was used, and to remember that the goal is to make sure what you’re sending is relevant, truthful, and specific enough to signal that you actually know who you’re talking to. Attendees all agreed that communications should be brief enough to respect LP’s time, and human enough to warrant a response.

The human element is non-negotiable

What came through clearly on the IR side is that no matter where LPs land on AI-generated outreach, IR professionals don’t want to be in a position where an LP feels like the relationship is being managed by a bot. The reputational risk is real, and it’s shaping how carefully teams are thinking about what AI touches and what it doesn’t.

AI can handle the prep, the research, the first draft, the operational lift. It cannot build a relationship, and it can’t do business. 

There was a story that surfaced in the room about an IR associate who used AI to fix a problem in some analysis. When asked how it was fixed, the answer was “I don’t know, Claude did it.” That’s a risky sentence, and reiterated the need for firm-wide guidelines about where human judgment stays in the process.

Compliance is top of mind

SEC regulations and compliance considerations are sitting in the back of everyone’s mind when it comes to AI in LP communications. Nobody had clean answers. But the awareness is there, and it’s shaping how cautious teams are about what they automate and what they don’t. That guardrail question isn’t resolved yet for most firms, but continues to be a top priority.

Build a tool, not just a habit

One perspective I heard and gave me pause was that there’s a difference between using AI as an assistant and building AI into your infrastructure. Meaning, an assistant answers the specific question posed, but if you build a tool it builds and refines over time. IR professionals should be thinking about how to make their AI capabilities repeatable and institutional, not dependent on an individual’s prompting prowess.

The operational gap is real and unglamorous

This theme came up here, it also came up in our recent webinar with Private Markets Group as well, and it’s boring and unglamorous – data sources, data integrity, and data completeness remains an underlying issue. 

Reporting, deal stages, getting notes from a multi-person LP call into the CRM with the right context attached all came up as workflows people want to solve. Excel is still everywhere for portfolio monitoring, and most teams are on CRMs that weren’t built for private markets. The tools people want exist in pieces. 

A cohesive AI-native solution for an IR team, end to end, doesn’t really exist yet as a product in this market, and teams continue to look for tools that streamline data and operations. 

Relationship building at the center of the conversation

Across every conversation, the through-line cut to the heart of the IR function – how do you build, maintain, and strengthen relationships. Common knowledge is not to show up in front of an LP only when you need them, but to maintain consistent, low-stakes engagement like sharing something relevant or following up after an event. 

Of note: short-form content is resonating well. Firms are finding that consistency and thoughtfulness matter more than production value. 

The focus has shifted to the institutional relationship, not just at the individual contact level. Where AI entered this chat was in a question posed: “How can AI help me operationalize these consistent, but personalised, engagement points?” 

At the end of the day: What does real AI usefulness look like? 

One of the reasons I enjoy attending the PEI networking events is that the size lends itself to real conversations about what’s happening across the board in the IR function. If I had to summarize the day in one sentence, it’s that Investor Relations remains a relationship business. Any successful tool or technology that is implemented will make LP engagement feel more personal, not less, but will alleviate operational busywork on the backend. 

Nobody has the full playbook yet, but the questions the industry is asking are spot on.

At Altvia, those are the questions driving our product direction.

We build LP and deal sourcing engagement software for private capital firms. If you’re thinking through what AI-enabled IR looks like in practice, we’d like to be part of that conversation.

Schedule time to talk to our team.

On May 1, 1975, the SEC abolished fixed commissions in public equity markets. Captive investors, information asymmetry, pricing power, all dynamics that broker-dealers had taken for granted for generations collapsed almost immediately. Discount brokerages proliferated. Retail investors entered at scale. Many firms adapted and rebuilt their operating models around what the new investor base actually needed, others that didn’t were absorbed.

That transformation took three decades and the same structural forces are moving through alternative investments today, but they are moving faster.

What LP sophistication actually looks like now

The LP who accepts a static PDF summarizing their private holdings ninety days after a quarter closes is the same LP receiving real-time marks, granular exposure data, and daily attribution across their public portfolio. They have noticed the gap. More importantly, they are acting on it.

Operational quality has become a formal gating criterion, not a secondary consideration. Research from CSC Global found that 85% of LPs have rejected an investment opportunity over operational concerns alone, and 68% now rank operational clarity above historical returns when evaluating a GP. For a growing number of institutional LPs, the quarterly reporting cycle is a disqualifying signal.

Dedicated private markets teams with data infrastructure, proprietary evaluation frameworks, and multi-fund coverage models are now standard among large endowments, sovereign wealth funds, and pension systems. Preqin data shows that the median fundraising cycle stretched to 19 months in 2024, nearly five months longer than a decade prior. 

LPs are benchmarking responsiveness, data availability, and communication discipline as proxies for operational maturity. With public market benchmarks as their reference point, institutional LPs are now evaluating GPs on criteria that would have once been considered secondary:

• A slow response to a data request
• An inconsistent reporting format across funds
• A re-up conversation that only starts when the GP needs capital

The pull model is structurally broken

The traditional GP communication model runs on pull. LPs request information, GPs respond at scheduled intervals. The LP carries the burden of staying informed, knowing when to ask, and interpreting whatever arrives. That model has been the industry standard for decades, and it persists today mostly because replacing it requires operational investment that many GPs have not made.

GPs who invert the model by pushing timely, targeted intelligence to LPs continuously rather than waiting for the quarterly window create a compounding relationship advantage:

• A portfolio company experiencing material developments warrants communication before the next scheduled update.
• An LP nearing their allocation limit in a sector needs context before they make a decision that removes them from a future raise.
• A re-up conversation that starts six months before a fund close, grounded in documented relationship history and engagement data, is categorically different from one that starts at the deadline.

In a recent Altvia-hosted webinar, Matt Curtolo, LP & GP Advisor, MC Advisory, who managed hundred of GP relationships, put it plainly:

“After every LP conversation, the discipline that separates durable IR operations from reactive ones is recording what the LP needs to see and when they want to hear from you again, and then actually doing it.”

That is not a technology observation. It is a relationship management discipline observation. But at any meaningful scale, that discipline requires infrastructure to execute.

The operational infrastructure requirement

The cultural shift from reactive reporting to proactive intelligence delivery is real, but culture alone does not produce personalized LP communications at scale or surface relationship risk signals before they become visible problems.

That requires a data foundation where every LP interaction, commitment event, document exchange, and engagement signal is captured as structured information, and where that information informs what happens next.

Most GPs are still assembling reporting packages by hand and building re-up lists in spreadsheets. The firms pulling ahead are doing something structurally different: treating LP behavioral data as a strategic asset: tracking who is engaging, with what, at what depth, and when.

The compounding consequence of not moving

The wealth channel is entering the alternative market space at scale. High-net-worth and ultra-high-net-worth individuals in the US alone collectively hold an estimated $8 trillion in global wealth, with alternatives representing a fraction of most portfolios. GPs who build the operational infrastructure to serve a high-volume, intermediary-mediated investor base will access a transformative capital source. Those who cannot execute the proactive intelligence model at scale may find that channel effectively inaccessible regardless of investment performance.

The LP sophistication shift is not a temporary condition to be managed until market dynamics ease. It is a structural reset of the baseline expectations that govern institutional capital commitment decisions. The equity market transformation took decades because technology cycles were slow and capital markets were regionally fragmented. Neither condition holds today.

The playbook from that transformation is available. Firms that adapted early thrived. Firms that waited were marginalized or absorbed. The pattern is not obscure. The question is whether you use it.

Download the Altvia whitepaper, Massive Alternative Market Shift: Déjà Vu?, for the full analysis of where the alternatives industry is heading and what it demands operationally.

For most of private equity’s history, the operational model was built around a concentrated investor base. Deep relationships. Manual processes that worked because the volume was manageable and the relationships were few enough to hold in your head.

That model served the industry well, but it’s running out of runway.

The investor base entering alternatives right now is categorically different in size, composition, and expectation. The proportion of RIAs planning to increase their allocations to private equity moved from 45% in 2024 to 74% in 2025, according to KKR’s 2025 RIA Survey. Family offices, high-net-worth individuals, and wealth platforms are committing capital across fund strategies, co-investments, and secondaries simultaneously. The firms that build the operational infrastructure to serve this investor base at scale are positioned to grow in ways that were structurally unavailable five years ago.

The question is not whether to build for it, but rather how to start and move quickly.

What scaling to thousands of LPs actually changes

Going from hundreds of institutional LPs to thousands wealth-channel investors is not a linear increase in workload. It is a different category of operational challenge entirely.

With hundreds of LPs, a skilled IR team can manage relationships through memory, judgment, and high-touch communication. Reporting can be assembled manually. Co-invest preferences can be tracked in a spreadsheet. Re-up conversations can be initiated based on what a partner remembers from the last meeting.

At thousands of LPs across fund commitments, co-investments, secondaries, and continuation vehicles, none of that holds. Consider what changes:

• A single LP may now have three or four distinct relationships with your firm across different vehicles, each with its own reporting requirements, fee economics, and communication cadence.
• Co-invest pipelines require real-time preference tracking across a much larger population. The LP who passed on deal X but has expressed interest in sector Y needs to be identified and contacted before the window closes.
• Wealth-channel investors expect reporting formats compatible with their portfolio management platforms, not quarterly PDFs assembled by hand.
• Re-up conversations cannot start at the deadline when you have thousands of relationships to manage. They have to start six months out, which means you need to know where each relationship stands before anyone picks up the phone.

Over 84% of wealth managers surveyed by BNY Pershing expected their alternatives allocations to increase, according to a February 2025 survey. That capital is moving toward GPs who can receive it operationally, not just those who have the best investment track record.

The firms moving fast are doing three things now

The good news is that the infrastructure gap between where most mid-market GPs operate today and where they need to be is closable. The firms that are moving quickly share a common approach.

• They are treating LP data as a strategic asset, not a record-keeping function. Every interaction, commitment, co-invest conversation, and communication preference gets captured in a structured system. Not because it is tidy, but because that data is what makes proactive engagement possible at scale. Knowing that an LP opened your Q3 report three times but has not responded to your last two emails is an early signal. Knowing that a family office has taken co-invest on two deals but passed on a third tells you something about their appetite. That intelligence exists in every firm. Most firms cannot access it systematically.
• They are segmenting LP workflows before they need to. Institutional LPs, family offices, and wealth-platform investors do not have the same reporting expectations, communication cadences, or service models. Firms that build segmented workflows before volume forces the issue, scale without the friction of retrofitting. Firms that wait are rebuilding infrastructure mid-fundraise, which is the worst possible time.
• They are thinking about re-up earlier than feels necessary. The re-up conversation that begins six months before a close looks nothing like the one that starts at the deadline. The difference is not relationship quality or intent, it’s whether you have a system that tells you where each LP stands before anyone picks up the phone. At 500 LPs, that kind of advance visibility does not happen through institutional memory. It requires infrastructure in place before you need it.

Where the public equity parallel is instructive

The equity market transformation of the 1970s and 1980s offers one honest lesson for alternatives GPs: the firms that built for the new investor base before the volume arrived ended up with compounding advantages. The firms that waited until volume forced their hand rebuilt while their competitors were already operating from a position of accumulated institutional intelligence.

The alternatives industry is in an earlier stage of the same transition. In the United States, evergreen vehicles and semi-liquid fund structures grew to $348 billion in AUM and attracted $64 billion in inflows in 2024. (McKinsey, Asset Management 2025: The Great Convergence) That is not the ceiling. It is the starting point.

The operational infrastructure that allows a firm to serve 1000+ LPs across multiple vehicles with the same relationship quality it delivers to 400 does not get built overnight. But it does get built incrementally, and every fund cycle that a firm invests in it compounds the advantage. The LP relationship data captured in Fund III informs the re-up strategy for Fund IV. The co-invest preferences tracked across wealth-channel investors sharpen the pipeline for the next deal. The communication workflows built for one vehicle extend to the next without starting over.

That accumulation effect is the real opportunity. Not just operational efficiency, but institutional intelligence that makes each subsequent raise faster, each LP relationship more durable, and each new team member immediately effective from their first day.

The firms that see that clearly and start building now are not just preparing for a future state. They are creating an advantage that is available right now, with the LPs they are already managing, in the fund cycle they are already running.