AI in Private Markets | Considerations for Small- and Mid-Sized Managers

By Mads Døssing, Platform Strategist at The Good Guys Company | June 06, 2025

EXECUTIVE SUMMARY

Profitability in Traditional Asset Management has declined, leading to a greater focus on Private

Markets, which has led to intensified competition in a fundraising environment that is currently

under stress from macroeconomic headwinds. So far, the bigger managers have been able to

continue their growth, but the small- and mid-sized firms have begun to face challenges. This

white paper explores how these managers can leverage artificial intelligence (AI) to enhance

efficiency and gain a competitive edge.

The application of AI can help all types of Private Market Asset Managers. However, this paper

focuses on the application for small and mid-sized firms as these are believed to be able to benefit

the most by limiting the resource and scale gap they currently face compared to the bigger firms.

This white paper will highlight areas AI can help limit this gap and increase competitiveness of

small- and mid-sized managers, particularly:

Fundraising can benefit from AI by optimizing communication through detailed meeting

preparation and actionable follow-ups, fostering more meaningful relationships.

AI offers the potential to increase the efficiency of RFP and RFI processes, leading to a first draft

substantially faster than what is currently possible.

In research, AI can accelerate the analysis of both quantitative and qualitative data, facilitating

more informed decision-making and improving the creation of compelling narratives for

investors.

AI can streamline the investment process by automating deal pre-screening, data extraction

from virtual data rooms (VDRs), and the creation of investment committee (IC) memos,

ultimately speeding up transaction execution.

This paper serves as a guide for small- and mid-sized private equity managers seeking to leverage

AI to enhance efficiency, improve decision-making, and ultimately, thrive in an evolving market.

INCREASED COMPETITION IN AN ALREADY STRESSED FUNDRAISING ENVIRONMENT

From 2007 until 2022, profitability in traditional asset management halved from 15 bps to

approximately 8 bps. This decreased profitability of traditional assets over the last two decades

has led to an increased focus on Private Markets as a way for asset managers to rejuvenate their

revenue side. However, this move by traditional asset managers has led to a substantial increase

in competition as both alternative and traditional managers conglomerate in the Private Markets

space.1 This increased competition comes at a time when the global fundraising environment is

increasingly tough. Higher interest rates and economic uncertainty has driven an increased

spread between buyers and sellers in the Private Market space, leading to a tougher exit

environment where managers can choose to either hold their positions or exit at the cost of

returns.

2024 marked the third consecutive year where capital raised as well as the number of fund

closings decreased. During these years, the larger firms have managed to maintain momentum in

fundraising while small- and mid-sized firms have been struggling.2 The outlook going into 2025

was originally expected to be an easing up of the exit environment, which in turn could stimulate

the fundraising environment, but so far this has not materialized due to geopolitical uncertainty.

This means managers need to themselves find a way to entrench their market positions and

position themselves for growth.

From what we have seen working with actors in the industry, as well as according to Bain (2024),

the increased competition in the Private Markets space will lead to the long-term winners going in

one of two directions:

1. Build a specialized alpha-generating firm that focus on a single asset class (e.g. Private Debt)

and build out a strong offering in this space with a tailored operating model.

2. Build a scale platform that can diversify across Private Markets (e.g. Private Equity, Real Estate,

Private Debt etc.) and build out an operating model that can adjust and adapt to increasing

complexity and different requirements.

The simplified core of Private Markets

As the fundraising environment continues to be under pressure from macroeconomic headwinds and geopolitical uncertainties, Private Market managers need to increase their strength in core business functions (raising and deploying capital).

In a simplified manner, one can say that by increasing the ability to consistently raise capital and

deploy raised capital, a manager can grow their existing funds while maintaining the fund’s top

performance. Thereby, strengthening these parts of the business is a priority, no matter if you seek

to build a specialized alpha-generating firm or a scale platform.

Raising capital: Fundraising

Raising capital for new vintages of fund families as well as initiating new mandates can be

conglomerated under the umbrella of the fundraising function. In the fundraising universe

managers can choose to prioritize different types of Limited Partners (LPs) such as institutional

clients (e.g. pension funds and sophisticated single-family offices), where issuances of RFPs and

RFIs are common practice or private wealth clients (e.g. multi-family offices and UHNW), which

tend to be more relationship-driven. Strengthening your fundraising capabilities can be done

either by hiring additional staff or augmenting the existing staff with tools to make their work more

efficient and higher quality.

Deploying capital: Investment Management

Deploying capital for both funds and mandates can be conglomerated under the umbrella of the

investment management function. The investment management function covers research,

origination as well as due diligence, execution and monitoring of investments. A key part of

building a scalable Private Markets manager is ensuring you have strong origination capabilities

(extensive pipeline of top opportunities) as well as the transaction engine to execute on the

opportunities in a timely manner. You can build a strong origination network by hiring senior

professionals and a strong transaction engine either by having a substantial bench of more junior

staff or augmenting existing staff with tools to make their work more efficient and higher quality.

THE NEED FOR EFFICIENCY IN CORE BUSINESS FUNCTIONS

Artificial Intelligence as a tool for increased efficiency

Based on the high-level descriptions in the previous sections, it is possible to separate the

fundraising and investment management functions into a total of 4 capability focus areas.

Shared among these areas is the need to process large amounts of historical data, whether it be

previous meeting notes, previous RFP/RFI responses as well as internal unstructured data,

quantitative and qualitative research data or unstructured data from a Virtual Data Room (VDR).

This is where Artificial Intelligence (AI) comes into play. The concept of AI is not a new invention. It

has however, seen new business applications emerge after the emergence of Large Language

Models (LLMs) and more recently, AI agents and Retrieval-Augmented Generation (RAG).

The ability to process and interact with large swathes of both quantitative and qualitative data

creates the opportunity to augment existing human teams with a data analysis engine that

ongoingly improves. This presents an interesting opportunity for Private Market managers, who

operate in a space, where human employees are expensive to employ and you want to extract the

maximum amount of value from each employee.

The application of AI can help all types of Private Market Asset Managers. However, this paper

focuses on the application for small and mid-sized firms as these are believed to be able to benefit

the most due to the resource and scale gap they currently have compared to the bigger firms and

the ability for AI to reduce this resource and scale gap.

INCREASING EFFICIENCY THROUGH THE APPLICATION OF ARTIFICIAL INTELLIGENCE

Applying Artificial Intelligence in fundraising and investment management functions

When looking at fundraising and investment management functions, the 4 working areas covered

so far in the paper is 1) relationship management & fundraising, 2) RFP / RFI processes, 3)

research & origination and 4) investment process. Based on our discussions with managers and

emerging as well as leading service and tech providers, we have highlighted the AI potential as well

as the barriers of adoption.

What is meant here is that the potential for AI to increase efficiency in e.g. relationship

management & fundraising is deemed high with low barriers of adoption. There are already

multiple providers with adoptable solutions in this space or even managers experimenting with

own applications in case of sensitive information. The following sections will go into greater detail

on each of these working areas to describe concrete use cases and explain the potential as well as

the barriers of adoption.

EXAMPLE AI USE CASES IN THE PRIVATE MARKETS INDUSTRY

Relationship management & fundraising

Relationship management and fundraising in Asset Management in general, but especially in

Alternative Investments, is a constant roadshow game, where business development and senior

investment professionals are almost constantly on the road visiting prospects and maintaining

relations to existing LPs.

CRM systems have existed for a long time and today it is normal for fundraisers to have constant

access to their CRM on both their laptop and smartphone. The CRM system today is normally

integrated with your emails, and you can get notifications and updates to make sure tasks and

reach-outs never fall between the cracks. However, with the constant meetings with different

people as well as the many different emails that are sent out on a daily basis, it can be difficult to

stay on top of it all and not mix different interactions together. This is an interesting use case for

AI to assist fundraisers in preparing for meetings by analyzing previous touchpoints as well as

draft emails. Many CRM systems have begun to roll out AI agents that function almost as a

personal assistant to the fundraisers, which is a promising way of providing high-touch solutions

to LPs in an efficient and more scalable way than previously thought possible.

Conclusion:

The benefits here are focused on enabling stronger relationships and better business

outcomes as fundraisers would be better prepared for meetings and would have more

accurate responses with faster response times leading to more effective and efficient building

of relationships

This use case has a privacy / confidentiality concern that has to be taken into consideration,

but this can be solved either by working with specific vendors or hosting your own application

EXAMPLE AI USE CASES IN THE PRIVATE MARKETS INDUSTRY

RFP & RFI Processes

Especially asset managers dealing with a more institutional LP segment will understand the pain

of RFIs and RFPs in today's market environment. The tricky part about institutional RFIs and

RFPs is that they vary substantially in content asks from institution to institution (even though

many questions will be repeats). This also means automating workflows previously have been a

challenge for managers.

The writing up of Due Diligence Questionnaires (DDQs) as well as the substantial amount of data

that has to be gathered from all parts of the business to respond to an RFP is a herculean task

for many managers.

Additionally, this area is an often-ignored use case compared to the more “attractive” AI topics

like deal screening and financial modelling automation. However, this is one of the topics where

substantial human resources could be freed up across the entire organization (front-to-back) by

implementing AI solutions to efficiently gather inputs and prepare initial draft response packs to

RFIs and RFPs.

Conclusion:

AI can significantly reduce the time it takes to send a first draft of an RFP/RFI response for

internal review

This solves the initial hurdle of gathering data as well as overcoming the “blank page” or copy-

pasting from previous responses

EXAMPLE AI USE CASES IN THE PRIVATE MARKETS INDUSTRY

Research & originiation

Research is a core part of the Private Markets business. Not only is it used for commercial due

diligence purposes, but it is also used as a powerful marketing tool and as a way to stay relevant

in an increasingly content-driven world, where managers constantly compete for the eyeballs

and attention of LPs.

The entire research process is built around analyzing large amounts of both quantitative and

qualitative data such as traditional and alternative market data, news articles etc. The research

process is usually used either as part of a commercial due diligence process and can yield a call-

to-action for the pursuit of an investment opportunity (internal impact) or for thought leadership

purposes (external impact).

Today, these workflows are usually handled by human employees who perform the analysis

(sometimes augmented with statistical tools and code scripts) and draft the research papers

that are then either distributed internally to the investment teams or to existing clients or shared

on insights pages for marketing purposes.

Much like the investment process use cases, the research workflows rely heavily on a multitude

of data sources that have to be analyzed and turned into actionable content. AI solutions today

can be used to increase the efficiency of the data gathering and analysis work compared to

historical solutions like Python scripts, VBA macros, and close study of white papers and

articles. We are not talking about replacing employees but making the employees more efficient

and increasing actionable output.

Conclusion:

AI can be used to drive higher quality commercial due diligence as well as thought leadership

due to the increased quantity of both quantitative and qualitative data that can be processed

This can in turn lead to either better decision making when pursuing investment opportunities

as well as create more engaging content for LPs

EXAMPLE AI USE CASES IN THE PRIVATE MARKETS INDUSTRY

Investment process

The Private Market investment process is dependent on a pre-screening process based on a

number of high-level investment criteria. Any opportunity that passes this initial screening is

usually funnelled into a due diligence phase, which relies on substantial amounts of human

effort as junior staff will fetch and structure data from the VDR and plug it into their financial

model templates to calculate the attractiveness of said opportunity. If an opportunity shows

promise, it might be shown at the investment committee meetings multiple times. Each time

requires a memo to be drafted, another human-driven process.

Today, these processes from screening to IC are largely dependent on deal team members

pulling long hours to perform manual workflows that in themselves do not add much value. And

in certain cases (like an opportunity with a short transaction window), the ways of working today

forces employees to “burn midnight oil” as a way of getting the job done. Not because of the

value-add but because of the lack of proper tools to execute on transactions fast.

In the increasingly competitive Private Market industry, having an efficient transaction engine is

key, and to achieve this, multiple buy-side houses are already exploring AI technologies to

augment their teams and sometimes even automate certain workflows in the investment

process. Everything from automatic pre-screening of deals to fetching and structuring data from

VDRs to drafting of IC memos, the applications for AI in the investment process are many. This is

one of the concrete opportunities for small and mid-sized firms to close the efficiency gap to the

larger managers. It is also one of the opportunities, where we have seen examples (especially in

the US) of managers adopting AI to build scalable transaction engines.

Conclusion:

AI can significantly reduce the effort of deal team members across the entire investment

lifecycle from pre-screening to VDR data extraction to due diligence and IC approval

The efficiency gain can be used to scale the transaction engine and in turn enable the raising

of bigger funds while retaining key talent

TANGIBLE EXAMPLE OF AN AI PROVIDER USED BY PRIVATE MARKETS FIRMS

Hebbia AI

Hebbia AI is an American software provider that has built a Retrieval-augmented Generation

(RAG) AI model designed for the buy-side industry.

Many Private Market firms as well as sell-side M&A firms (especially in the US) have begun to

implement Hebbia AI as a core part of their pre-screening and diligence workflows. Many firms

have reported substantial increases in screening and diligence efficiency, leading to a faster

diligence process as well as increased capacity among deal team members.

TGGC is not receiving any compensation for highlighting this provider.

Hebbia is only one of many providers that can be applied to different parts of the operating model,

whether it be in the fundraising function, the investment management and research function, or

other functions like operations, fund admin etc.

If you are interested in learning more about how to define a long-term strategy, future-proof your

operating model or implement AI tools into existing AI use cases, reach out to us at The Good Guys

Company (TGGC). We provide you with independent, hands-on buy-side experience as well as

exposure to a broad network of leading and emerging tech and service providers.

#AI #OperatingModel #PrivateMarkets