Brightwave's LinkedIn newsletter The Next Wave is live! In this first installment, we explore the applications of AI to middle-market private equity due diligence workflows. Subscribe today to stay up to date on future editions, each posting here on the website one week after it drops on LinkedIn.

Introducing Brightwave's Investment Research Spotlight Series

In the last few months, there has been a marked shift in the conversations around AI in investment research. Among our discussions with customers, prospects and conference attendees, one theme has consistently surfaced: “How can we use AI in a real way in our daily workflows?”

To answer this question in a meaningful way, we are launching our Spotlight Series: several installments focused on the real-world applications of AI technology in investment research and due diligence workflows. We’re kicking it off with a focus on a segment that has felt both contracting competitive pressures and increased deal flow in recent years: middle-market private equity.

The Middle-Market PE Challenge: Doing More with Less in 2025

Middle-market PE firms typically operate with lean deal teams and limited internal research support, but are expected to still cover a broad universe of potential targets. Unlike mega-cap buyouts that attract extensive sell-side research and disclosures, middle-market targets often have limited public information due to their size and private status. This leads to several constraints for investment teams:

• Coverage Gaps: Analysts must manually piece together data from disparate sources (industry reports, niche databases, news articles, etc.), which is time-consuming and can provide fragmented, incomplete views. Many attractive companies are overlooked simply because information is hard to find.
• Speed of Execution: In auction processes or proprietary deals, speed is vital. Small teams juggling multiple deals can struggle to quickly analyze each opportunity. Delays in diligence or market research can mean lost deals to faster-moving competitors.
• Fragmented Data: Information on mid-sized companies is often unstructured (PDF filings, websites, transcripts) or spread across multiple databases. Processing each document and integrating these into a coherent picture by hand is a manual challenge that requires both human brainpower and more staffing.
• Resource Constraints: For firms without dedicated research teams, hiring specialist researchers or dedicating weeks to map out a niche market is often impractical. Middle-market firms need to do “more with less”, scaling sourcing efforts without significantly increasing cost.

Accelerating Investment Due Diligence: How AI Creates Competitive Advantage

For many investment analysts, a large and critical portion of their job is to handle the due diligence process for potential targets. Diligence often involves sifting through hundreds (if not thousands) of pages of financial statements, customer contracts, legal documents, and industry reports to identify risks and verify information. For a lean team, this manual document processing can consume the majority of their working hours, creating bottlenecks in deal flow. AI research tools can drastically improve this process in several ways:

• Rapid Document Processing to Generate Investment Outputs: Purpose-built AI platforms can analyze thousands of pages in minutes, extracting key data points and flagging important details that might take an analyst days or even weeks. From a company’s confidential information memorandum (CIM), AI platforms can instantly identify key financial metrics, growth rates, customer concentration, and even subtle cues in footnotes. This allows the deal team to focus on interpretation rather than rote data extraction.
• Deeper Insight & Error Reduction: By cross-referencing data across multiple documents, AI platforms can spot inconsistencies or red flags that a rushed human read might miss. Crucially, not all AI is created equal, and choosing a platform that thoroughly reads every page of every document is important for maximizing accuracy. As LLMs progress in their semantic ability, AI’s ability to catch small but critical details will outpace human brainpower and become a real competitive edge.

Middle-market PE funds are often fighting battles on multiple fronts: not only are they competing with other firms in the space, they also contend with large-cap PE shops that have infinitely more resources in the diligence process. To conduct the same level of quality diligence, AI platforms can be an important tool in the toolbox, allowing teams to boost both coverage and confidence in the investment decision.

Developing Deep Industry Expertise: Mapping Niche Markets with AI

Middle-market investors frequently target niche industries or fragmented markets, where the ability to map out the landscape confers a huge advantage. AI research platforms are particularly valuable in creating and updating these market maps at both scale and speed, allowing teams to stay up-to-date on the competitive intelligence that might give them an edge in the next deal process.

• Comprehensive Market Mapping: In a fragmented industry, dozens of small private companies might compete, and data on them can be scarce. AI platforms can help triage the publicly available information by processing charts, tables and other long documents to generate a report that immediately summarizes the most important factors. Templates with these key sections can produce comparable reports across multiple players in the industry, making it easy for teams to generate clear market maps centered on the most important factor.
• Identifying Competitors and Ecosystem Relationships: AI-driven platforms can not only produce accurate information on companies, but also reveal relationships and competitive linkages that can be crucial later on for an investment thesis. For example, if two companies are direct competitors or if one is a supplier to another, external forces like tariffs or regulation that affect one can be noted to also affect the other. For a middle-market investor performing diligence on a potential acquisition, these types of insights are gold and inform both valuation and post-acquisition strategy.
• Continuous Competitive Intelligence: One of the biggest challenges (and shortcomings) of a market mapping exercise is that the market doesn’t stand still after an initial map is drawn. With preset reports that include already-identified key factors, AI platforms can flag a new entrant, a competitor launching a product, or shifts in customer sentiment that might change the thesis or takeaway. This allows the market map to become a living asset, which in turn helps middle-market firms remain proactive in defending and growing their portfolio companies post-investment. This ability can be game-changing for lean teams competing with large-cap firms that have historically had much bigger portfolio support teams.

AI for Middle-Market Private Equity: Why 2025 Is The Tipping Point

Middle-market private equity investment teams occupy a unique position within the investment ecosystem: while they may lack the resources and support that exist within much larger PE firms, their ability to experiment and flexibility with new tools can level the playing field. Almost as importantly, the mandate to do so can feel more urgent: scaling resources, gaining a competitive edge in the diligence process, and effectively monitoring portfolio companies can have a higher ROI than for larger funds.

Adopting and effectively managing an AI platform amplifies the effectiveness of a human team. For many firms, processing the sheer volume of opportunities and information contained within a potential acquisition presents clear manual challenges. AI platforms can directly address these issues by automating labor-intensive tasks and synthesizing data. Recent surveys show that adoption of AI in private equity has surged — over 80% of PE/VC firms were using AI by late 2024, up from 47% a year prior — underscoring that AI has shifted from a novelty to a critical tool for competitive strategy.

For middle-market private equity, the promise of AI is to serve as a force-multiplier for small teams:

• Handling routine research work
• Scanning vast collections of documents for known investment signals
• Enabling faster, more informed decisions

As larger funds continue to develop custom AI models in-house, middle-market PE has a unique window of opportunity to leverage more precise third-party tools. Early adopters are likely to enjoy outsized benefits in sourcing proprietary deals and executing better investments, augmenting human expertise with machine intelligence.

For ambitious middle-market PE firms, embracing AI in investment research is no longer optional — it’s quickly becoming essential to staying ahead of the curve in 2025 and beyond.