The Impact of AI on Private Equity and Secondary Markets

The private secondary market has seen explosive growth in recent years. Investment bank Jefferies Financial Group found secondary transactions totaled around $162 billion in 2024 — a 45% increase from the previous year. 

Platforms like Augment* are helping lead the surge. The innovative marketplace allows investors to buy and sell existing stakes in private companies or funds before a traditional exit event, such as an IPO or acquisition. This means individuals and smaller institutions like pensions or endowments can access private equity funds or venture capitalist portfolios; traditionally, they might be excluded due to high capital requirements.

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AI systems employ highly advanced algorithms that quickly process vast amounts of historical and real-time data. This can help investors improve their decision making in secondary market transactions.

AI systems can interpret structured data — think financial statements or changes in stock prices. But these systems can also process unstructured data, such as news articles or social media posts. The result is a more nuanced, holistic understanding of the current market.

While using AI isn’t the same as having a crystal ball, the technology can help predict market trends, gauge investor sentiment, or manage risk.

Investors might also use AI to divvy up investments into different asset classes, tailoring the portfolio to their goals, risk level, and market conditions. And they can continue using AI to monitor the portfolio, making adjustments as the market changes.

Several specific AI technologies are contributing to its rise in financial markets.

• Machine Learning (ML): These algorithms consider historical data to predict future stock prices and optimize portfolios.
• Natural Language Processing (NLP): This type of AI analyzes written language, from news and earning reports to speeches and social media posts. NLP systems can provide investors with insight into management’s thoughts and emotions — sometimes before they’re reflected in asset prices.
• ‍Blockchain & Smart Contracts: Smart contracts are automatic agreements that are stored on a blockchain, or a digital ledger that stores transactions. Together, blockchain and smart contracts can create more efficient and secure transactions in the secondary market — particularly when it comes to digital assets, like cryptocurrency or non-fungible tokens.

AI has brought a number of benefits to the financial sector. Quick, automated transactions have increased efficiency. Algorithms have the ability to process multiple large data sets at the same time, yielding more accurate pricing. This is especially useful in the sometimes-murky secondary market, even as platforms like Augment improve transparency by displaying real-time pricing for private companies. 

But the rise of AI in secondary markets presents its own set of challenges, too. Regulatory bodies including the Securities and Exchange Commission (SEC) have warned investors about scammers who might take advantage of AI’s complexity and growing popularity. AI-generated information can be inaccurate, biased, incomplete, or misleading, they cautioned. These shortcomings could evolve as the technology improves. 

AI is transforming secondary markets. Transactions are generally faster, safer, and more efficient.

For decades, private equity firms have relied on two main levers to generate returns: financial engineering and operational improvements. But now, a third lever is emerging — AI-driven intelligence.

AI is no longer just a back-office tool. It’s becoming a core part of the investment strategy, helping firms analyze data faster, identify hidden opportunities, and make more informed decisions throughout the entire investment lifecycle.

In secondary markets, this matters even more. GPs and LPs are dealing with complex fund structures, timing pressures, and liquidity events. AI can help investors assess a portfolio’s underlying value, identify market dislocations, and make decisions based on predictive analytics — not just historical performance.

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One powerful use case for AI is in deal sourcing. Instead of relying solely on human networks or slow-moving databases, AI can scan massive volumes of market, performance, and sentiment data to identify undervalued or under-discovered assets.

For secondary buyers, this means faster access to relevant opportunities — especially in GP-led processes or tail-end fund transactions where speed and insight are critical.

AI also enhances valuation modeling. Traditional models often rely on static assumptions. But AI-driven scenario tools can adjust valuations in real time based on shifting inputs like macroeconomic indicators, portfolio company news, or sector trends. This dynamic approach helps buyers and sellers in secondaries better align on pricing — even in volatile markets.

Due diligence is one of the biggest bottlenecks in secondary transactions. Legal documents, fund performance records, and investor agreements all need to be reviewed — a time-consuming and expensive process.

AI can help speed that up significantly. Tools powered by Natural Language Processing (NLP) can automatically analyze fund LPAs, financial disclosures, and governance documents. They can flag potential risks, highlight unusual clauses, or even detect early signs of financial distress.

This kind of automation not only improves efficiency — it raises the quality and consistency of due diligence. And for platforms like Augment, which aim to make private market access more seamless, this is a natural extension of the value AI brings: making smarter investing easier at scale.

As AI matures, it’s not just improving how individual deals are done — it’s reshaping how entire portfolios are built and managed. Secondary market participants who adopt AI-driven tools may be better positioned to move faster, price more accurately, and navigate risk with greater clarity.

In a space where timing, transparency, and trust matter, AI isn’t just a tech upgrade — it's becoming a strategic advantage.

Technologies like ML and NLP rapidly analyze huge amounts of data, empowering investors to make better-informed market predictions and stock purchases.

AI will continue to reshape the landscape of financial markets, underscoring the need for regulation to keep up with the rapidly developing technology.

As interest grows in private secondaries, investors are also looking for smarter tools and rankings to help guide their decisions. Resources like a curated pre-IPO stock list can provide added confidence and clarity in identifying growing private companies to watch.