Due diligence, one of the foundational aspects of private market investing, has long been conducted by hand, relying on human expertise. The manual review of documents like financial statements, legal contracts, intellectual property portfolios, and corporate records can be time consuming, annoying, and painstaking. The advancements of artificial intelligence (AI) can help automate the tedious tasks of due diligence in addition to enhancing the depth, speed, and scope of analysis. In this blog, learn more about AI for due diligence, specifically in VC investments and mergers and acquisitions.

AI for Due Diligence

At its core, AI due diligence involves leveraging technologies like machine learning (ML) and natural language processing (NLP) to automate and enhance traditional due diligence processes. Machine learning algorithms can be trained to identify patterns and anomalies across vast datasets. Natural language processing can help these systems parse, understand, and extract meaning from unstructured text within contracts, emails, and financial reports.

Benefits of AI for Due Diligence

One benefit of AI for due diligence is sheer scale and efficiency. Large data sets could take human teams weeks or months to analyze. AI systems can scan thousands of documents in minutes, flagging potential issues and highlighting important information that might have been missed otherwise in a manual review. According to the DealRoom, by automating due diligence, manual effort can be decreased by up to 80%, allowing human teams to focus more on strategic analysis than administrative tasks.

Use Cases in Venture Capital Investing

For venture capital investing, AI is being integrated across the entire investment lifecycle.

1. Deal Flow Automation and Startup Evaluation

One challenge in VC investing is sifting through a large amount of startups in order to identify opportunities, acting as the first filter towards making an investment. AI tools like Caena and Tracxn can help automate the sourcing process by filtering through vast amounts of data on startup performance, market trends, and news coverage to highlight companies that align with an investor’s specific thesis. This can help VCs allocate more time to engaging with deals rather than researching opportunities.

2. Enhanced Document Review and Risk Identification

Once a target investment opportunity has been identified, AI can help review legal documents, flagging non-standard clauses, potential liabilities, and regulatory issues. It can also help spot financial anomalies or inconsistencies in accounting practices that could indicate deeper problems or potential fraud.

3. Portfolio Monitoring and Management

The role of AI in due diligence can even extend post-investment. Tools can parse unstructured data from founder updates and financial reports, structuring it to provide real-time insights into portfolio company performance. This can help investors monitor key metrics, identify risks early, and make informed decisions about follow-on funding.

Use Cases in Mergers and Acquisitions

In mergers and acquisitions (M&A) where transaction sizes are typically significantly larger, AI can also be beneficial for due diligence efforts.

1. Information Requests

For buy-side teams, AI can perform analysis by scouring public sources like press releases, financial reports, legal filings, and media coverage to identify advancements, regulatory issues, or reputational concerns. This can help craft a more targeted information request list for acquirers.

2. Data Room Analysis

Once a data room has been established, AI can help parse through the information provided. It can detect gaps and check for missing documentation, generate concise summaries of lengthy documents, and flag compliance issues.

Limitations of AI for Due Diligence

Despite the benefits that AI can bring to the due diligence process, it is not an end-all-be-all solution. Blind reliance on AI systems can be dangerous and put the user at risk. The current state of AI is significantly better than when the first AI chatbots came out, but AI systems are still prone to confirmation bias, misinformation, and can “hallucinate”, or invent facts. They also produce outputs with limited information on how it came to those conclusions, which when left unchecked, can have significant errors and misjudgments.

Therefore, AI for due diligence should only be used in conjunction with human intervention, not as the sole source of due diligence efforts. AI may never be able to fully replace human expertise, strategic thinking, and negotiation skills. It can be beneficial in handling the high-volume, repetitive data crunching and initial flagging, but human experts should investigate the nuances, apply context, exercise judgement, and make the final strategic calls.

Final Thoughts

AI is a beneficial tool that can help enhance due diligence efforts but cannot and should not fully replace human efforts. With use cases in both venture capital investing and mergers and acquisitions, AI can help accelerate processes, uncover deeper insights, and automate tedious manual work, helping free up human efforts for deeper analysis and final decision making.

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The information presented here is for general informational purposes only and is not intended to be, nor should it be construed or used as, comprehensive offering documentation for any security, investment, tax or legal advice, a recommendation, or an offer to sell, or a solicitation of an offer to buy, an interest, directly or indirectly, in any company. Investing in both early-stage and later-stage companies carries a high degree of risk. A loss of an investor’s entire investment is possible, and no profit may be realized. Investors should be aware that these types of investments are illiquid and should anticipate holding until an exit occurs.

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