Use this button to switch between dark and light mode.

Copyright © 2024 LexisNexis and/or its Licensors.

Artificial Intelligence Investment: Risks, Due Diligence, and Mitigation Strategies

December 08, 2023 (7 min read)

By: Shabbi S. Khan, Natasha Allen, David W. Kantaros, Chanley T. Howell, Graham P. MacEwan, and Avi B. Ginsberg, FOLEY & LARDNER LLP


Given the increasing prevalence and application of AI technology in many industries, purchasers of and investors in businesses across industries and sectors must be prepared to address AI-related issues, including the investigation, evaluation, and assessment of technology companies that own, provide, and offer AI solutions, as well as companies that use or incorporate AI technologies in their businesses, services, and operations.

The field of AI has witnessed exponential growth over the past decade, capturing the attention of investors seeking opportunities in this transformative technology. This article explores the AI investment landscape, including trends in AI funding and M&A, the key players in the market, benefits and risks associated with AI investments, the role of data in AI systems, the legal and regulatory framework surrounding AI, the importance of due diligence with AI investments, and the role and impact the purchase agreement has with respect to transactions in this field.

The AI Market Landscape

The investment landscape surrounding AI is experiencing remarkable growth and presents numerous opportunities for investors. Over the past decade, AI funding has accounted for approximately 10% of global venture capital dollars, signaling the immense interest and potential returns associated with investing in this transformative technology. Large tech-focused companies are actively seeking opportunities to acquire AI companies to enhance their capabilities and expand their market presence. Additionally, venture capital and private equity firms have recognized the potential of AI and have actively invested in AI-focused start-ups to capitalize on their growth potential.

As with all M&A transactions, there are significant benefits and risks to consummating a transaction involving an AI company, but the dynamic, revolutionary nature of the AI field presents unique cost-benefit and risk considerations for AI-related investments. Benefits associated with AI investments include the possibility of earning high returns; disrupting various industries including healthcare, finance, manufacturing, and transportation; and creating competitive advantages. Risks associated with AI investments include inherent volatility and rapidly changing market conditions; technological challenges (including technical glitches, algorithmic biases, risk of reputational harm, data privacy concerns, and cybersecurity threats); regulatory and ethical concerns; and viability and longevity issues.

For practical guidance on the role of data in AI systems and importance of data quality, Key AI-related due diligence activities, and the unique characteristics of AI companies in terms of assets and value, subscribers may follow this link.

Not yet a Practical Guidance subscriber? Sign up for a free trial of Practical Guidance to read this complete article.

Sell-Side Considerations

AI companies seeking investment and/or exit opportunities (and their advisors) would do well to consider the opportunities, risks, and prescribed actions detailed herein. By considering and anticipating how the purchaser intends to operate, an AI company can better position itself for post-closing processes and changes. The following questions can serve as a starting point for sellers in the AI industry to consider as an investor begins to conduct due diligence of their companies.

Future Trends and Predictions in AI Acquisitions

The field of AI investments is continuously evolving, and staying abreast of future trends and predictions is crucial for successful navigation of the AI investment landscape. Some key future trends and predictions in AI acquisitions include:

  • Vertical-specific AI solutions. As AI technologies mature, there may be a shift toward vertical-specific AI solutions tailored to meet the unique needs of specific industries or sectors. Investors should assess the target company’s alignment with industry-specific requirements and evaluate its potential to capture market share in targeted verticals.
  • Increased cross-industry collaborations. AI technologies have the potential to disrupt multiple industries. In the future, we can expect increased cross-industry collaborations, where
    AI companies and traditional industry players form strategic partnerships or engage in acquisitions to leverage AI capabilities. Investors should monitor these collaborations and evaluate their potential for creating synergies and unlocking new market opportunities.
  • Regulatory and policy developments. The regulatory and
    policy landscape surrounding AI technologies will continue to evolve. Investors should closely follow regulatory developments, anticipate potential regulatory changes, and assess the target company’s ability to adapt to evolving legal and compliance requirements. Compliance with regulations and industry standards will be crucial for long-term success in the AI investment space.

Further considerations in the AI investment landscape include the impact of rapid growth on the long-term health and stability of AI companies, the role of talent acquisition and associated risks in AI M&A, legal and ethical considerations, and future trends and predictions. By taking these considerations into account, investors can navigate the evolving AI investment landscape more effectively and make informed decisions that maximize the potential of their AI investments. 

Subscribers may view the full article in Practical Guidance.

Not yet a Practical Guidance subscriber? Sign up for a free trial of Practical Guidance to read this complete article.

Shabbi S. Khan is a partner and intellectual property lawyer with Foley & Lardner LLP. His practice focuses on patent portfolio counseling and management, preparation and prosecution of patent applications, patent infringement analysis, patent validity analysis, and intellectual property due diligence primarily in the fields of artificial intelligence and machine learning, computer software including cloud and SaaS-based technologies, medical devices, digital therapeutics, and artificial intelligence in health care. He is a member of the Electronics Practice Group and the firm’s Innovative Tech Sector.

Natasha Allen is a strategic advisor, supporting companies in all stages of growth in complex decision making across a broad range of corporate matters. She is a partner with the firm, serving as Co-Chair for Artificial Intelligence within the Innovative Technology sector, Co-Chair of the Venture Capital Committee, and is a member of the Venture Capital, M&A, and Transactions Practices. She also serves as Pro Bono chair for the firm’s Silicon Valley office.

David W. Kantaros serves as Co-Chair for Artificial Intelligence within the firm’s Innovative Technology sector and is a member of the Private Equity & Venture Capital and Transactional & Securities Practices. He represents venture capital and private equity funds as well as publicly and privately held corporations in the emerging technology and life science industries.

Chanley T. Howell is a partner and intellectual property lawyer with Foley & Lardner LLP, where his practice focuses on a broad range of technology law matters. He is a member of the firm’s Technology Transactions, Cybersecurity, and Privacy Practice and the Sports, Health Care, and Automotive Industry Teams.

Graham MacEwan is an associate in the Business Law Department with Foley & Lardner LLP. Graham is based in the Boston office where he is a member of the Transactions Practice Group.

Avi B. Ginsberg is a cybersecurity and data privacy attorney with Foley & Lardner LLP based in Boston. He has substantial industry experience in cybersecurity and international business transactions. He regularly helps corporate clients respond to ransomware attacks and data breaches, evaluate privacy risk and compliance strategies for complex data sets, and develop kids’ privacy approaches for online games and metaverse experiences.

Related Content

For an overview of the M&A due diligence process, as well as where to find practice notes, templates, and checklists relating to this topic in Practical Guidance, see


For an overview of current practical guidance on generative artificial intelligence (AI), ChatGPT, and similar tools, see


For a discussion of the primary and emerging legal issues relating to the acquisition, development, and exploitation of AI, see


For an analysis of the key issues to consider when companies transfer intellectual property assets in a strategic transaction such as a merger or acquisition, see


For practical guidance on the process of uncovering and understanding information about the status, value, and risks associated with the transfer of IP assets as part of a business deal, see


For a template that may be used when reviewing a target company’s material IP license agreements as part of a due diligence investigation conducted in the course of a merger or acquisition, see


For charts to be used by legal counsel to track and document IP assets during due diligence review, see


For a form request list to be used in an IP due diligence investigation during an acquisition, see


For a checklist that identifies key issues for performing a software and IT due diligence investigation of a seller, including a review of cloud computing and open source software considerations, see