AI and ESG: Emerging forces shaping growth strategies and M&A

This challenge is compounded by increasing regulatory scrutiny, exemplified by the EU’s AI Act, which came into force on August 1, 2024, and will be fully effective by August 2, 2026. Although the UK has not enacted similar horizontal AI regulations, existing regulatory bodies such as the Financial Conduct Authority, Information Commissioner’s Office and Competition and Markets Authority are focusing on AI within their respective domains.

ESG factors, on the other hand, are becoming increasingly important as stakeholders demand more responsible and sustainable business practices. Investors, customers and regulators are increasingly focusing on ESG performance, and companies that fail to address these issues may face reputational risks and financial penalties. On the other hand, companies that excel in ESG can attract more investment, build stronger customer loyalty and achieve long-term sustainable growth. Again, regulatory intervention, particularly in terms of disclosure requirements, continues to increase alongside the rise of litigation for “greenwashing” in cases where the sustainability credentials of products or investments are believed to be overstated.

Investors in growth companies are increasingly focused on answering these two questions in their due diligence work. Specific questions on the use of AI (addressing intellectual property, data privacy and ethical concerns) are becoming standard in due diligence questionnaires, together with specific queries that address ESG as a standalone subject. This diligence work is then progressing into ongoing obligations on the part of businesses to develop and adhere to ESG frameworks and provide appropriate reporting, enabling financial investors to comply with their own investors’ requirements, and equally ensuring that corporate investors’ own ESG credentials are not damaged by the approach of the investee company.

AI, of course, is also being used in the diligence process itself, speeding up contract reviews and enabling dealmakers to get a view on a more comprehensive data set than would typically have been possible with traditional methods.

In both investment and M&A, the use of AI is becoming a key area for risk allocation through specific warranties, with businesses also pushing back in return and seeking to exclude liability for third-party large language models and the intellectual property issues arising from the use of third-party content to train artificial intelligence models or general artificial intellectual output.

AI and ESG are also, of course, key drivers for corporate activity in their own right. Corporates have been looking to reshape their portfolios of products and services to improve their ESG position (acquiring or investing in those that enhance their position while disposing of non-core businesses that are problematic from an ESG perspective), and many tech-enabled businesses have been created to fulfill ESG market needs.

AI has also given rise to a significant boom in corporate venture activity, given the size of the investment needed in development and computing resources to bring general-purpose AI models to market. M&A in the AI sector is also increasing as the technology and the ecosystem mature, posing unique legal and regulatory challenges, including potential anti-trust and/or national security reviews.

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