Mergers & Acquisitions in the AI Sector – Navigating Complexities Beyond Legal Foundations

In Part 1, we laid the legal groundwork for AI-sector M&A. Now, we dive into what really drives successful deals: strategy. As AI becomes integral to business models, acquisitions go far beyond IP and talent. They demand a holistic approach—balancing regulatory uncertainty, ethical AI, ESG priorities, and integration challenges. This article explores how buyers can manage risk, uphold values, and secure long-term advantage in an AI-driven world.

Employment of key personnel

Many transactions are conditional upon the successful retention of top AI researchers and engineers. These individuals are frequently highly sought-after professionals and key employees who are instrumental to the continuous development and management of the AI assets, given that the bankability/ profitability of the assets is the main reason for the transaction. 

The prospective buyer will typically review the employment terms (e.g. the employment agreement, employment handbook, and company policies) of such key employees at the due diligence stage to ensure that these key employees can be successfully retained and integrated into the purchaser’s workforce. 

1. Share Purchase

For an outright share purchase, the key employee would likely remain an employee of the target company, and there is no transfer of employment to the buyer. In such cases, the due diligence would usually comprise a review of the key employee’s employment terms for compliance with local laws. If preferred, buyers may also try to align the key employee’s current employment terms with the buyer’s standard form (although the employment benefits would usually be offered on similar or on even better terms).

Assuming that the buyer wishes for the employee to enter into a fresh employment agreement on the buyer’s standard form, closing for an outright share purchase will be conditional on the employee executing (i) a mutual termination agreement of the existing employment agreement; and (ii) a fresh employment agreement based on the buyer’s standard form.

2. Asset Purchase

For an asset purchase, the key employee would usually be part of the purchased assets to be moved to the prospective buyer. In such cases, the employee’s existing employment agreement would need to be terminated, and the employee would need to enter into fresh employment terms with the buyer. This is given that a change of the employee’s employer on record is necessitated. 

Unlike a share purchase, the transfer of an employee’s employment to a new entity is governed by section 18A of the Employment Act 1968, which requires that the employee’s terms of employment remain the same unless the employee agrees to a variation of such terms. A transfer also does not constitute a break in employment for the transferred employee.

For employees who are on work passes (e.g. Employment Passes), an application would need to be filed with the Ministry of Manpower to transfer the employee from his/her existing employer to the buyer. Alternatively, the employee’s current work pass would need to be cancelled, and a fresh work pass applied for under the buyer. Depending on circumstances, the latter approach may be the faster approach (albeit more cumbersome to apply for fresh work passes).

Closing will therefore be conditional on the following:

1. the employee executing a mutual termination agreement of the existing employment agreement;
2. the employee executing a fresh employment agreement based on the buyer’s standard form; and
3. (if employee is on work pass) the successful application / transfer of the employee’s work pass to the buyer.

ESG characteristics 

The proliferation of AI and its associated infrastructure has significant environmental consequences. The data centres used to house AI servers are a source of electronic waste, in addition to being consumers of immense amounts of energy and water. Environmentally minded prospective buyers should carefully assess the energy and water management aspects of the target AI business. Prospective buyers may also pay close attention to the AI infrastructure’s access to green energy. 

Additionally, prospective buyers might be concerned with whether the target AI business has effectively implemented ethical AI principles, guidelines, and policies. To this end, the target AI assets should be assessed for algorithmic bias, responsible use and management of data, potential to address societal challenges, potential for harm, and mechanisms for transparency and accountability, among other aspects. As part of this process, the buyer should consider whether the target AI asset aligns with the buyer’s organisational values. 

Regulatory compliance

Those looking to acquire or invest in AI assets should be mindful of the laws applicable to such ventures. While a few jurisdictions have AI-specific legislation, such as the EU’s AI Act, many other jurisdictions, including Singapore, do not (yet) have comprehensive AI-specific legislation. The difficulties in legislating AI arise due to the rapid rate at which the AI space is evolving. 

As the AI space grows increasingly sophisticated, there is also a growing need for sensible legislation that remains appropriate and applicable in the long term. AI is rapidly revolutionising how people live and work in both subtle and overt ways, and holds great promise for creating economic opportunities. It is thus perhaps only a matter of time before AI-specific legislation is enacted in Singapore. We anticipate that regulatory certainty in the AI space would improve investor confidence in this sector as well. 

AI businesses and their investors should keep a watchful eye on regulatory developments applying to AI applications, as such developments could necessitate changes in their AI product and business strategies. An indication of potential areas for regulatory developments in the AI space might be gleaned from the policy papers published by the government. These include the National Artificial Intelligence Strategy 2.0, which outlines Singapore’s ambitions and strategies to realise the benefits of an “AI-enabled future”, and the Model AI Governance Framework for Generative AI, which outlines nine dimensions to enable end-users to use Generative AI confidently and safely, while continuing to facilitate innovation. As AI applications grow increasingly pervasive and normalised in personal life and work life, we expect to see the development of regulations aimed at setting up guardrails to usher the development of AI towards a productive and morally responsible trajectory.

Conclusion

Overall, a robust legal due diligence process on the target’s AI business or AI assets will go towards mitigating the risks in investing in this rapidly evolving sector.  For prospective buyers, it is imperative to scrutinise the target’s customer contracts, intellectual property rights, data management mechanisms, employment contracts of key personnel, and compliance track record with local regulations. The ESG qualities and ethical standing of target AI businesses are also important to consider, in light of urgent global carbon mitigation efforts and concerns surrounding the ethics of AI deployment. 

This article is produced by our Singapore office, Bird & Bird ATMD LLP. It does not constitute legal advice and is intended to provide general information only. Information in this article is accurate as of 28 November 2025.