CHINA Trends and Developments Contributed by: Ting Liu, Fang Pan and Xiangru Chen, King & Wood Mallesons
employers to verify and sort out that they have imple - mented effective trade secret protection measures. Second, employers must conduct further investiga - tions to confirm that the scope, geographic area and duration of non-compete restrictions align with the employee’s actual access to confidential informa - tion. The Labor Dispute Interpretation (II) stipulates that if the agreed scope, geographic area or duration is incompatible with the trade secrets or intellectual property-related confidentiality matters known or accessed by the employee, the employee may claim the invalidity of the excessively broad provisions. This principle is directly applied in typical case No 4 released alongside the Labor Dispute Interpreta - tion (II). In this dispute, a pharmaceutical company sought to enforce a broad non-compete against a former chief technology officer who had accessed confidential information related to only two specific drugs from an affiliate company. The court ruled that the employee’s non-compete obligation should be limited to those two drugs. Furthermore, it held that a competitive relationship must be based on the substi - tutability of specific products or services, not merely operating in the same broad industry. This case under - scores that internal investigations must be prepared to defensibly justify the precise boundaries of the non- compete terms based on concrete evidence of the employee’s exposure. More challenging still, employ - ers must conduct more in-depth investigations and gather more direct evidence to prove that the services the employee provides or the work they perform for a competitor constitutes direct competition with their prior role at the original employer. In summary, the new legal framework requires employ - ers to strengthen internal investigations throughout the entire life cycle of non-compete management – from pre-implementation verification of trade secret protection systems to post-dispute confirmation of the appropriateness of non-compete terms – placing unprecedented demands on the rigour and compre - hensiveness of internal investigation processes. Summary The enactment of the New PRC Anti-Unfair Competi - tion Law and the Labor Dispute Interpretation (II) has significantly elevated employers’ internal investiga -
tion burdens. The New PRC Anti-Unfair Competition Law expands regulatory scope to cover cross-border bribery and data-related unfair practices, while intro - ducing compliance-focused enforcement tools like regulatory interviews and rectification orders. Mean - while, the Labor Dispute Interpretation (II) ties non- compete validity to trade secret protection, compel - ling employers to rigorously verify employees’ access to confidential information and justify non-compete terms with concrete evidence, thus demanding more comprehensive, evidence-based internal investigation frameworks. The Evolution and Impact of AI Tools on Internal Investigations Against the backdrop of 2025’s global AI revolution, generative artificial intelligence, large language mod - els and intelligent analytics tools have rapidly pen - etrated corporate governance. An increasing number of PRC employers are exploring AI-enabled internal investigations. While these tools are reshaping the methodologies for identifying employee violations and conducting internal investigations, they also present new challenges. The rise of AI in corporate internal investigations In 2025, an explosive growth in AI adoption occurred across industries, with internal investigation emerging as a key application scenario. This shift is driven by two core factors. • The growing complexity of misconduct – AI is indispensable for untangling complex and sophis - ticated misconduct. Modern violations are rarely simple one-off acts. Instead, they often involve intricate schemes spanning communication chan - nels, financial systems and operational data. For example, potential collusion between a procure - ment officer and a vendor might leave traces in encrypted messages, vaguely worded emails and altered transaction records. It is difficult for employers to connect these scattered clues via tra - ditional manual search and sampling methods. But AI provides significant assistance through natural language processing and network analysis. More importantly, it can simultaneously handle millions of documents, identify hidden relationships and map entire communication and transaction networks.
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