Chinese courts have ruled that AI adoption alone does not justify dismissing workers. Finnish employers have far broader discretion — but the legal risk emerges earlier than many boards realize.
When a Hangzhou tech company tried to replace its AI quality-assurance supervisor with a large language model — offering him a 40% pay cut to a different role, then firing him when he refused — China's courts ruled the dismissal illegal. The Hangzhou Intermediate People's Court decision, published in late April as part of a set of typical AI-related labor cases, established a principle now drawing international attention: AI adoption alone does not justify firing workers.
Finnish employers operate under very different rules, but the underlying question Chinese courts raised is one Finnish boards will face soon, if they aren't facing it already: at what point does deploying AI shift from being a productivity-driven investment to a decision that results in a reduction of the workforce?
"There is no black and white answer to that," says Sanna Honkinen, head of employment practice at Hannes Snellman. And that ambiguity, she warns, is where the legal risk lives.
The Chinese precedent
The Hangzhou ruling, upheld on appeal on April 28, centered on a quality assurance supervisor identified only as Zhou. Hired in 2022 at a monthly salary of 25,000 yuan (USD3,676) to oversee his employer's AI output, Zhou was told in 2025 that the company intended to replace his role with a large language model. He was offered a different position at 15,000 yuan — a 40% pay cut — and dismissed when he refused.
The Intermediate People's Court ruled that AI-driven job replacement does not constitute a "major change in objective circumstances" under China's Labor Contract Law, the legal threshold normally required to justify redundancy-based termination. The court also found the reassignment offer unreasonable on its own terms. The ruling built on a December 2024 Beijing arbitration decision involving a map data worker dismissed after AI took over his role, reaching the same conclusion: adopting AI is a business choice, not an unforeseen event, and its costs cannot be shifted unilaterally onto employees.
The cases have drawn international legal attention because they cut against the assumption — common in at-will jurisdictions like the United States — that AI-driven restructuring is a straightforward business decision. Finland's framework sits between these poles.
The Finnish legal reality
Finnish employers have considerably more discretion than their Chinese counterparts to restructure around AI.
"In Finland, the employer has the right to decide what business activities are operated and how business and roles within the company are organized," Honkinen says.
Roles can be terminated for financial, production-related, or reorganization reasons linked to technological development, including AI adoption, provided the amount of work has genuinely declined. But that discretion comes with procedural strings attached.
Under Finland's Co-operation Act, employers with at least 50 employees must begin change negotiations if planned measures could materially affect employees' work tasks, working methods, working hours, or lead to layoffs or dismissals on financial or production-related grounds. Employers with 20 to 49 employees face similar obligations in cases involving broader personnel reductions.
Employers must also assess whether employees can be reassigned or retrained before dismissals take place. "The employer has to consider whether the employee can be placed into another role or trained for another role," Honkinen says.
That retraining obligation is narrower than it sounds. Companies do not have to educate employees into entirely new professions — the expectation is shorter-term training into adjacent roles where employees already possess the core capabilities needed.
The timing trap
The harder question for Finnish boards is not whether they can reduce roles, but when AI adoption becomes serious enough to trigger the formal negotiation process.
That is Honkinen's central warning. Companies that drift from AI experimentation into operational deployment without recognizing the transition can find themselves on the wrong side of the procedural line.
"At what point does the company have sufficient information on the estimated impacts on employees?" she says. There is no clean answer in the statute — and the timing matters, because employers cannot make business decisions that directly result in headcount reductions before change negotiations have been completed.
At the same time, change negotiations cannot be held on a “just in case” basis without a concrete plan and an assessment of workforce impacts. "That is something that needs to be remembered," Honkinen says.
As understanding of AI’s concrete impact on business operations grows, it becomes increasingly likely that we will see more change negotiations carried out already at the stage when new AI investments are being considered, she adds.
The Chinese rulings flagged a structurally similar issue from the opposite direction. Courts there argued that if AI restructuring becomes necessary, employers should first prioritize retraining workers, offer reasonable reassignment terms, and provide support measures before moving to dismissals. Two very different legal systems have landed on overlapping employer obligations.
The transition is already underway
A 2025 survey commissioned by OP Financial Group found that 38% of large Finnish companies had already replaced some work tasks with AI, while more than half said they planned to do so in the future. The same survey found that 84% of companies had trained employees to use AI tools.
An IMF paper published earlier this year estimated that around one-fifth of Finland's workforce faces a risk of AI-related job displacement, particularly in software development, finance, and administrative work — even as Finland remains among the countries best positioned to benefit from AI adoption overall.
Honkinen says the largest impact is likely to fall on knowledge-work sectors where companies can automate parts of expert workflows without removing the need for human oversight. She pointed particularly to junior roles, including in the legal sector itself, where AI can increasingly automate repetitive tasks previously handled by entry-level employees.
"The most junior roles are, of course, roles where there might be the most impact," Honkinen says. But she argued the issue is more complicated than simply reducing headcount. "You can't really have senior employees in the future without first having junior employees."
That tension is likely to become more visible across Nordic companies as AI takes over portions of administrative, analytical, and documentation-heavy work that traditionally formed the training ground for younger professionals.
Rather than eliminating entire professions, Honkinen says many companies are likely to redesign workflows and redistribute responsibilities. "It's more a matter of changes in the scope of work. New skills and new tasks might be introduced."
Most companies are still approaching AI cautiously rather than aggressively replacing workers. "At the moment, the general assumption is that individuals are still needed to verify the results of AI," she says.
What boards should actually ask
Honkinen says boards should focus less on immediate labor savings and more on whether management has a credible long-term workforce strategy.
"What they should ask from management is whether there is systematic development of employee skills and capabilities taking place in the company," she says.
She describes the current moment as a "strategic transformation of working life," where companies need clearer plans for training employees, introducing AI tools, and adapting organizational structures over time.
In practical terms, that points to several questions Finnish boards and management teams should be working through now:
Is there a documented workforce skills plan tied to the AI roadmap, not just a cost-savings case?
At what threshold does a pilot become a deployment that triggers change negotiation obligations — and who inside the company is responsible for flagging that line?
Are AI usage policies in place before deployment scales, including rules on what data employees can share with external tools and how confidential information is handled?
Are change-negotiation timelines built into AI rollout plans, rather than treated as an afterthought once decisions have effectively been made?
"In many companies, there is a growing need for new policies and new instructions to employees as to how to use AI," Honkinen says.
Despite the pace of technological change, she does not see a strong need for entirely new labor legislation in Finland. "The thing with law is that when we have technological innovation, it might be difficult to have a legal framework that is always able to follow the technological innovations."
The larger challenge for Finnish employers, she suggests, is operational rather than legislative. Companies need to decide when AI adoption stops being a technology experiment and becomes a workforce restructuring process — and act before the law makes that decision for them. At the same time, they need to ensure employees are systematically trained to use AI effectively and responsibly.
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5 min read
Chinese courts have ruled that AI adoption alone does not justify dismissing workers. Finnish employers have far broader discretion — but the legal risk emerges earlier than many boards realize.
When a Hangzhou tech company tried to replace its AI quality-assurance supervisor with a large language model — offering him a 40% pay cut to a different role, then firing him when he refused — China's courts ruled the dismissal illegal. The Hangzhou Intermediate People's Court decision, published in late April as part of a set of typical AI-related labor cases, established a principle now drawing international attention: AI adoption alone does not justify firing workers.
Finnish employers operate under very different rules, but the underlying question Chinese courts raised is one Finnish boards will face soon, if they aren't facing it already: at what point does deploying AI shift from being a productivity-driven investment to a decision that results in a reduction of the workforce?
"There is no black and white answer to that," says Sanna Honkinen, head of employment practice at Hannes Snellman. And that ambiguity, she warns, is where the legal risk lives.
The Chinese precedent
The Hangzhou ruling, upheld on appeal on April 28, centered on a quality assurance supervisor identified only as Zhou. Hired in 2022 at a monthly salary of 25,000 yuan (USD3,676) to oversee his employer's AI output, Zhou was told in 2025 that the company intended to replace his role with a large language model. He was offered a different position at 15,000 yuan — a 40% pay cut — and dismissed when he refused.
The Intermediate People's Court ruled that AI-driven job replacement does not constitute a "major change in objective circumstances" under China's Labor Contract Law, the legal threshold normally required to justify redundancy-based termination. The court also found the reassignment offer unreasonable on its own terms. The ruling built on a December 2024 Beijing arbitration decision involving a map data worker dismissed after AI took over his role, reaching the same conclusion: adopting AI is a business choice, not an unforeseen event, and its costs cannot be shifted unilaterally onto employees.
The cases have drawn international legal attention because they cut against the assumption — common in at-will jurisdictions like the United States — that AI-driven restructuring is a straightforward business decision. Finland's framework sits between these poles.
The Finnish legal reality
Finnish employers have considerably more discretion than their Chinese counterparts to restructure around AI.
"In Finland, the employer has the right to decide what business activities are operated and how business and roles within the company are organized," Honkinen says.
Roles can be terminated for financial, production-related, or reorganization reasons linked to technological development, including AI adoption, provided the amount of work has genuinely declined. But that discretion comes with procedural strings attached.
Under Finland's Co-operation Act, employers with at least 50 employees must begin change negotiations if planned measures could materially affect employees' work tasks, working methods, working hours, or lead to layoffs or dismissals on financial or production-related grounds. Employers with 20 to 49 employees face similar obligations in cases involving broader personnel reductions.
Employers must also assess whether employees can be reassigned or retrained before dismissals take place. "The employer has to consider whether the employee can be placed into another role or trained for another role," Honkinen says.
That retraining obligation is narrower than it sounds. Companies do not have to educate employees into entirely new professions — the expectation is shorter-term training into adjacent roles where employees already possess the core capabilities needed.
The timing trap
The harder question for Finnish boards is not whether they can reduce roles, but when AI adoption becomes serious enough to trigger the formal negotiation process.
That is Honkinen's central warning. Companies that drift from AI experimentation into operational deployment without recognizing the transition can find themselves on the wrong side of the procedural line.
"At what point does the company have sufficient information on the estimated impacts on employees?" she says. There is no clean answer in the statute — and the timing matters, because employers cannot make business decisions that directly result in headcount reductions before change negotiations have been completed.
At the same time, change negotiations cannot be held on a “just in case” basis without a concrete plan and an assessment of workforce impacts. "That is something that needs to be remembered," Honkinen says.
As understanding of AI’s concrete impact on business operations grows, it becomes increasingly likely that we will see more change negotiations carried out already at the stage when new AI investments are being considered, she adds.
The Chinese rulings flagged a structurally similar issue from the opposite direction. Courts there argued that if AI restructuring becomes necessary, employers should first prioritize retraining workers, offer reasonable reassignment terms, and provide support measures before moving to dismissals. Two very different legal systems have landed on overlapping employer obligations.
The transition is already underway
A 2025 survey commissioned by OP Financial Group found that 38% of large Finnish companies had already replaced some work tasks with AI, while more than half said they planned to do so in the future. The same survey found that 84% of companies had trained employees to use AI tools.
An IMF paper published earlier this year estimated that around one-fifth of Finland's workforce faces a risk of AI-related job displacement, particularly in software development, finance, and administrative work — even as Finland remains among the countries best positioned to benefit from AI adoption overall.
Honkinen says the largest impact is likely to fall on knowledge-work sectors where companies can automate parts of expert workflows without removing the need for human oversight. She pointed particularly to junior roles, including in the legal sector itself, where AI can increasingly automate repetitive tasks previously handled by entry-level employees.
"The most junior roles are, of course, roles where there might be the most impact," Honkinen says. But she argued the issue is more complicated than simply reducing headcount. "You can't really have senior employees in the future without first having junior employees."
That tension is likely to become more visible across Nordic companies as AI takes over portions of administrative, analytical, and documentation-heavy work that traditionally formed the training ground for younger professionals.
Rather than eliminating entire professions, Honkinen says many companies are likely to redesign workflows and redistribute responsibilities. "It's more a matter of changes in the scope of work. New skills and new tasks might be introduced."
Most companies are still approaching AI cautiously rather than aggressively replacing workers. "At the moment, the general assumption is that individuals are still needed to verify the results of AI," she says.
What boards should actually ask
Honkinen says boards should focus less on immediate labor savings and more on whether management has a credible long-term workforce strategy.
"What they should ask from management is whether there is systematic development of employee skills and capabilities taking place in the company," she says.
She describes the current moment as a "strategic transformation of working life," where companies need clearer plans for training employees, introducing AI tools, and adapting organizational structures over time.
In practical terms, that points to several questions Finnish boards and management teams should be working through now:
Is there a documented workforce skills plan tied to the AI roadmap, not just a cost-savings case?
At what threshold does a pilot become a deployment that triggers change negotiation obligations — and who inside the company is responsible for flagging that line?
Are AI usage policies in place before deployment scales, including rules on what data employees can share with external tools and how confidential information is handled?
Are change-negotiation timelines built into AI rollout plans, rather than treated as an afterthought once decisions have effectively been made?
"In many companies, there is a growing need for new policies and new instructions to employees as to how to use AI," Honkinen says.
Despite the pace of technological change, she does not see a strong need for entirely new labor legislation in Finland. "The thing with law is that when we have technological innovation, it might be difficult to have a legal framework that is always able to follow the technological innovations."
The larger challenge for Finnish employers, she suggests, is operational rather than legislative. Companies need to decide when AI adoption stops being a technology experiment and becomes a workforce restructuring process — and act before the law makes that decision for them. At the same time, they need to ensure employees are systematically trained to use AI effectively and responsibly.
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