When artificial intelligence (AI) started to change how the world operated, many of us were in love. As a team that’s worked with many businesses entering foreign markets, we can tell you: AI is a supremely powerful tool, but it’s not the full picture.
If all the talk is about numbers, automation and efficiencies, global employment is about people. It’s not something machines can do on their own.
The Role Of AI In Global Workforce Planning: Helpful, But Not Reliable
AI aids in recruitment, role-matching, and workforce allocation by reducing the time taken to assess decisions relating to the workforce by compiling large data sets. But AI has its built-in limitations, not the least of which is bias.
AI learns from the data it’s trained on, and without proper safeguards, it can repeat or even amplify unfair practices.
There’s great power in the predictive analytics that AI is capable of, but it struggles to address cultural differences and local compliance complexities in the context of global employment.
For example, hiring in Japan isn’t as simple as analysing data and assigning a role. Japanese workplace culture, with its emphasis on hierarchy, seniority, and job loyalty, imposes unique constraints that AI alone cannot navigate. Human oversight is essential — AI needs to assist decisions, but human judgment should be the centre of decision-making.
Can AI Remove Bias Without the Help of Humans?
There are many scary headlines about how AI can perpetuate bias, but what does that mean in practice? Hiring algorithms often score candidates lower because their resumes don’t reflect patterns found in candidates considered traditional success. It was not intentional, but this was the reality, and the bias was present in the data.
AI does not have bias on its own, it learns from what we give it. If that data is a mirror reflecting past inequities, so will the results. That’s why corporations need artificial intelligence and good people, experts to question outcomes, audit systems, and ensure decisions align with fairness and inclusivity.
Setting periodic reviews to assess the results of its AI-based systems. Thus, one well-known UK recruitment firm set up periodic reviews to look at the results of its AI-based recruiting engine. They didn’t accept the rankings at face value — they tested them, looking for patterns that would suggest bias. This manual process corrected the system so that it was fairer.
The best businesses using AI get the mix between the two exactly right, using AI to extract patterns and human insight to exercise fairness.
Professionals should regard AI as a helper, not a master. You need a human lens to counterbalance AI recommendations and ensure they align with company values and long-term vision.
Artificial Intelligence Can Only Take You So Far in Global Payroll
If you have been processing the payroll of a global workforce, you would recognise the complexity. The tax laws, social security contributions, tax residency rules, etc. can make the whole issue hugely complex.
It’s like trying to solve a jigsaw puzzle while the pieces keep morphing. AI can automate 1,000,001 calculations, but it’s the exceptions that cause the real headaches.
AI enables scaling, and is fabulous for automating repetitive tasks, but human international payroll experts and their domain knowledge are better suited for special cases. It’s the difference between automation that works in theory and solutions that work in practice.
AI is a tool, not the answer.
At Acumen International, we don’t just follow technology — we supplement it with the skills and knowledge of people who’ve worked in the trenches.
Where Are Legal and Ethical Boundaries of AI?
While AI can quickly answer questions, its output can be inaccurate or biased, largely due to data that is incomplete or biased.
AI can sometimes produce inaccurate or misleading outputs, known as hallucinations. Without human checks, these mistakes can create serious legal risks. In global employment, errors in contracts or compliance with local regulations can lead to costly issues across jurisdictions.
AI’s development, deployment and use span multiple sectors and cross-national borders, creating global opportunities and challenges.
That’s when human validation becomes necessary. Signing off on every AI-generated output may be tedious, but in practice, it’s a negligible price to pay to avoid even more costly mistakes. Companies need teams that understand the laws and the grey areas where interpretation matters.
With the growing need for AI governance, new initiatives aim to reduce risks and promote AI systems that are fair, trustworthy, and focused on human rights.
Trouble With Overconfident AI
If you were consulting a human expert, you wouldn’t be getting the response presented in such a confident manner that the AI models like to give—even if they’re wrong.
The issue comes in with how the AI processes information: it’s geared to respond to specific types of prompts rather than to truly understand the nuances of the user’s request. This can lead to overconfidence in the AI recommendations, especially on sensitive questions like cross-border payroll or tax matters.
That’s where human oversight is key — to validate AI-driven recommendations and bring a level of scrutiny appropriate for high-stakes decisions.
The Expanding Field of AI Regulation
The rise of AI platforms—spanning everything from art to speech simulation — has sparked important discussions about regulation. Governments are working to create frameworks that balance progress with responsibility.
By 2024, at least 300 laws governing the use of AI existed, in some form, worldwide. We need guardrails to make AI work for everyone.
These collaborations reflect an increasing come-together of the sharing consensus that AI governance needs to be global, inclusive and anticipatory. Nations are not only following the steps for ensuring innovation and competition, while also addressing the challenges to the digital economy, social well-being and public governance posed by AI.
OECD — Keep an Eye on What Happens Next
The Organisation for Economic Co-operation and Development (OECD) has curated a live database on national AI policies. The database contains details of over 1,000 AI policy initiatives across 69 countries, territories, and the European Union.
This database is continually updated, updated along with new AI policies and strategies, reflecting the important conversation around responsible AI governance as technology moves faster than ever.
Governments and local authorities around the world are starting to respond to the potentially pervasive impacts of Artificial Intelligence across all areas of society, releasing policies that regulate the use of this new and transformative technology – all of which are now documented in this database.
How Do We Create Explainable AI Decisions?
The truth is, most AI models function like a black box. They provide outputs without any transparent window into the reasoning process that led to them. That can be dangerous in areas such as global payroll or compliance, in which transparency is key.
Large language models, for example, provide answers through patterns without explaining their logic. This cannot replace human subject matter experts who must bridge this gap between transparency, accuracy, and explainability of AI-based decisions in high-stakes domains such as legal compliance or people.
When Does AI Require Human Adaptability?
AI systems — no matter how powerful they are — are generally not very strong. While AI can demonstrate great results with known data, but in new and complex real-world situations the output may either be limited, vague or completely incorrect.
Global employment is complex, with different laws, cultures, and individual circumstances. It takes human judgment to ensure decisions are both compliant and employee-friendly.
Why We Must Bridge the Digital Divide
AI has great potential to improve how we manage the global workforce. This is especially true for complex tasks like payroll processing, compliance tracking, and global talent management. AI can improve multinational employers’ decision-making and operational processes through its speed in analysing data and forecasting trends. AI promises efficiency, but it has no lived experience and can miss nuances of hiring compliance.
AI jobs are one of the fastest growing global sectors. But you have to frame it the right way. We should consider humans working with AI. Such practices can help us amplify positive impacts and minimise harmful consequences.
By understanding both the upsides and downsides of AI, businesses will be able to adopt AI technology properly while not eliminating the human touch in employed talent approaches.
Acumen International offers a balanced solution: technology and people. Combining technology with a human touch is key to tackling global employment challenges in 2025.
With laws around AI and governance frameworks constantly evolving, having a human touch alongside advanced tools has never been more important. We are here to support you on your global employment journey.