Reshaping how companies operate: AI’s impact on the workplace

As AI develops rapidly, much discussion around the future of employment is taking place. Lumii AI’s Mei Yuxiang discusses the impacts

Much of the public discussion around artificial intelligence focuses on a single question: how many jobs will AI replace? But that framing misses the larger transformation already beginning to take place inside companies.

Over the next five years, AI will have a significant impact on the global labor market, particularly for entry-level white-collar workers performing repetitive digital tasks. In many areas, AI agents are already capable of outperforming inexperienced employees and businesses are increasingly beginning to recognize the economic advantages of restructuring teams around AI systems.

Rather than relying on large departments, many companies are moving toward much smaller, elite teams working alongside AI agents. The economic logic is straightforward. AI systems can often operate at less than 10-15% of the cost of human labor, while also reducing the management complexity and communication inefficiencies that emerge as organizations grow larger.

This is especially important in China, where companies have historically been cautious about spending heavily on enterprise SaaS tools, but are highly receptive to opportunities for dramatic cost reduction and operational efficiency.

The jobs most vulnerable to AI

Not all professions face the same level of risk. The jobs most exposed to AI disruption tend to share several characteristics.

The first are roles built around highly standardized operating procedures where it is easy to measure whether work has been completed correctly. The second are jobs involving repetitive tasks and waiting time between actions, such as administrative processing or coordination work. The third are roles that already operate almost entirely online.

Jobs involving physical processes, offline coordination, or hands-on operational work remain relatively protected for now. But digital office roles that already support remote work can be integrated into AI-driven systems almost seamlessly because they already exist inside fully digital environments.

This is why the impact on white-collar employment may arrive faster than many expect.

“An AI agent Is a virtual employee” Is probably wrong

The next phase of AI adoption is not simply about adding AI features to existing software. That thinking is already obsolete.

Today, many organizations view AI agents as virtual staff and actively explore replacing staff to reduce costs. The logic feels compelling: lay off eight employees at $4,500 per month each ($36,000 total) and subscribe to an AI service for $3,000 monthly, saving $33,000. Most people now understand this model. Unfortunately, it is already outdated. This is a shift we’ve observed in the market over the past three months.

The relationship between AI agents and human employees is not a simple “one agent replaces one employee” model, nor is it about distilling someone’s work into an agent and then letting them go. Both framings are flawed.

Why do people fall into this trap? Because “treating agents as virtual employees” is the most intuitive analogy. Yet the technical reality is counter-intuitive.

Unlike a single human, AI has near-infinite compute, requires no rest, and maintains perfect memory. Humans are fundamentally limited; AI is infinitely scalable. For unlimited AI, deliberately splitting context across multiple agents to make them collaborate adds little real value beyond making the system superficially resemble a human team.

AI can cut costs and improve efficiency, but that’s not the full story

Another common misconception is viewing AI purely as a cost center. While AI can reduce headcount and improve efficiency, this view is incomplete.

If only some companies adopt AI for cost savings, they gain a competitive advantage. But once every company does the same, the advantage disappears for all — it becomes as if no one had adopted it.

Forward-thinking companies have already moved past this mindset. They are using AI not just to cut costs, but to expand what the business can achieve — delivering better services and accomplishing things that were previously impossible. This requires deep integration of AI into industry-specific business processes. Without such integration, AI brings no more value than purchasing another SaaS tool.

The AI era is fundamentally different from the SaaS era. SaaS primarily digitized existing processes. AI is beginning to act as the enterprise’s brain, redefining “AI-native processes” themselves.

Why startups will move faster

The pace of adoption will differ significantly depending on company size.

Large enterprises face more constraints, including concerns about layoffs, reputational risk, and the complexity of internal control systems. As a result, they are likely to move more cautiously.

Smaller companies and startups, however, are positioned to move much faster. Many are already focused obsessively on efficiency and can adapt rapidly without the burden of large bureaucratic structures or legacy systems.

But regardless of company size, the economic incentives behind AI adoption are becoming increasingly difficult to ignore. Over time, even slower-moving organizations will likely be forced to adapt as AI-driven competitors become more efficient.

Regulation will likely remain reactive

Globally, there is growing discussion around regulating AI’s impact on employment. But in China, the current focus remains far more practical and operational.

Most businesses are primarily concerned with solving immediate problems: reducing labor costs, improving productivity, and managing workflows more efficiently. Regulatory responses are likely to emerge later, after the real-world effects of AI become more visible.

That means the next several years may involve rapid experimentation and deployment before more formal restrictions or labor protections begin to appear.

White-collar work will not disappear—but it will change

There is a growing belief that AI will eventually eliminate most white-collar employment. But the outcome is likely to be more complicated than simple mass unemployment.

A relatively small number of positions may become permanently unnecessary. However, the majority of white-collar workers will probably continue to have jobs—they will simply be doing very different kinds of work than they do today.

The transition is similar to the arrival of personal computers and office software. Before tools like Microsoft Office became widespread, offices relied heavily on paper-based systems.

Digital software dramatically improved efficiency, but it did not eliminate office work altogether. Instead, it transformed how work was performed.

AI is likely to follow a similar pattern, though at a much faster pace.

The core transformation is not the complete removal of humans from business operations. It is the restructuring of business processes around collaboration between humans and AI agents. Humans will remain involved, but they will increasingly operate alongside AI systems in entirely new ways.

China is already moving quickly in real-world AI deployment. As these systems become more deeply embedded inside companies, the transformation of white-collar work may arrive far sooner than many businesses currently expect.