The repricing of human work in the age of AI

By Chiharu Maki

Once a struggling family-run restaurant, a sushi place grew over nearly 18 years into a celebrated Sapporo establishment. In 2024, it moved to Ginza and became members-only, with course prices now high enough to make a returning diner wonder if it was really the same restaurant.

The striking difference in price prompted a broader reflection on how we value human work. As AI makes many tasks easier to replicate, and therefore cheaper to perform, work that creates distinctive, difficult-to-reproduce value appears to command a higher premium. A sushi master’s craft is one example.

For leaders, this raises a central question: How can they redesign organizations for a world where AI is now a part of everyday work?

So, what, exactly, makes work valuable?

According to Deloitte’s 2026 Global Human Capital Trends, 93 percent of corporate AI investment goes toward technology. Yet organizations that intentionally design how humans and AI work together are twice as likely to achieve the expected return on investment on their AI investments and 2.5 times as likely to deliver stronger financial performance.

Technology may not be the bottleneck. The scarcer resource may be people who turn AI into business value.

In Japan, some companies are beginning to answer this question in their own way. One example is a health-tech company, with a local presence here in the Philippines, that has created a new incentive scheme for the era of AI. Depending on performance, compensation could exceed 10 times the business’ publicly reported average annual pay.

The number is, however, not the most interesting part. The company is not simply paying for expertise but is compensating for organizational leverage. It is looking for someone who can redesign work, systems, and processes around AI, enabling the organization to create outcomes on an entirely different scale.

This may signal where talent portfolios are heading. People may increasingly be valued not for task volume, but for their ability to multiply value across the organization.

As AI lowers the price of execution, it raises a more difficult question: Which human contributions should command a premium? Judgement is one. Adaptability is another. Accountability may be the most undervalued of them all.

AI performs remarkably well when patterns are observable, tasks are repeatable and feedback is unambiguous. Business, however, rarely behaves so politely. Client priorities shift, markets evolve, critical talent departs, strategies lose relevance and information remains incomplete. Yet consequential decisions must still be made.

This messiness is precisely where judgment matters. AI forces organizations to make choices they have often avoided: which work truly matters, which decisions require judgment and which outcomes someone must still be willing to own.

A similar lesson is emerging in education. The recent Programme for International Student Assessment by the Organization for Economic Cooperation and Development (OECD) results found that students who used AI for specific school tasks often performed worse than nonusers. Yet frequent users who were taught to assess AI-generated information tended to perform better. The OECD cautions that this does not prove causality, but that pattern is suggestive.

The question is not simply whether people use AI, but whether AI strengthens thinking or substitutes for it.

The same may be true at work. Competitive advantage may increasingly depend on whether organizations help people think better with AI rather than outsource their judgment to it.

For leaders, that challenge comes down to four areas of questions:

• Work: What should AI do? What should humans still do? Where should they work together?
• Decisions: Where does human judgment genuinely add value? When AI contributes to a decision, who owns the outcome?
• Talent: Which capabilities are becoming commodities? Which ones are becoming scarcer and more valuable?
• Rewards: What are we really paying people for?

The fundamental question in an AI-era talent strategy is no longer simply “How many people do we need?” It is “What do we need people for?”

This is a much harder question. Every decision about skills, roles, rewards and investment signals which human qualities an organization values.

Which returns the discussion to the sushi restaurant. It now commands such a high price because the market recognizes something distinctive and difficult to reproduce. Guests are willing to pay for that value, allowing the craft to be refined further.

In the AI era, organizations will not pay a premium for human effort simply because it is human; nor will they pay a premium for AI proficiency alone. The paradox is that the more work AI can perform, the less useful it becomes to reward people simply for being busy.

The premium will go to those who can direct intelligence, human or artificial, toward outcomes that matter and who are willing to own the consequences. Seen this way, “What are we really paying people for?” is more than a question about compensation. What businesses pay for is what they choose to value. And over time, what organizations choose to value shapes the kind of people they create.

Chiharu Maki is a director with the Technology & Transformation practice at Deloitte Southeast Asia, a member firm of the Deloitte network.