Workers most often want AI as an equal partner, not a replacement

This guide is for foreign professionals in Korean companies, especially in accounting, legal, HR and administration, who are deciding how to work with AI. Research from 2023 to 2026 points the same way: AI is changing many tasks, but workers often want to stay involved, and equal partnership is the level they most often prefer. Use the findings below to decide which tasks to hand over and which to keep.

How far AI reaches into work

Three studies give a sense of scale.

• Researchers from OpenAI and the University of Pennsylvania estimated in March 2023 that about 80% of the U.S. workforce could have at least 10% of their work tasks affected by large language models, and about 19% of workers could see at least 50% of their tasks affected. The paper was published in the journal Science in June 2024.
• The Anthropic Economic Index, first published on February 10, 2025, analysed about one million conversations with Claude. Roughly 36% of occupations used AI for at least a quarter of their tasks, and use leaned toward augmentation (57%) rather than automation (43%). Its report of January 15, 2026 found that, combining data across its reports, 49% of jobs had seen AI use for at least a quarter of their tasks.
• The World Economic Forum's Future of Jobs Report 2025, published in January 2025, expects 170 million jobs to be created and 92 million to be displaced between 2025 and 2030, a net gain of 78 million jobs.

The direction is clear: AI takes over parts of jobs, and people who learn to work with it gain time for other work. In 2023, Harvard Business Review put this view in a headline for an interview with Harvard Business School professor Karim Lakhani: AI will not replace humans, but humans with AI will replace humans without AI.

The Human Agency Scale

A Stanford University team (Shao and others, first posted in June 2025 and revised in February 2026) asked 1,500 workers in 104 U.S. occupations how they want AI agents to handle 844 tasks. It also asked 52 AI experts what the technology can do. The surveys ran from January to May 2025. Instead of a simple "automate or not" choice, the team used a five-level Human Agency Scale:

Key findings:

• H3, equal partnership, was the level workers most often wanted. It was the dominant choice in 47 of the 104 occupations.
• In 47.5% of tasks, workers wanted more human involvement than the experts thought the technology required.
• When workers wanted automation, the top reason was freeing time for higher-value work (69.38% of responses). Next came repetitive tasks (46.6%), chances to improve quality (46.6%) and stressful tasks (25.5%).
• The main concerns were lack of trust in AI's accuracy, capability or reliability (45.0%), fear of job replacement (23.0%) and the absence of human qualities in AI (16.3%).

This is not only resistance to change. In accounting, legal and HR work, an error can affect the whole organization, so people want AI's help but want a person to keep the final judgment and the responsibility.

Four zones for deciding what to automate

The study sorted tasks by two questions: do workers want automation, and can AI already do the task?

The four zones come from the study. The examples in the last column are suggestions for typical office work, not results of the study.

Matching the level to the job

A practical split for support functions:

• Accounting. Let AI do data entry and first drafts, such as a draft of the financial statements. Accountants review and analyse the numbers and explain them to management (around H4).
• Legal. AI can search statutes, collect cases and draft contracts from standard clauses. Legal staff interpret the law, adapt drafts to the company's situation and assess risk (H4 to H5).
• HR. Resume screening and interview scheduling can be largely automated (H2). Final hiring decisions, performance reviews and conflict resolution need human judgment and emotional intelligence (H4 to H5).

The Stanford team also found early signs that valued skills are shifting from information processing to interpersonal and organizational skills. Analysing information is becoming less emphasized, while organizing and planning work and training others rank highest for required human involvement. For an accountant, this means turning financial data into advice for management. For legal staff, it means coordinating many stakeholders toward a workable solution. For HR, it means supporting people's growth and shaping the culture.

Plan for people's experience, not only for efficiency. AI can take over burdensome tasks, but the sense of competence, safety and belonging that people get from work still comes from other people. Ask what you want colleagues and clients to feel when they work with you.

What organizations are preparing

PwC's 2025 AI Business Predictions said AI agents, or "digital workers", would become new team members and double knowledge work capacity, and that companies would need new ways to manage teams of people and AI. Its 2026 predictions add that agentic workflows are spreading faster than governance models can keep up. In many cases agents can do roughly half of the tasks people now do, but that requires a new kind of governance.

PwC advises mapping each workflow step by step: where agents own the work, where people do, where they collaborate and how each step is overseen. Employees who orchestrate agents need to spot and correct their mistakes, connect them into teams and find new tasks for them. New roles related to oversight and strategy appear, and companies need new measures for the results of mixed teams.

Checklist

1. List your tasks and rate each for repetition, complexity, creativity and contact with people.
2. Mark which tasks AI can lead and which you must lead.
3. Start small, with email drafts or meeting notes, then move to analysis reports and proposal drafts.
4. Build the skills AI does not replace: critical thinking, creative problem solving, stakeholder management and judgment.
5. Share what works with other teams, and take colleagues' concerns about trust and job security seriously.
6. Ask how your company will measure results when people and AI work together.