When Time is No Longer Worth Money: AI and the Transformation of Work Structure

Jakarta — For more than two centuries, time has been the invisible foundation of capitalism. We are paid per hour, work eight hours a day, overtime is calculated based on additional time, and retirement is determined by years of service. This logic has become so entrenched that it is rarely questioned. The wave of artificial intelligence (AI) is shaking this foundation. When a single engineer in Jakarta can develop an AI-based system in four hours that subsequently works autonomously for 24 hours without interruption, the fundamental question is no longer how long he worked, but rather who controls the system and how value is created and distributed.

Here Indonesia faces a major challenge: how to restructure labour law, wage systems, and social protection in the face of the radical transformation in the meaning of time within the digital economy.

Indonesia has approximately 144 million workers in 2025, with more than 59 per cent still in the informal sector. This structure has been fragile in time-based protection from the outset. Most informal workers, such as online motorcycle taxi drivers, small traders, and digital freelancers, do not enjoy fixed hourly wages, overtime guarantees, or stable pensions. Now, with the increasingly widespread penetration of AI, from the use of ChatGPT by consultants to Copilot by programmers, to administrative automation in banking and e-commerce, the relationship between time and economic value is increasingly severed.

In a 2024 survey by the Ministry of Communication and Information Technology, approximately 37 per cent of technology companies in Indonesia have already adopted AI systems for operational efficiency, with this figure projected to exceed 60 per cent by 2027. This means change is no longer a topic of discussion, but a reality that is unfolding.

To date, Indonesia’s labour law system, governed through the Labour Law and updated through the Job Creation Law, remains heavily based on the logic of working hours. The minimum wage is calculated based on adequate living needs per month, overtime is paid per hour, and employment relationships are assumed to be stable and tied to a single employer.

In an AI-based economy, at least three different time regimes emerge. First, there is “machine time”, when workers are responsible for systems that run 24 hours. A data engineer at a fintech company may officially work 40 hours per week, but if a system failure occurs at two in the morning, he must be on call. His salary remains the same, but the value he safeguards could be worth billions of rupiah in transactions per hour.

Second, there is “personal time”, when freelance workers use AI to complete projects quickly and are paid based on results, not time. A consultant in Jakarta can produce a strategic report worth Rp500 million in just a few days because they are assisted by AI.

Third, there is the classic “hourly time”, such as nurses, teachers, or factory workers who are still paid based on the duration of work, not the output produced.

This fragmentation creates new inequalities. Workers who have access to AI systems and a strong reputation can switch to result-based schemes with higher incomes. Meanwhile, those without access to technology will remain dependent on hourly time with stagnant value.

World Bank data shows that Indonesian labour productivity is still about 23 per cent of the average for developed countries. If AI increases the productivity of skilled groups by two or three times, but does not increase the productivity of other groups, then the income gap will widen sharply. Indonesia’s Gini coefficient, currently around 0.38, has the potential to increase again if this transformation is not managed with appropriate redistribution policies.

On the other hand, Indonesia has significant opportunities. The demographic dividend continues until around 2035, with approximately 70 per cent of the population at productive age. If AI is used as a tool to increase productivity, not merely as a substitute for labour, Indonesia can make a leap in global value chains. For example, the manufacturing sector, which accounts for approximately 18–19 per cent of GDP, can integrate AI to increase production efficiency by 15–20 per cent, as demonstrated in various Industry 4.0 studies.

The digital financial services sector, which grows in double digits every year, can also expand financial inclusion, at lower cost, through AI-based credit analysis automation. However, these benefits will only be optimal if public policy can ensure more equitable value distribution.