AI and the Future of Work: Worker Rights in the Sharing Economy

Introduction

The term “sharing economy” is perhaps less well-understood than “gig economy” or “platform economy”. Where “platform economy” typically relies on work being assigned via some sort of digital platform and “gig economy” refers to project-based or task-based assignments, “sharing economy” refers to an economy where assets, whether physical (such as cars or rooms) or intangible (such as time or skills) are shared among workers and consumers alike. This sharing can be facilitated by a platform or not, or be assigned one project at a time or by hiring a consultant on retainer. Thus, the sharing economy can include both gig and platform economies in different forms.

Increasingly, no matter the form taken by the sharing economy, there are three notable points for policymakers to consider. First, there is an upward trend among young people and graduates participating in the sharing economy, despite its precarity. Second, the sharing economy is facilitated by digital technologies such as algorithmic management, which disrupts traditional labour structures and labour rights, thus requiring fit-for-purpose policies to address these changes. Third, policies intended to support an inclusive and equitable sharing economy need to include social protection provisions, professional and career development opportunities, and shared community building opportunities for sharing economy workers.

In this article, we unpack those three points to indicate the potential for the growth of the sharing economy in Malaysia and reiterate the need for greater engagement with sharing economy workers and stakeholders in the development of public policies.

Graduate trends in the sharing economy

Whilst it is difficult to estimate the overall market size of the sharing economy, MDEC found that a total of 246 Malaysia-based platforms command a market size of approximately RM18.8 billion as of Q1 2025¹. The sharing economy landscape is quite diverse, ranging from logistics and on-demand work to rides and transportation, to name a few sectors. Between 2016 and 2024, there has been an increase of over 1.6 million participants who make a living through digital platforms. These platforms, alongside larger foreign-based gig platforms, e.g. Grab, Bolt, are increasingly being used by graduates to garner income, given the recent trends of non-standard employment² among graduates.

Between 2013 and 2021, the number of tertiary-educated workers in non-standard employment almost doubled from 8.6% to 15.8%³. This is a worrying trend as non-standard employment is more precarious in nature, given limitations in aspects such as career progression, wage growth and social protections. A contributing factor is also the limited number of high-skilled jobs being generated in the market, with the mismatch resulting in graduates venturing outside standard employment to generate greater income in the short term.

KRI’s 2024 Shifting Tides report highlighted the increasing trend of self-employed graduates moving towards self-employment in recent years, from 3.3% in 2010 to a peak of 22.2% in 2020. However, there were mixed findings in terms of their motivation to pursue self-employment as a career, based on the type or nature of self-employment.

The report considered three main types of self-employment, namely employers, sole proprietors and freelancers. Employers were motivated by the opportunity for better income compared to standard employment at 40.4%, in contrast with sole proprietors (28.7%) and freelancers (10.7%), who noted the inherent flexibility that self-employment offers. Sharing economy workers fall into the freelancers category as they provide the supply or access to assets and/or services via a digital platform that acts as an intermediary and facilitates the transaction of products and assets between providers and users⁴.

A wide range of earnings has been recorded by the different types of self-employed, with 15.5% of employers reporting monthly incomes of over RM5,000 compared to only 1.0% of sole proprietors and 1.8% of freelancers. Another concerning pattern that was highlighted in the report was the percentage of sole proprietors and freelancers who earned below the minimum wage in 2024 which was RM1,500. Over half of freelancers (51.5%) and 37.2% of sole proprietors earned below the minimum wage.

The report also examined the prevalence of social protection coverage among the self-employed. Unsurprisingly, nearly two-thirds of graduates (63.3%) who become employers have a form of social protection in terms of contributions to EPF and SOCSO. However, more than a third of sole proprietors (34.6%), as well as 41.1% of freelancers, have no form of social protection whatsoever. These groups are among the most vulnerable in the labour market as they have limited means to protect themselves in the event of an interruption or loss of income, which makes them more susceptible to falling into poverty. These vulnerabilities are exacerbated by changes to the labour structure brought about by algorithmic management.

Impact of sharing economy on labour structure

The sharing economy is made possible by the use of digital technologies and big data analyses that enable more comprehensive analysis and organisation of assets on a large scale with minimal human intervention. For example, instead of needing to have taxis waiting in a fixed location and have passengers head to that location, ride-hailing apps can direct the nearest available drivers to wherever passengers are waiting. Similarly, instead of having inventory getting stale on the shelves, inventory managing software can use sales and marketing data as well as logistics data and weather patterns, to predict when to restock supplies, allowing the reassignment of both assets and labour to other tasks.

This sort of algorithmic management can increase business efficiency, opportunities and satisfaction. However, in automating some decision-making responsibilities, algorithmic management can have some unintended negative consequences on worker welfare. Impacts on individuals arising from algorithmic bias and perverse incentives have been well documented⁵. Recent research on societal impact has also considered how algorithmic management affects labour structures⁶.

Three ways that algorithmic management affects labour structures are: the individualisation of work, the reconfiguration of roles and obligations, and the concentration of power⁷.

The individualisation of work

As software takes over the work of assigning and scheduling tasks to human workers in the sharing economy, they reduce the need for negotiations and other social interactions that traditionally defined how jobs were allocated. A floor manager is no longer needed to compare worker availability and preferences to assign shifts to a shared kitchen; software or artificial intelligence (AI) will do the job more quickly and effectively.

Instead of needing to compromise and come to consensus, workers in the sharing economy can just show up to the slots they have been assigned that suit their needs and preferences. There are also few shared breaks or organisation-wide meetings for workers to interact with each other. While this can provide workers with a sense of flexibility and autonomy, in the long run it can reduce natural opportunities for camaraderie and community that typically occur in traditional workplaces.

The reconfiguration of roles and obligations

Similarly, in the sharing economy typical organisational structures such as hierarchies and workflows are streamlined by algorithms, software and platforms. On one hand this can reduce bureaucracy; on the other hand it can disrupt typical work relationships and structures around which many labour laws are defined. For example, employment status (e.g. are sharing economy workers platform employees or independent contractors?) and liability (e.g. who is responsible for equipment maintenance or liable for accidents involving shared vehicles?) are being redefined within the sharing economy.

Obligations that traditionally came with managerial or supervisor roles do not automatically translate to software. A manager may know that for the next few months one of her employees needs to leave early on Wednesdays to take a sick parent to the doctor, but it is not a given that that information will be provided to (or taken into account by) an algorithm that is coded to optimise productivity.

The concentration of power

More decision-making within the sharing economy being entrusted to AI and algorithms, whose logic may not be fully understood, may lead to a lack of transparency and understanding of how priorities and concessions are managed. Software continually collects data on worker performance and business outcomes, which may be shared with platforms but are rarely shared with workers. This information asymmetry between capital and labour leads to a power imbalance that is hard to address due to a corresponding lack of human intervention in the process. As such, policy intervention is needed to protect worker rights.

Public policy priorities that support worker rights in the sharing economy

Malaysia is no stranger to worker rights and social protections, labour being governed by regulations such as the Employment Act and the Employees' Social Security Act. Although these laws were drafted well before the advent of digital technologies, they remain the basis for worker protections in the country. As technology and work evolves, so must regulations.

Given the growth of the platform economy in Malaysia, the government sought to ensure adequate social protections for platform workers, especially during the Covid-19 pandemic. For example, as part of the national economic recovery stimulus package during the pandemic, the government contributed 70% of social security contributions for workers with platforms registered with MDEC⁸.

More recently, in August 2025, the Gig Workers Bill has been passed in Parliament⁹. Despite criticisms both that it tries to do too much¹⁰ and that it does too little¹¹, the law is intended to establish a minimum standard of protection for gig workers.

We propose that, beyond social protections, future policies should also address the following three areas of worker needs: professional development, community building and grievance processes.

Incentivise training and professional development

Skills development should be seen as a lifelong process whereby individuals can acquire new skills or technical training throughout their professional careers. However, workers in the sharing economy may have limited accessibility to accredited skills development programmes. SOCSO’s 2024 Bina Kerjaya 2.0 programme offered a subsidy of up to RM4,000 for the self-employed, gig workers, or informal workers to encourage their transition to standard employment¹². However, this programme also has its limitations, as participants can only opt for a single course, and it is only offered to diploma holders¹³. Given the increasing trend of degree holders who are venturing into non-standard employment, it would be beneficial for this group to be included in the programme. Incentivising accreditation programmes and facilitating micro-courses could also encourage more workers to participate in training.

Facilitate worker community groups and associations

Union membership in Malaysia has historically been low¹⁴, and this has resulted in reduced collective bargaining coverage and low wage growth. Opportunities for worker associations to form within the sharing economy are generally organic and emerge from the grassroots. Although they are not formal unions, worker associations and community groups have been instrumental in onboarding new workers, providing guidelines for navigating the sharing economy more effectively and generally supporting and helping one another. Such organisations should be encouraged and given a voice in business and policy decision-making. For example, worker representation should be present in discussions on expanding wage agreements to protect all workers, not just formal employees but also contract and migrant workers¹⁵.

Establish clear worker-centric grievance processes

The provision of clear and accessible grievance processes would go a long way to addressing issues and concerns arising from algorithmic management. In place of a human resources department, the sharing economy would benefit from having a complaints or appeals process in place. Workers could then be assured that any reports they make regarding issues they face will be met with meaningful follow-up and redress as appropriate. Instituting such a process could go together with defining roles and responsibilities of persons in the sharing economy as well as limits of software and algorithms. Increasing labour rights and legal expertise in this field will also help address worker concerns and protect worker rights.

Conclusion

The sharing economy is here to stay. It is important that the technologies that enable more efficient and flexible use of assets are governed well so that they do not undermine worker welfare. No matter how much technology improves efficiency or productivity, it must be remembered that worker wellbeing is essential to a thriving economy. Stakeholders of the sharing economy, from policymakers to workers to consumers, who understand the collective and structural effects of digital technologies will be able to advocate for and develop flexible, fit-for-purpose worker-centric policies.