Impact of AI on White Collar Indian Work: An Analysis of ‘Bullshit Jobs‘ | TechPolicy.Press

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Earlier this year, India released its annual Economic Survey. Interestingly, the 2024-25 Economic Survey has a chapter titled ‘Labour in the AI Era: Crisis or Catalyst’. The Chapter takes a realistic stock of AI adoption trends and forecasts. It concludes that “estimates about the magnitude of labor market impacts (by AI) may be well above what might actually materialize.” Given the nascent stage of AI development and deployment, the National Economic Survey refrains from deterministically predicting the impact of AI on the labor market.

However, the survey poses an important question worth considering: “What were the problems in the world that demanded AI as the answer?” In other words, is AI a solution in search of a problem?”. This question is to be read in light of India’s unemployment crisis. The International Labor Organization’s India Employment Report 2024 revealed that the proportion of educated youth who are unemployed doubled from 35.2% in 2000 to 65.7% in 2022. The trend of AI adoption raises alarms about automating jobs, especially white-collar jobs. In October 2024, it was reported that Indian fintech company PhonePe laid off 60% of its customer support staff over the past five years as part of a shift to AI-powered solutions.

AI Adoption Trends

Recent reports indicate that India is a global leader in AI adoption, with 30% of Indian enterprises adopting AI compared to the global average of 26%. NASSCOM’s AI Enterprise Adoption Index 2.0 reveals that India’s 2024 AI adoption index score is 2.47 on a 4-point scale, compared to 2.45 in 2022, with a 2X rise in the number of companies in the Expert stage of AI adopters. With India’s AI market expected to grow at 25-35% CAGR over the next 3-4 years, there is no doubt that AI’s role in Indian corporate spaces is only expected to grow.

Apart from the PhonePe instance cited above, there is no conclusive data to predict the extent of job automation due to AI. A 2024 study by the Indian Institute of Management, Ahmedabad, on labor force perception of AI (“IIMA Study”) states that 68% of the surveyed white-collar employees expect AI to partially or fully automate their jobs in the next five years. 40% of white-collar employees perceive that their current skills will become redundant.

While the exact impact of AI on employment is yet to be established, the impact of earlier technologies on labor markets has been studied. In the context of the computer revolution, Goos and Manning, in 2003, observed a trend of labor polarization in the UK, marked by a growth in high-skill cognitive jobs and low-skill manual occupations, with a simultaneous reduction in middle-income routine jobs. In the same year, a study by Autor et al. confirmed this finding by providing a task model that categorized jobs into routine and non-routine and cognitive and manual and further observing that automation is limited to simple rule-based routine cognitive and manual routine jobs while this automation complements non-routine complex jobs. However, more recent studies have debunked the historical trend of automation being limited to routine and simple tasks. In 2013, Frey and Osborne observed that the recent technological advancements, which included AI and ML, are also leading to the automation of non-routine jobs. The study concludes that algorithms that run on big data allow for the automation of a wide array of skilled jobs.

Now that it is established that AI adoption is taking place in India and is likely to automate jobs irrespective of the skill level required, the nature of AI deployment and the manner of automation is also to be considered. The IIMA Study states that the interviewed employees shared multiple use cases for AI-powered solutions that lead to a workforce reduction. Based on the study, the main areas of automation are bucketed into three categories:

• Repetitive tasks: Data entry operators, quality inspectors, demand forecasters, and language translators are experiencing workforce reductions.
• Supervisory roles: Human supervisors are being replaced with monitoring and managing systems.
• Compliance roles: quality control inspectors and demand planners, management information systems (MIS) managers, and IT support teams are impacted by AI tools that perform their function.

While these jobs are currently being automated, there is also a trend of new jobs being created due to AI. The IIMA Study states that the interviewed business executives shared that AI technologies have led to the creation of new specialized roles such as visualization, forecasting, natural language processing (NLP) experts, and prompt engineers. Further, the study reveals that 63% of the interviewees expect AI to create new job roles over the next five years. The trend of simultaneous job reduction and creation as a result of technological innovation has been well documented. Technological progress is found to have two effects on employment: first, the destruction effect, where technology substitutes for labor, and second, a capitalization effect, where the growth from technological innovation will lead to the creation of jobs in industries with high productivity.

The outcome of these simultaneous forces will be analyzed through the theory of ‘bullshit jobs’ proposed by anthropologist David Graeber.

AI and ‘Bullshit Jobs’

In his 2018 book, ‘Bullshit Jobs: A Theory,’ David Graeber argued that the 21St Century is riddled with people toiling away in jobs that don’t seem to do anything productive. He elaborates how John Maynard Keynes predicted in 1930 that due to technology, society would be able to cut down labor to a fifteen-hour work week. Instead of this utopia, David Graeber argues that in the UK and the US, there has been a decline in the number of workers employed as domestic servants, in industry, and in the farm sector, with a simultaneous rise in professional, managerial, clerical, sales, and service workers. People are working harder than they ever have in the ballooning service sector. Graeber argues that the reason for this is moral and political:

The ruling class has figured out that a happy and productive population with free time on their hands is a mortal danger. (Think of what started to happen when this even began to be approximated in the sixties.) And, on the other hand, the feeling that work is a moral value in itself, and that anyone not willing to submit themselves to some kind of intense work discipline for most of their waking hours deserves nothing, is extraordinarily convenient for them.

Without delving into the morality of ‘bullshit jobs,’ Graeber’s observation of the rise in service jobs is true for India as well. Services in India account for 54% of the GDP and 31% of the labor force. Blume Venture’s Indus Valley Annual Report 2024 also argues that India’s youth dream of what they term ‘AC jobs’ or cushy office jobs in the public or private sphere. These are the same jobs that Graeber argued as ‘bullshit jobs’ or those that can be rendered away or easily automated.

With the rise of AI, scholars have taken a second look at Graeber’s theory and argued that AI will not create a Keynesian utopia but will only create more bullshit jobs. Graeber has categorized bullshit jobs into five types: (i)Flunkies, jobs that exist to make other people look important such as personal assistants, corporate receptionists, and gatekeepers; (ii) Goons, jobs that involve enforcing pointless rules or hierarchies such as security guards and corporate compliance officers; (iii) Duct Tapers or jobs that exist to fix problems created by other bullshit jobs such as IT support staff, corporate lawyers, and human resources personnel; (iv) Box Tickers or jobs that involve following pointless procedures or generating meaningless reports such as data entry clerks, paralegals, and insurance adjusters and lastly (v) Taskmasters or jobs that involve creating busywork for others or micromanaging their activities such as middle managers, certain human resource personnel, and some consultants.

Despite technological advancements, labor has not been reduced for humankind; instead, it has led to the creation of new “bullshit jobs.” Graeber’s theory can be used to analyze trends in Indian white-collar jobs, as observed in the IIMA study. The three identified avenues of automation in Indian white collar jobs perfectly fall into categories of bullshit jobs: Repetitive tasks of data entry operators, quality inspectors, demand forecasters, and language translators are Box Tickers; Supervisory roles of managers perfectly correspond with Taskmasters and Compliance roles of quality control inspectors and demand planners, management information systems (MIS) managers and IT support teams are Duct Tapers. Thus, as per recent trends, India is witnessing the automation of three categories of bullshit jobs: Duct Tapers, Box Tickers, and Taskmasters.

It is further argued that this trend of automation reveals that bullshit jobs that are getting automated are the ones that do not require a human presence. The remaining two categories of bullshit jobs, Goons, and Flunkies, require a corporeal person to serve their purpose. Thus, we have progressed enough that certain categories of bullshit jobs are getting automated.

Conclusion

While the automation of bullshit jobs might be read as a welcome trend, this is to be read in conjunction with the other trend observed in the IIMA Study, the creation of new AI-focused jobs. It is argued that these AI-focused jobs will be nothing but new warped versions of the existing categories of bullshit jobs. Based on applying the bullshit jobs theory to the trends depicted in the IIMA Study, the following are the likely trends in Indian white-collar jobs in the coming few years:

• Box Tickers to be highly automated: Jobs that require processing information and generating outputs, such as data entry and clerking, will likely see huge levels of automation. It can be reasonably assumed that since this application of AI is widely used and is cost-effective, this category of bullshit jobs is likely to diminish significantly.
• New kinds of Duct Tapers: Compliance roles such as corporate law, IT support, and quality control are already seeing automation trends. This is likely only to increase as AI-powered solutions can minimize human error and minimize compliance costs. However, due to AI bias and inherent limitations, experts argue that we will likely see ‘human in the loop’ review mechanisms. This points to the emergence of new kinds of duct tapers. The deployment of AI is likely to be accompanied by certain ethical standards and guidelines, whether from the governmental or self-regulatory, to assuage fears of AI discrimination and bias. New duct tapers will emerge to maintain compliance and enforce these guidelines in AI deployment strategies.
• Rise of AI taskmasters: The Indian corporate sector is already seeing automated systems for monitoring and managing workflow processes. Given this trend, it is likely that corporates will deploy automated management systems to manage and micromanage their labor, including but not limited to attendance systems and hour trackers.
• Flunkies will remain, and new flunkies will emerge: Flunkies such as receptionists and personal assistants are likely to not be automated as their existence as a corporeal person is essential to their function. However, there are likely to be new AI-powered flunkies. A key example is AI-powered note-taking applications for meetings. Having AI-leveraged technology for tasks such as note-taking performs the same function as human flunkies: make the management look good by showcasing their capabilities and due diligence.

Despite the wide adoption of AI in Indian white-collar jobs, the AI boom is still in its nascent stage. While these predictions can help understand how AI will impact labor and white-collar work, a litany of factors, the key of which is the legal regulation of AI, will play a role in determining the trajectory of AI-integrated work.