"Will AI take my job?": Technological Unemployment or a Revolutionary Transformation?
Future, Facts, History, and Analysis of the Public Sentiment Worldwide
ChatGPT was the talk of the town in the past couple of years. It stirred a mix of tension, confusion, and hope among people, with fears of job losses, uncertainty about the future, and expectations for a modern era. Topics like "Will ChatGPT kill XYZ jobs?" trended across Quora, sparked debates, and dominated Twitter and Instagram. YouTube, in particular, was flooded with videos offering hacks to "beat the evil job-sucker" ChatGPT.
But, ChatGPT was a buzzword.
In reality, it was a result of an extensive research and development in the fields of AI and automation since past many decades. In recent years, the world has witnessed a surge in the number of startups dedicated to developing AI-driven products and solutions.
This growth has been fueled by massive investments pouring into AI companies, which reflects a strong belief in the potential of artificial intelligence.
Nearly 40% of global employment is exposed to AI!
The AI market in India is projected to reach $8 billion by 2025, growing at a compound annual growth rate (CAGR) of over 40% from 2020 to 2025!
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Industry leaders, policymakers, and major corporations are increasingly embracing AI as a cornerstone of future development.
Donald Trump's administration emphasized prioritizing AI innovation by removing regulatory barriers against AI, in addition to the Biden administration's focus on establishing ethical guidelines. Meanwhile, India's push for AI leadership through the IndiaAI Mission, launched last year, received a significant boost with the Union Cabinet approving over ₹10,300 crore to strengthen the country's AI ecosystem. (I will elaborate on all of it in the newsletter, so keep reading!)
This only implies that political leaders and thought leaders around the world are increasingly viewing AI as a transformative tool capable of revolutionizing sectors ranging from healthcare and education to finance and manufacturing. While the fear of losing jobs could be valid, there are better questions to ask:
How will the workforce and job market evolve in response?
What implications will this shift have on India and global economy?
What does it mean to witness a change in the landscape with AI taking over laborious, repetitive, and even moderately creative tasks?
Here is what the history tells about Technological Unemployment
The displacement of labour with the rise of technology (also known as ‘Technological Unemployment’) likely dates back to humanity's earliest invention of the wheel. The issue was first formally addressed in the early 1800s by David Ricardo, in the context of the Industrial Revolution in Britain. Higher wages for British workers compared to those in other countries prompted Great Britain to seriously consider costly inventions and the introduction of new technologies as a solution.
Popularized by John Maynard Keynes in the 1930s, He describes technological unemployment as "only a temporary phase of maladjustment." If that’s true, it certainly undermines the fears of those who resist the idea of an advanced future!
Similarly, Leontief (1983), observing the dramatic improvements in the processing power of computer chips, expressed concern that people would be replaced by machines, just as:
Horses were made obsolete by the invention of internal combustion engines,
Artisan weavers were reduced to poverty after the introduction of mechanized looms, and
Retail cashiers were displaced by self-service and cashierless stores.
History has indeed recorded automation substituting the human labour in the short term but has also led to the creation of complementary jobs in the long term:
Horsemen lost jobs but jobs in manufacturing cars, trucks, and engines emerged,
Artisan weavers were diminished but machine operators, supervisors, and quality controllers, and
Retail cashiers gave way to engineering, and system maintenance for self-service technologies.
Now, in 2025, the world stands perplexed at the crossroads of AI innovation and the fear of an uncertain job market.
Fin Fact! The term "Luddite fallacy" is often used to criticize the view of those concerned about long-term technological unemployment, suggesting that they are committing a fallacy by failing to account for compensation effects.
It is AI’s world, and we are living in it
Why wouldn’t I start this section by talking about Nvidia’s stocks soaring and making initial investors Millionaires and Billionaires!
A pioneer in the GPU (graphics processing units) industry, was a standout performer in the bull market of 2024. By the way, GPUs are the things that make ChatGPT possible because they are crucial for training large neural networks (that mimics your brain!). Its stock gained 220% over the past year. Nvidia, now on the market for 25 years, has achieved a staggering 373,000% increase since its first-day closing price.
Nvidia's stock rose significantly due to its dominant position in the semiconductor industries, which experienced explosive growth in demand for obvious reasons. Nvidia's AI-focused chips, such as the H100 and A100, are widely recognized as industry leaders, and the “insane” demand for these GPUs from tech giants, startups, and data centers drove Nvidia’s revenue and stock valuation to new heights.
Fin for thought! By the way, why do you think India is not manufacturing its own GPUs? Let me know in the comments if you want the next newsletter to discuss this in depth! (wink, wink)
Here’s a starter, to address the scarcity and high cost of GPUs, the government has two options in my opinion - either to allow businesses to address the GPU challenge independently or to invest in public funds to make GPUs accessible to businesses.
Artificial intelligence also turned certain stocks into market darlings in 2024.
AppLovin (APP) reported a 66% surge in advertising revenue, tripled profits, and a 740% stock rise, driven by enhancements in its AI model. Palantir Technologies (PLTR) showcased AI-driven solutions for customers, achieving 30% sales growth and a 360% stock increase. Vistra (VST) benefited from rising electricity demands driven by AI, with its stock soaring 260% as the utilities sector drew AI-related interest.
According to data by Statistica, companies worldwide raised $56 billion from VCs in 2024 across 885 deals. This represents a 192% increase from 2023, when investors poured $29.1 billion into generative AI startups across 691 deals. Below is an information-packed table for number-nerds!
What will the arrival of AI mean for the labour force?
Productivity Boost!
AI will kill the jobs for the skilled ones? No, AI will the bridge the gap between the moderately-skilled and the super-skilled ones to boost overall productivity.
AI-powered tools, such as IBM Watson Health, assist in diagnosing diseases, reducing error rates, and accelerating the diagnostic process. Automating tasks like scheduling, medical billing, and patient record management saves valuable time for healthcare professionals. Similarly, machine learning algorithms enable real-time identification of fraudulent transactions with high accuracy.
On a personal note, I utilized ChatGPT as an efficient tool to support the writing of this newsletter! There is also growing evidence that generative AI can enhance the productivity of less-skilled employees within an organization or occupation.
Previous technological advances have been skill-biased, where high-skill workers experienced wage gains because of productivity improvements while people in lower-skilled jobs, where tasks are repetitive, experienced job losses and decreased real wages due to automation. GenAI could automate a significant portion of a job’s tasks, leading to potential job losses in occupations affected the most.
We have limited quantitative data about the usability of generative AI systems like ChatGPT for real business tasks: A new study tested very different types of users in different domains but arrived at the same conclusions:
Erik Brynjolfsson and colleagues from Stanford and MIT conducted a study where the results showed that the less-skilled agents benefited the most from AI tools, with the bottom 20% improving task throughout by 35%, far exceeding the average. In contrast, the top 20% saw minimal or no improvement, suggesting the AI tool primarily helps bridge skill gaps.
Income inequality!
AI will kill jobs and bring income inequality? No, AI will replace traditional jobs with the new ones and can bring inequality if unregulated!
Research in labour economics shows that the rise of computers and information technology has contributed to income inequality by automating routine middle-income jobs, a phenomenon known as job polarization. This has eroded mid-tier roles, such as clerical and administrative tasks, which once provided stable, middle-class incomes. As a result, the labour market has become divided into high-income workers in specialized roles and low-income workers in jobs resistant to automation. This, in turn, resulted in a widened income gap and concerns about economic mobility.
Along with an expected structural job loss, I believe the future awaits to see some big players in the AI field leading to an unprecedented industrial concentration. Companies like Open AI, Google DeepMind or NVIDIA can be the google of tomorrow (Imagine that!). But amongst thousands of players, only a handful will dominate, pushing many others in the field itself to the peripheries.
Less industrial concentration!
AI will turn all the non-techies to losers in the long term? No, Everyone will win with AI!
An internal memo leaked from Google in May 2023, in which a researcher said that “open-source models are faster, more customizable, more private, and pound-for-pound more capable” than proprietary models. The researcher said that processes in small open-source models can be quickly repeated by many people and end up better than large private models that are slowly iterated by a single team and that open-source models can be trained more cheaply.
In the Google researcher’s view, open-source AI may end up dominating the expensive proprietary models. Lower costs and higher availability is making it easier for college students to secure funding for their AI startups. (data) It means that AI will likely transform all the fields while the scale of its impacts may differ industry wise.
AI-driven sectors of the future
As per Google Cloud’s official website, Businesses are exploring practical applications tailored to their industries to unlock value and efficiency. The core areas in business are: Embedding AI into strategic business operations. Top Use Cases as per google: Multimodal AI, AI-powered search, AI agents, Enhanced customer experiences, Strategies for deepfake defense.
As discussed earlier, IMF staff examines the potential impact of AI on the global labour market and almost 40 percent of global employment is exposed to AI (That’s huge!). Historically, automation and information technology have tended to affect routine tasks, but one of the things that sets AI apart is its ability to impact high-skilled jobs.
By the way, pharmaceutical sector is undergoing a massive transformation with the integration of artificial intelligence (AI) and they are a great investment for today and a smart choice for tomorrow. We will help you or your friend invest in those Pharma companies: Click here to check out our product: Pharma Select.
In advanced economies, such as the United States, Germany, Japan, and the United Kingdom, about 60 percent of jobs may be impacted by AI. Roughly half the exposed jobs may benefit from AI integration, enhancing productivity. For the other half, AI applications may execute key tasks currently performed by humans, which could lower labour demand, leading to lower wages and reduced hiring. In the most extreme cases, some of these jobs may disappear.
In contrast, emerging markets (like India, Brazil and South Africa) and low-income countries (like Ethiopia, Nepal and Haiti), AI exposure is expected to be 40 percent and 26 percent, respectively. These findings suggest emerging market and developing economies face fewer immediate disruptions from AI.
AI could also affect income and wealth inequality within countries.
We may see polarization within income brackets, with workers who can harness AI seeing an increase in their productivity and wages—and those who cannot falling behind. Research shows that AI can help less experienced workers enhance their productivity more quickly. Younger workers may find it easier to exploit opportunities, while older workers could struggle to adapt.
The effect on labour income will largely depend on the extent to which AI will complement high-income workers. If AI significantly complements higher-income workers, it may lead to a disproportionate increase in their labour income. Moreover, gains in productivity from firms that adopt AI will likely boost capital returns, which may also favor high earners. Both of these phenomena could exacerbate inequality.
India’s policy and outlook
After a meeting with Vishal Sikka, former Infosys CEO and founder of Vianai Systems, on Saturday, PM Modi tweeted (check the screenshot below):
India’s push towards AI leadership is embodied in the IndiaAI Mission, launched last year to accelerate advancements in the sector. The Union Cabinet, chaired by PM Modi, approved over ₹10,300 crore for the initiative, marking a significant investment in building the country’s AI ecosystem. The Mission will be implemented by ‘IndiaAI’ Independent Business Division (IBD) under Digital India Corporation (DIC) and has the following components as described in the graph below:
As per some estimates, in 2025, the primary focus of AI investments for Indian organizations will center on enhancing customer experience (27%), planning and strategy (16%) and optimization of IT functions (16%). To realize these goals, organizations must address key challenges, including data accessibility issues (46%), limited AI skills (42%) and difficulty in integration and scaling (38%).
But the way forward is challenging..
AI development is energy-intensive, with large-scale model training and deployment contributing to significant carbon emissions, raising sustainability concerns.
Last year, several cutting-edge large language models like OpenAI’s GPT itself were launched, including Microsoft’s AI-powered Bing, Google’s Bard, and OpenAI’s GPT-4. These are more sophisticated than their predecessors from the 1950s, and are revolutionary in processing and generating human-like text.
But the other side of this efficiency and excellence is a huge economic cost: data centers operate 24/7 and are significant energy consumers, primarily powered by fossil fuels. They account for 2.5 to 3.7 percent of global greenhouse gas emissions, surpassing the aviation industry. Most energy in data centers is used by processors and chips, as AI systems process information through binary states (you know those zeros and ones?).
There are some serious ethical concerns attached with the AI boom too. Key issues include bias in algorithms, where AI systems harbour a lack of transparency (it’s called a "black box" for that reason). It makes decisions difficult to understand or explain or to be answerable. Data privacy is another major concern, as AI often relies on vast amounts of personal data (sometimes collected without consent!) leading to risks like identity theft and surveillance.
These issues like bias in algorithms, misuse for surveillance, lack of transparency, and potential harm to societal harmony need their own fair share of stage in the hype around these rapid AI revolutions.
Despite all the hopes and optimism, challenges are rampant and sprawling. But no one can deny that the future of the world is for AI to lead!
Stay tuned until the AI era!
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Interesting perspective :)