The advent of artificial intelligence (AI) has ushered in a new era of technological innovation, fundamentally altering the landscape of the job market. AI assistants, with their advanced capabilities, are at the forefront of this transformation, reshaping the way businesses operate and employees work.
One of the recurring themes of the societal discussion on generative AI is how it will transform the future of work. According to CEO of MotleyCrew, Egor Kraev it doesn’t seem too far-fetched that systems using Large Language Models (LLMs) could, for example, produce code comparable in quality to that of at least a junior programmer – and there is no shortage of investment, in both large firms and startups, into making that happen. The same holds for other knowledge workers, for example copywriters and illustrators.
AI’s journey began in the mid-20th century, but it has seen exponential growth in recent years, especially with the advent of generative AI technologies. Companies like Microsoft have recognized the potential of AI to drive efficiencies and enhance data-driven decision-making. The market for generative AI is expected to burgeon into a $1.3 trillion industry by 2032.
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Would large-scale societal disruption follow as whole segments of white-collar work are automated?
Let us start with some historical perspective. How many of our readers know what a typing pool is? These days encountered almost only in last-century detective novels, the typing pool was, before computers became commonplace, a room where typists sat, that is people whose job was to type business correspondence fast and without mistakes (as correcting typos made with a mechanical typewriter was unsightly).
With the advent of computers, one could correct errors before printing the letter (if it needed to be printed at all), and typing pools, and the profession of typist, disappeared. Did typing disappear? Of course not, but from a profession, it turned into merely a skill that people in certain jobs are supposed to possess.
Let us also consider another profession, that of a car mechanic. Once upon a time, when cars were a novelty and required constant maintenance, to own and use one, it was necessary to employ a full-time mechanic who took care of the car. As cars evolved and required ever less routine maintenance, did the profession of car mechanic disappear? On the contrary, as cars became cheaper and easier to own, the total demand for cars, and thus car mechanics, has only grown. The profession has become more demanding and highly skilled but is unlikely to become obsolete.
A combination of these two trajectories is precisely the path that many current knowledge-intensive roles, such as data analysis or programming, will follow: their basic level will go from a full-time job to a skill that people in other roles, such as product management, are simply expected to have; and their advanced level will become even more advanced and powerful, due to all the new generative AI tools available to practitioners.
Contrary to the common fear that AI will replace human jobs, the reality is more nuanced. AI is creating new job roles and augmenting existing ones, enabling workers to focus on more strategic tasks. There is a burgeoning demand for AI experts, including programmers, data scientists, and professionals well-versed in AI frameworks.
Over the last half a century or so, programming has moved from assembler (literal “copy memory address x to memory address y” kind of instructions) to languages like C++, with their explicit control over memory allocation, to simpler and more forgiving languages such as Python. Of course, use cases for assembler or C++ are still there, but someone wanting to learn coding to do, for example, data analysis these days will likely start with Python and often find it enough for their needs. As this was happening, the profession of the programmer was never in danger of becoming extinct, just like that of the car mechanic – it only changed tools – Egor Kraev.
Many other creative professions (and yes, programming is a highly creative pursuit), for example, copywriters or illustrators, as well as managerial roles, haven’t experienced a similar sort of change merely because until the current generation of Generative AI Models, Computer Algorithms just weren’t very good at working with natural language text, or with images.
Now that this has changed, we can expect a similar evolution in those professions: ever more powerful tools that take away the drudgery and leave to the human the quintessentially human part: the human dimension, the intent of the work, its strategic implications, and the judgment calls involved.
The potential impact AI goes beyond front-line jobs, too. When you think about it, how much management work in large companies can be thought of as consuming and generating text according to a set of relatively fixed (if not always explicitly written down) rules? Not all of it, certainly, but a lot.
The integration of AI into business systems has led to a significant shift in hiring trends. The Upwork Research Institute reports a 600% increase in job posts seeking generative AI skills from the fourth quarter of 2022 to the first quarter of 2023. Moreover, 49% of hiring managers surveyed indicated they would hire more independent talent and full-time employees due to generative AI.
Millennials and Gen Z are leading the conversation on AI, with the latter being particularly tech-savvy and open to embracing emerging technologies. This generational shift is crucial as it indicates a growing AI literacy among the workforce, which is essential for navigating the AI-transformed job market. Professional services, technology, and education are the sectors most actively engaging with AI. In these industries, AI is not only popular but is also driving significant changes in job functions and skill requirements.
As AI takes over routine tasks, the remaining jobs will increasingly require critical thinking and soft skills such as communication, collaboration, and problem-solving. This shift may lead to job displacement in certain roles, but it also opens up opportunities for innovation and the creation of new job categories.