Which Jobs Will Arise and Disappear with Generative AI?
The rise of generative AI is not just a technological marvel; it’s a catalyst for change that promises to shape the future of the global workforce. As per the latest McKinsey research, generative AI could add a staggering $2.6 trillion to $4.4 trillion annually to the global economy. Given the scale of this impact, it is crucial to discuss how this specialized form of AI is set to alter the job landscape, both by eliminating some roles and creating new ones.
It is our position that it is increasingly evident that generative AI will become an integral part of all AI systems, either as specialized components or as overarching elements. For instance, generative models are already being used in data analysis pipelines to create reports and could potentially serve as ‘master algorithms’ coordinating other specialized functions. This convergence is backed by scientific focus on interoperability and AutoML, as well as growing investment in the field. As AI systems evolve in complexity, the distinction between traditional and generative AI is likely to become increasingly irrelevant.
In this blog, we will explore which jobs are most susceptible to being phased out due to generative AI, which new roles are likely to be created, and how different industries may feel the impact.
The Current State of AI in the Job Market
In the modern era, AI technologies have firmly embedded themselves into the job market’s fabric, revolutionizing the way we work, communicate, and make decisions. From streamlining operations in manufacturing plants to providing intelligent virtual assistants in customer service, AI has emerged as a game-changer across diverse industries. However, the advent of generative AI marks a seismic shift in the magnitude and depth of this influence.
Generative AI, with its inherent capabilities to create, mimic, and adapt, enhances the potential of existing AI systems by an astounding 15 to 40 percent. This isn’t just a numerical increment; it signifies a broader, deeper reach into sectors and roles that were once considered solely human domains.
Take, for instance, the creative world of content creation or intricate decision-making processes in research and development. While traditional AI systems have provided tools and assistance in these sectors, generative AI holds the promise of becoming a co-creator, collaborator, and even an innovator.
This is already being reflected in adoption rates. For example, a recent Salesforce survey of 1,000 marketers revealed that the most common use of generative AI among marketers is:
- Basic content creation (76%)
- Writing copy (76%)
- Inspiring their creative thinking (71%)
- Analyzing market data (63%)
- Generating image assets (62%)
Focusing on the business side of things, customer operations, marketing and sales, software engineering, and R&D are on the cusp of a major transformation due to generative AI. These areas alone are predicted to capture about 75 percent of the value that generative AI brings to the table. It’s not just about automating tasks but reimagining how they’re executed.
In customer operations, we can expect more personalized, intuitive interactions; in marketing and sales, there’s potential for hyper-targeted campaigns crafted with insights from AI; software engineering could witness a surge in productivity with AI drafting codes based on natural-language prompts; and R&D can leverage AI to forecast trends, simulate scenarios, and even come up with innovative solutions.
The essence here is that generative AI is not just another technological advancement but a transformative force poised to reshape industries. It offers solutions tailored to specific business challenges and ensures outcomes that are not only efficient but also measurable in their impact.
Jobs at Risk of Obsolescence
As generative AI technologies continue to advance, certain job roles are at greater risk of becoming obsolete. While this technology has the potential to augment the capabilities of individual workers and substantially increase labor productivity, it’s important to consider its impact on existing professions.
Creative Fields: Writing, Designing, Journalism
In the creative industries like writing and design, generative AI shows great promise in generating content based on natural-language prompts. Generative AI could support content creation in marketing and sales, potentially taking over jobs that involve repetitive or formulaic writing and design tasks. It can also be used to assist in journalism by pulling together and analyzing sources, creating outlines, and even helping write final pieces. While it may not completely replace human creativity, it certainly raises questions about the value of routine creative work.
Data Analysis
The banking and high-tech industries could be particularly impacted by generative AI, with a potential value addition ranging from $200 billion to $340 billion annually. In data analysis, generative AI’s capability to mine large datasets and identify patterns could automate what was once a labor-intensive job. The technology can also forecast trends and generate data visualizations, which may limit the need for specialized data analysts in the future.
Customer Service
Customer service roles could see drastic changes as well. Generative AI has shown proficiency in supporting interactions with customers. For instance, AI-powered chatbots can handle customer queries more efficiently, thereby reducing the need for human operators in call centers. Generative AI could automate work activities that currently take up 60 to 70 percent of customer service representatives’ time, enhancing efficiency but also possibly phasing out certain roles.
Automation in Manufacturing
The impact of generative AI isn’t limited to white-collar jobs. In manufacturing, automation technologies have already begun replacing some blue-collar jobs. Generative AI takes this a step further by potentially automating complex tasks that require an understanding of natural language or intricate patterns. In the long term, this could reduce the number of blue-collar jobs in manufacturing sectors, although the full extent of this is still being studied.
Transportation Industry
The rise of self-driving vehicles and AI in the transportation sector poses a significant threat to jobs, particularly for truck drivers, taxi drivers, and various other roles. Studies from Oxford University and Deloitte suggest that up to 47% of the workforce could be displaced. Mitigation strategies like a robot tax and Universal Basic Income (UBI) are being discussed to offset the impact. The rapid adoption of AI technologies could lead to widespread job displacement, but solutions are being considered.
It’s clear that generative AI holds significant potential to reshape the job market. According to the McKinsey report on the economic potential of generative AI, updated adoption scenarios suggest that half of today’s work activities could be automated between 2030 and 2060, largely due to generative AI’s increased ability to understand natural language. While this presents numerous opportunities for efficiency and productivity, it also poses challenges that need to be managed carefully, such as workforce transition and re-skilling.
Emerging Job Roles due to Generative AI
While generative AI threatens to make some job roles obsolete, it’s crucial to remember that technological advancements also create new opportunities. In fact, as we mentioned, McKinsey research estimates that generative AI could add between $2.6 trillion to $4.4 trillion annually to the global economy, providing new avenues for employment and productivity. Here, we examine some of the emerging job roles that owe their existence to the rise of generative AI technologies.
Prompt Engineers
As generative AI becomes increasingly integrated into various business functions, there will be a growing need for experts who can optimize human-AI interactions. Prompt engineers specialize in crafting precise and impactful prompts to guide generative AI models effectively. Their work ensures that AI tools align with business goals and produce specific, useful outputs.
AI Trainers
AI models don’t just become effective autonomously; they require training to operate efficiently. AI trainers are responsible for fine-tuning generative AI systems, using both data and expertise to improve the model’s performance. They focus on training the AI to understand nuances and complexities, thereby making the technology more effective and reliable.
Generative Design Architects
In industries like manufacturing, construction, and even fashion, generative design architects use AI to generate various design options based on a set of input parameters. The AI can then run simulations to determine which designs are most efficient or effective, revolutionizing the iterative design process and potentially adding a value of $400 billion to $660 billion a year in the retail and consumer packaged goods sectors alone, according to the McKinsey report.
Data Curators for AI
Given that generative AI relies heavily on data, the role of data curators becomes increasingly significant. These professionals are responsible for sourcing, cleaning, and maintaining the data that feeds into AI models. They work to ensure that the data is representative and free from biases, thus improving the accuracy and reliability of generative AI systems.
Ethics Compliance Managers
As generative AI takes on a larger role in decision-making processes, ethical considerations become more important than ever. Ethics Compliance Managers will be responsible for ensuring that AI systems are developed and deployed in a manner that adheres to ethical guidelines and regulations. This includes safeguarding against biases, protecting data privacy, and ensuring transparency in AI operations.
Emerging roles like these indicate that while generative AI has the potential to automate up to 60 to 70 percent of tasks in certain jobs (McKinsey, “The economic potential of generative AI”, June 2023), it also opens new doors for specialized roles that didn’t exist before. It’s an exciting frontier, but one that will require investments in worker retraining and skills development to fully realize its benefits.
Sector-Specific Impacts of Generative AI
As generative AI continues to mature and find applications across diverse sectors, its impact is felt everywhere from healthcare to logistics. Let’s delve into the transformative effects this technology is expected to have on various industries:
- Healthcare: Generative AI can be a game-changer for the healthcare industry. Whether it’s in drug discovery, where AI can predict molecular interactions, or in personalized patient care, where AI can generate treatment plans tailored to individual health profiles, the potential is immense. Furthermore, with the ability to analyze vast datasets, generative AI could aid in early disease detection, understanding health trends, and predicting disease outbreaks.
- Finance: Banking and finance stand to gain significantly from generative AI. The big annual value added to the banking sector might come in the form of AI-driven financial advisors, fraud detection systems, or generative models that can predict stock market trends based on a plethora of factors.
- Retail: In the retail sector, generative AI holds the promise of revolutionizing the shopping experience. Imagine a system that can generate personalized shopping lists based on your preferences or predict fashion trends based on global data analysis.
- Education: Generative AI in education could mean personalized learning paths for students, where the AI generates content and resources tailored to an individual’s learning pace and style. Additionally, it can assist educators in creating lesson plans, grading assignments, and providing automated feedback to students, allowing for more one-on-one time with learners.
- Transportation and Logistics: Generative AI’s potential in transportation and logistics revolves around optimizing routes, predicting maintenance needs, and even aiding in the design of vehicles. With the ongoing development of autonomous vehicles, generative AI can play a crucial role in simulating countless driving scenarios to train these vehicles, ensuring safety and efficiency.
While these sector-specific impacts highlight the promise of generative AI, they also underscore the importance of businesses and industries to adapt and evolve. The pace of workforce transformation will likely accelerate, with technological feasibility, economic considerations, and adoption timelines reshaping industries faster than ever before.
The Duality of Technological Advancements
Historically, every significant technological advancement has presented a dual-natured impact on society. The introduction of the printing press, the industrial revolution, and the dawn of the internet age — all came with their respective challenges and opportunities. Generative AI is no exception to this trend.
At its core, generative AI is a tool, and its impact on the job landscape hinges on how society chooses to harness its capabilities. On one hand, it offers unprecedented potential in terms of productivity, innovation, and growth. The prospect of adding trillions of dollars in value to the global economy stands as a testament to this potential. On the other hand, without thoughtful and deliberate application, generative AI could lead to job displacements, further income disparities, and a host of societal challenges.
This duality underscores the importance of a balanced approach. The goal should be to leverage generative AI to unlock new horizons of possibilities while simultaneously safeguarding the workforce and ensuring a fair distribution of benefits.
A recent McKinsey report (”Generative AI and the future of work in America”, July 26, 2023) shows the impact of generative AI on various sectors in the U.S. job market. It suggests that while generative AI will accelerate automation, it’s not expected to result in significant job losses. Instead, it’s likely to enhance roles in STEM, creative, and business and legal professions. The healthcare sector is poised for substantial growth, with an estimated 3.5 million more jobs needed by 2030. Conversely, jobs in office support, customer service, and food services are expected to decline.
You can read the full report here.
A Convergence of Strategy and Action
As we peer into the future, the profound impact of generative AI on the job landscape is unmistakable. However, the direction of this impact — whether it’s predominantly positive or negative — rests largely on collective decisions and it’s not predetermined or inevitable.
Policymakers play a crucial role in shaping this trajectory. Their decisions can foster an environment that promotes innovation while protecting workers’ rights. Corporate strategies will dictate how businesses integrate AI into their operations, either as a force that displaces employees or as a tool that augments human capabilities. And on an individual level, foresight and adaptability will determine how well one navigates the evolving job market.
It is a fact that the absence of legislation around generative AI is a pressing concern that can sway its impact on jobs. Lack of regulation risks unchecked automation and job losses, while thoughtful legislation can guide AI to augment human labor. The most glaring legislative gaps lie in ethical guidelines, re-skilling programs, and data privacy. Without ethical standards, AI could be misused, leading to societal issues. The absence of mandated re-skilling programs leaves workers vulnerable to job displacement. Lastly, data privacy remains a grey area, especially in sensitive sectors like healthcare and finance. Legislation can serve as a crucial guidepost for responsible AI deployment.
The era of generative AI is just beginning. Its ripples will be felt across every industry and every job role. As readers, it’s imperative to not only understand these changes but to actively prepare for them. Consider the skills and roles that will emerge, and those that might become obsolete. Think critically about where you fit into this landscape and chart a path that ensures your relevance in the world reshaped by AI. This isn’t just a call to adapt; it’s a call to thrive in the age of generative AI.
