The AI-fication of Jobs by Huy Nguyen Trieu Preparing Ourselves for the Future of Work
What's it about?
The AI-fication of Jobs (2024) unpacks the seismic shifts AI is bringing to the job market, from mass automation to the rise of supercharged professionals. It serves as both a wake-up call and a guide, showing readers how to embrace AI-driven change and thrive in the careers of tomorrow.
Experts predict that AI will impact up to 60 percent of jobs in developed economies, with half of these jobs being enhanced productivity-wise and the other half potentially being eliminated altogether.
While predictions like these may seem abstract, they represent real lives, careers, and communities. The challenge we face is to recognize the gravity of these shifts and engage thoughtfully with AI’s potential, ensuring that society, not just technologists, drives the conversation.
To navigate this transformation, we must shift our perspective and embrace three key trends: mass displacement, supercharged professionals using AI to increase productivity, and creative disruptors who leverage AI for innovation. The future of work isn’t something to fear but something we must actively shape, and this lesson aims to guide us in doing just that.
To understand the specific kind of impact that AI can have on jobs and society in general, it’s helpful to look to the past and see what’s happened in these kinds of situations before. In particular, we can look at three different industrial revolutions.
The first one happened in the early nineteenth century, when mechanization first began to threaten jobs in areas like the textile industry. The English Luddites, who got their name from a protester named Ned Ludd, raged against the machines. But their rebellion wasn’t just about smashing equipment; they were talented artisans fighting for their survival.
Yet, despite their efforts, there was no stopping the first Industrial Revolution. By the mid-1800s, the skilled crafts the Luddites had fought to preserve were mostly replaced by mass production, leaving many artisans displaced and impoverished.
When we zoom out though, a bigger picture emerges. Mechanization also boosted productivity and enabled economic growth on an unprecedented scale. On the whole, more jobs were created than lost. The costs were steep for some, but for British society in general, the first Industrial Revolution laid the foundation for modern economic prosperity.
Fast forward to the second Industrial Revolution, in the early twentieth century, and we see the pattern repeating. The rise of electricity, steel, and the further expansion of mass production methods created millions of jobs, transforming manufacturing into the backbone of the global economy.
While factory work brought opportunities for many, it also devalued skilled craftsmanship. So we ended up with clear winners and losers. The winners were the engineers, managers, and industrial workers in booming sectors like automobiles and chemicals. And the losers were the artisans and agricultural workers, whose trades were overshadowed by machines and urbanization.
Then came the Third Industrial Revolution, starting in the mid twentieth century and driven by the internet and digital technologies. Computers and automation reshaped industries, creating high-paying jobs in fields like software development while decimating middle-skilled roles like clerical work. Digitalization opened doors for some while slamming them shut for others. Those who couldn’t adapt faced declining wages and limited opportunities, widening the gap between high- and low-paid workers.
Still, throughout all these revolutions, overall employment rates remained surprisingly stable. Jobs didn’t disappear – they shifted. Societies found new ways to adapt, with emerging industries offsetting losses in older ones.
But the transitions were rarely smooth. Wage inequality grew with each technological leap, leaving some thriving while others struggled to keep up. Now, as we enter the era of AI, history offers valuable lessons. Like the industrial revolutions before it, AI will reshape work. But as we’ll see in the next section, this time will be different.
The debate over AI and jobs boils down to two camps: those who say “We’ve Seen It Before” and those who believe “This Time It’s Different”. Even the so-called three godfathers of AI – Yoshua Bengio, Geoffrey Hinton, and Yann LeCun – are split between these two sides.
The “We’ve Seen It Before” camp sees AI as part of the historical pattern – disruptive at first, but ultimately a driver of job creation and economic growth. They say AI will displace some jobs but create new industries and opportunities, just like the steam engine, electricity, and the Internet before it. In this camp you’ll find optimists like Yann LeCun and Bill Gates.
Then there’s the “This Time It’s Different” camp. They argue that AI isn’t just another tool – it’s fundamentally different. Why? Because AI doesn’t just transform industries; it replicates human skills directly, putting individual roles at risk in ways we’ve never seen before. On this side of the debate you’ll find Geoffrey Hinton, who left Google in protest in 2023, raising alarms about the pace of AI development and its potential risks, as well as fellow AI pioneer Yoshua Bengio. Elon Musk is also firmly in the “This Time It’s Different” camp, warning that AI could disrupt society on an existential scale.
The author Huy Nguyen Trieu also believes that this time is different. The main reason lies in AI’s unique transmission mechanism. Past technologies reshaped industries first. That reshaping would ripple out to affect workers, but it could lead to new industries and more jobs in the long run. AI, however, skips this step. It directly targets individual tasks and roles, leaving the industries doing the same kind of work, just with fewer human beings. Many jobs, including customer service representatives, translators, and even fashion models, are already seeing their entire professions change as companies experiment with AI-generated models.
AI doesn’t just improve tools or processes – it substitutes human expertise. Unlike previous shifts, this AI-fication of jobs challenges the value of human skills outright. This change is profound, personal, and happening faster than it ever has before.
No one can predict the future, but we do live in an age where models can give us a good idea of how certain scenarios might play out. The CDE Innovation Prism is one such model, and it offers a practical framework to make sense of how AI might affect us.
The model breaks innovation into three categories: Cheaper/Better/Faster (C), Different (D), and Enhancing (E). By examining these categories, we can better understand how new technologies disrupt markets and create opportunities.
Cheaper/Better/Faster innovations focus on efficiency. Disruptors target specific market inefficiencies, unbundle services to improve quality or price, and eventually rebundle to expand their reach. Think of Amazon: it started with books, offering a faster and more affordable way to shop, then grew into a global powerhouse. AI fits this model when it directly competes with human labor by offering cheaper, faster alternatives to tasks once done by people.
Next we have Different innovations, which break the mold entirely. These are the bold, transformative ideas – like Facebook reinventing social interaction or the iPhone defining the smartphone era. Disruptors take risks and face high uncertainty, but when successful, they don’t just improve industries; they redefine them. AI could follow this path by generating entirely new roles or sectors we haven’t yet imagined.
Enhancing innovations, meanwhile, amplify what already exists. They help incumbents adapt by improving productivity or accessibility. Think of Salesforce, which optimized workplace efficiency for businesses. AI could work as an enhancer rather than a replacer of human work. It could automate the repetitive tasks in someone’s job and provide tools for smarter decision-making, enabling companies and individuals to achieve more.
Whether AI is competing, creating, or enhancing, the CDE Prism gives us a structured way to understand its impact and prepare for the future. With this framework in mind we’ll jump into the next section.
As we’ve just seen, the ‘C’ in the CDE Innovation Prism stands for Cheaper/Better/Faster. When applied to AI, this means using the technology purely as a means of efficiency and cost reduction. AI can streamline tasks, improve accuracy, and often outperform humans in repetitive or data-heavy roles. Think about customer service chatbots or AI-powered data entry. These tools can work 24/7, in multiple languages, and at a fraction of the cost of hiring people.
The clothing company Mango already uses AI to create marketing campaigns without the need for photographers or models. In this mode, AI means big savings for businesses, but it can also lead to massive job displacement, especially for roles that are routine or predictable.
But it doesn’t have to be this way. When AI is used for Enhancing – the ‘E’ in CDE – we get collaboration between AI and humans. Here, AI acts as a tool to augment human capabilities – making our jobs faster, easier, and more efficient.
A great example is GitHub Copilot, which helps developers write code more effectively, boosting their productivity by over 25 percent. Similarly, in consulting, AI helps professionals analyze massive datasets, enabling them to deliver better results without replacing their expertise. The key here is that AI works with people, not against them.
Now we get to Different – the ‘D’ in CDE. Here, things get more speculative and unpredictable. What we’re looking at are ways in which AI can reshape the job market – not necessarily with an eye toward doing things faster or cheaper, but in ways that create whole new possibilities. Can AI innovations go beyond simply improving what we already have? Can it lead to entirely new products, services, and industries?
Think of things like AlphaFold 2, where AI revolutionized protein folding and led to new drug discoveries. Or self-driving cars that could reshape transportation. These kinds of breakthroughs don’t just tweak how we work; they change what we think is even possible. And while it’s thrilling, it can also go in any number of directions. AI like this can displace jobs but also lead to new forms of collaboration.
In our rapidly evolving workplace, knowing the different ways AI can innovate is an advantage. This is what we’ll look at in the last section: ways in which you can prepare yourself to be among those who are working alongside AI in creative, strategic, and problem-solving roles.
The fact of the matter is, AI is shaking up the world of work, and it’s happening fast. Unlike how we ignored the warnings about climate change decades ago, we need to act now. It’s not too late.
AI has the potential to solve massive global challenges, from advancing healthcare to reducing energy waste. But if we sit back and let it unfold without intervention, we risk deepening inequality, displacing millions of workers, and unraveling the social fabric of our societies.
Right now, tech giants like OpenAI, Google, and Microsoft are in an arms race, pushing AI to outpace human capabilities. While this innovation is exciting, it also runs a very serious risk of emphasizing business and money interests to the detriment of society.
This leaves us with two choices: passivity or action. If we’re passive, AI’s wealth and power will remain concentrated among tech elites, while the rest of us grapple with uncertainty. But if we actively shape its development, we can create a future where AI serves humanity – not just corporate profits.
Taking action means policymakers creating regulations to ensure AI’s benefits are shared equitably and accessibly. Businesses must invest in human-AI collaboration and help employees reskill so that they can collaborate with AI, not be replaced by AI. We should all be advocating for ethical practices, and pushing AI leaders toward solving societal challenges rather than just making profits. The future of AI is in our hands, and the choices we make today will determine whether AI means abundance for all, or for the few.
What we can also do is prepare ourselves for the ways in which AI can supercharge our careers. Becoming a supercharged professional isn’t about competing with AI – it’s about working alongside it to amplify your capabilities. Here’s how to make it happen:
First, focus on your domain expertise. Think of your field – whether it’s marketing, healthcare, engineering, or education – as your foundation. Deep industry knowledge gives you the edge to apply AI effectively and strategically, knowing how it can solve specific challenges in your work. The key here is staying curious and continually updating your skills to keep up with industry trends.
Second, develop AI literacy. You don’t need to code or build algorithms, but you do need to know how to use AI tools relevant to your role. For example, marketers might use AI for gaining customer insights, healthcare professionals might rely on AI for diagnosis support, and engineers could leverage it for design optimization. Courses, tutorials, or hands-on experimentation with AI tools can help you get comfortable with this tech.
Third, adopt a lifelong learning mindset. AI is evolving quickly, and the roles we’re familiar with today will continue to shift. Staying adaptable is essential. That means regularly exploring new tools, attending workshops, or networking with professionals who are ahead of the curve.
Lastly, blend your human skills with AI-driven efficiency. Soft skills like creativity, problem-solving, communication, and emotional intelligence are irreplaceable and highly valuable in an AI-powered world. By combining these strengths with AI’s analytical power, you can position yourself as indispensable.
Becoming a supercharged professional isn’t just a strategy – it’s a mindset. It’s about seeing AI as a partner, not a competitor, and leveraging its capabilities to thrive, innovate, and stay ahead of the curve. In the end, AI doesn’t have to be about replacing jobs; it can be about transforming how we work. How it all turns out is up to us.
The main takeaway of this lesson to The AI-fication of Jobs by Huy Nguyen Trieu is that unlike previous industrial revolutions, AI is different in that it brings change that doesn’t start at the industry level, but rather at the human level by directly replacing human skills.
The future of AI can be seen in three different categories: Cheaper/Better/Faster AI, which leads to the most job displacement, Different AI, which leads to wholly new innovations, and Enhancing AI, which leads to collaborative relationships and supercharged professionals.
There’s little doubt that AI will drastically transform the workforce, but with a better understanding, it’s possible that we can still see it as a cooperative tool rather than a threat of displacement. While we need to upskill workers so that they can excel as AI collaborators, we must also address the broader societal challenges and create policies and ethical practices that prevent mass displacement. This way, we can guide AI development so that it serves the collective good, avoiding a future where the benefits of AI are concentrated in the hands of a few. The future of work is not something to fear but something to shape.
Okay, that’s it for this lesson. We hope you enjoyed it. If you can, please take the time to leave us a rating – we always appreciate your feedback. See you in the next lesson.
The AI-fication of Jobs (2024) unpacks the seismic shifts AI is bringing to the job market, from mass automation to the rise of supercharged professionals. It serves as both a wake-up call and a guide, showing readers how to embrace AI-driven change and thrive in the careers of tomorrow.
Experts predict that AI will impact up to 60 percent of jobs in developed economies, with half of these jobs being enhanced productivity-wise and the other half potentially being eliminated altogether.
While predictions like these may seem abstract, they represent real lives, careers, and communities. The challenge we face is to recognize the gravity of these shifts and engage thoughtfully with AI’s potential, ensuring that society, not just technologists, drives the conversation.
To navigate this transformation, we must shift our perspective and embrace three key trends: mass displacement, supercharged professionals using AI to increase productivity, and creative disruptors who leverage AI for innovation. The future of work isn’t something to fear but something we must actively shape, and this lesson aims to guide us in doing just that.
To understand the specific kind of impact that AI can have on jobs and society in general, it’s helpful to look to the past and see what’s happened in these kinds of situations before. In particular, we can look at three different industrial revolutions.
The first one happened in the early nineteenth century, when mechanization first began to threaten jobs in areas like the textile industry. The English Luddites, who got their name from a protester named Ned Ludd, raged against the machines. But their rebellion wasn’t just about smashing equipment; they were talented artisans fighting for their survival.
Yet, despite their efforts, there was no stopping the first Industrial Revolution. By the mid-1800s, the skilled crafts the Luddites had fought to preserve were mostly replaced by mass production, leaving many artisans displaced and impoverished.
When we zoom out though, a bigger picture emerges. Mechanization also boosted productivity and enabled economic growth on an unprecedented scale. On the whole, more jobs were created than lost. The costs were steep for some, but for British society in general, the first Industrial Revolution laid the foundation for modern economic prosperity.
Fast forward to the second Industrial Revolution, in the early twentieth century, and we see the pattern repeating. The rise of electricity, steel, and the further expansion of mass production methods created millions of jobs, transforming manufacturing into the backbone of the global economy.
While factory work brought opportunities for many, it also devalued skilled craftsmanship. So we ended up with clear winners and losers. The winners were the engineers, managers, and industrial workers in booming sectors like automobiles and chemicals. And the losers were the artisans and agricultural workers, whose trades were overshadowed by machines and urbanization.
Then came the Third Industrial Revolution, starting in the mid twentieth century and driven by the internet and digital technologies. Computers and automation reshaped industries, creating high-paying jobs in fields like software development while decimating middle-skilled roles like clerical work. Digitalization opened doors for some while slamming them shut for others. Those who couldn’t adapt faced declining wages and limited opportunities, widening the gap between high- and low-paid workers.
Still, throughout all these revolutions, overall employment rates remained surprisingly stable. Jobs didn’t disappear – they shifted. Societies found new ways to adapt, with emerging industries offsetting losses in older ones.
But the transitions were rarely smooth. Wage inequality grew with each technological leap, leaving some thriving while others struggled to keep up. Now, as we enter the era of AI, history offers valuable lessons. Like the industrial revolutions before it, AI will reshape work. But as we’ll see in the next section, this time will be different.
The debate over AI and jobs boils down to two camps: those who say “We’ve Seen It Before” and those who believe “This Time It’s Different”. Even the so-called three godfathers of AI – Yoshua Bengio, Geoffrey Hinton, and Yann LeCun – are split between these two sides.
The “We’ve Seen It Before” camp sees AI as part of the historical pattern – disruptive at first, but ultimately a driver of job creation and economic growth. They say AI will displace some jobs but create new industries and opportunities, just like the steam engine, electricity, and the Internet before it. In this camp you’ll find optimists like Yann LeCun and Bill Gates.
Then there’s the “This Time It’s Different” camp. They argue that AI isn’t just another tool – it’s fundamentally different. Why? Because AI doesn’t just transform industries; it replicates human skills directly, putting individual roles at risk in ways we’ve never seen before. On this side of the debate you’ll find Geoffrey Hinton, who left Google in protest in 2023, raising alarms about the pace of AI development and its potential risks, as well as fellow AI pioneer Yoshua Bengio. Elon Musk is also firmly in the “This Time It’s Different” camp, warning that AI could disrupt society on an existential scale.
The author Huy Nguyen Trieu also believes that this time is different. The main reason lies in AI’s unique transmission mechanism. Past technologies reshaped industries first. That reshaping would ripple out to affect workers, but it could lead to new industries and more jobs in the long run. AI, however, skips this step. It directly targets individual tasks and roles, leaving the industries doing the same kind of work, just with fewer human beings. Many jobs, including customer service representatives, translators, and even fashion models, are already seeing their entire professions change as companies experiment with AI-generated models.
AI doesn’t just improve tools or processes – it substitutes human expertise. Unlike previous shifts, this AI-fication of jobs challenges the value of human skills outright. This change is profound, personal, and happening faster than it ever has before.
No one can predict the future, but we do live in an age where models can give us a good idea of how certain scenarios might play out. The CDE Innovation Prism is one such model, and it offers a practical framework to make sense of how AI might affect us.
The model breaks innovation into three categories: Cheaper/Better/Faster (C), Different (D), and Enhancing (E). By examining these categories, we can better understand how new technologies disrupt markets and create opportunities.
Cheaper/Better/Faster innovations focus on efficiency. Disruptors target specific market inefficiencies, unbundle services to improve quality or price, and eventually rebundle to expand their reach. Think of Amazon: it started with books, offering a faster and more affordable way to shop, then grew into a global powerhouse. AI fits this model when it directly competes with human labor by offering cheaper, faster alternatives to tasks once done by people.
Next we have Different innovations, which break the mold entirely. These are the bold, transformative ideas – like Facebook reinventing social interaction or the iPhone defining the smartphone era. Disruptors take risks and face high uncertainty, but when successful, they don’t just improve industries; they redefine them. AI could follow this path by generating entirely new roles or sectors we haven’t yet imagined.
Enhancing innovations, meanwhile, amplify what already exists. They help incumbents adapt by improving productivity or accessibility. Think of Salesforce, which optimized workplace efficiency for businesses. AI could work as an enhancer rather than a replacer of human work. It could automate the repetitive tasks in someone’s job and provide tools for smarter decision-making, enabling companies and individuals to achieve more.
Whether AI is competing, creating, or enhancing, the CDE Prism gives us a structured way to understand its impact and prepare for the future. With this framework in mind we’ll jump into the next section.
As we’ve just seen, the ‘C’ in the CDE Innovation Prism stands for Cheaper/Better/Faster. When applied to AI, this means using the technology purely as a means of efficiency and cost reduction. AI can streamline tasks, improve accuracy, and often outperform humans in repetitive or data-heavy roles. Think about customer service chatbots or AI-powered data entry. These tools can work 24/7, in multiple languages, and at a fraction of the cost of hiring people.
The clothing company Mango already uses AI to create marketing campaigns without the need for photographers or models. In this mode, AI means big savings for businesses, but it can also lead to massive job displacement, especially for roles that are routine or predictable.
But it doesn’t have to be this way. When AI is used for Enhancing – the ‘E’ in CDE – we get collaboration between AI and humans. Here, AI acts as a tool to augment human capabilities – making our jobs faster, easier, and more efficient.
A great example is GitHub Copilot, which helps developers write code more effectively, boosting their productivity by over 25 percent. Similarly, in consulting, AI helps professionals analyze massive datasets, enabling them to deliver better results without replacing their expertise. The key here is that AI works with people, not against them.
Now we get to Different – the ‘D’ in CDE. Here, things get more speculative and unpredictable. What we’re looking at are ways in which AI can reshape the job market – not necessarily with an eye toward doing things faster or cheaper, but in ways that create whole new possibilities. Can AI innovations go beyond simply improving what we already have? Can it lead to entirely new products, services, and industries?
Think of things like AlphaFold 2, where AI revolutionized protein folding and led to new drug discoveries. Or self-driving cars that could reshape transportation. These kinds of breakthroughs don’t just tweak how we work; they change what we think is even possible. And while it’s thrilling, it can also go in any number of directions. AI like this can displace jobs but also lead to new forms of collaboration.
In our rapidly evolving workplace, knowing the different ways AI can innovate is an advantage. This is what we’ll look at in the last section: ways in which you can prepare yourself to be among those who are working alongside AI in creative, strategic, and problem-solving roles.
The fact of the matter is, AI is shaking up the world of work, and it’s happening fast. Unlike how we ignored the warnings about climate change decades ago, we need to act now. It’s not too late.
AI has the potential to solve massive global challenges, from advancing healthcare to reducing energy waste. But if we sit back and let it unfold without intervention, we risk deepening inequality, displacing millions of workers, and unraveling the social fabric of our societies.
Right now, tech giants like OpenAI, Google, and Microsoft are in an arms race, pushing AI to outpace human capabilities. While this innovation is exciting, it also runs a very serious risk of emphasizing business and money interests to the detriment of society.
This leaves us with two choices: passivity or action. If we’re passive, AI’s wealth and power will remain concentrated among tech elites, while the rest of us grapple with uncertainty. But if we actively shape its development, we can create a future where AI serves humanity – not just corporate profits.
Taking action means policymakers creating regulations to ensure AI’s benefits are shared equitably and accessibly. Businesses must invest in human-AI collaboration and help employees reskill so that they can collaborate with AI, not be replaced by AI. We should all be advocating for ethical practices, and pushing AI leaders toward solving societal challenges rather than just making profits. The future of AI is in our hands, and the choices we make today will determine whether AI means abundance for all, or for the few.
What we can also do is prepare ourselves for the ways in which AI can supercharge our careers. Becoming a supercharged professional isn’t about competing with AI – it’s about working alongside it to amplify your capabilities. Here’s how to make it happen:
First, focus on your domain expertise. Think of your field – whether it’s marketing, healthcare, engineering, or education – as your foundation. Deep industry knowledge gives you the edge to apply AI effectively and strategically, knowing how it can solve specific challenges in your work. The key here is staying curious and continually updating your skills to keep up with industry trends.
Second, develop AI literacy. You don’t need to code or build algorithms, but you do need to know how to use AI tools relevant to your role. For example, marketers might use AI for gaining customer insights, healthcare professionals might rely on AI for diagnosis support, and engineers could leverage it for design optimization. Courses, tutorials, or hands-on experimentation with AI tools can help you get comfortable with this tech.
Third, adopt a lifelong learning mindset. AI is evolving quickly, and the roles we’re familiar with today will continue to shift. Staying adaptable is essential. That means regularly exploring new tools, attending workshops, or networking with professionals who are ahead of the curve.
Lastly, blend your human skills with AI-driven efficiency. Soft skills like creativity, problem-solving, communication, and emotional intelligence are irreplaceable and highly valuable in an AI-powered world. By combining these strengths with AI’s analytical power, you can position yourself as indispensable.
Becoming a supercharged professional isn’t just a strategy – it’s a mindset. It’s about seeing AI as a partner, not a competitor, and leveraging its capabilities to thrive, innovate, and stay ahead of the curve. In the end, AI doesn’t have to be about replacing jobs; it can be about transforming how we work. How it all turns out is up to us.
The main takeaway of this lesson to The AI-fication of Jobs by Huy Nguyen Trieu is that unlike previous industrial revolutions, AI is different in that it brings change that doesn’t start at the industry level, but rather at the human level by directly replacing human skills.
The future of AI can be seen in three different categories: Cheaper/Better/Faster AI, which leads to the most job displacement, Different AI, which leads to wholly new innovations, and Enhancing AI, which leads to collaborative relationships and supercharged professionals.
There’s little doubt that AI will drastically transform the workforce, but with a better understanding, it’s possible that we can still see it as a cooperative tool rather than a threat of displacement. While we need to upskill workers so that they can excel as AI collaborators, we must also address the broader societal challenges and create policies and ethical practices that prevent mass displacement. This way, we can guide AI development so that it serves the collective good, avoiding a future where the benefits of AI are concentrated in the hands of a few. The future of work is not something to fear but something to shape.
Okay, that’s it for this lesson. We hope you enjoyed it. If you can, please take the time to leave us a rating – we always appreciate your feedback. See you in the next lesson.
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