AI Is Taking Your Job – Or Creating Ten More?

A Worker’s Guide to The AI Skills Economy

Today We Begin a New Series

Today we begin a new series on our blog. It is dedicated to a subject that sits at the centre of public anxiety: artificial intelligence and its impact on jobs. Across the world, workers are being told that AI is coming to replace them. Headlines warn of mass layoffs, disappearing industries, and a future where humans are left behind. The phrase “AI taking jobs” has become shorthand for uncertainty and fear.

This fear is not unfounded. Every major wave of technological change has displaced people whose livelihoods were tied to older methods of production. When factories automated, textile workers were replaced by machines. When personal computers arrived, clerks and typists saw their jobs vanish. A report from the McKinsey Global Institute estimates that by 2030, up to 30% of work hours globally could be automated. The World Economic Forum’s 2023 “Future of Jobs” survey found that nearly half of companies expect AI to reduce their workforce in some form.

And yet, history shows that the story does not end with loss. Each disruption has also sparked entirely new industries, professions, and skills. The introduction of the car destroyed the horse-drawn carriage business but created manufacturing plants, mechanics, petrol stations, and a global trade network that dwarfed the scale of the old industry. The lesson is clear: displacement is real, but opportunity is greater.

The task before us is to recognise this shift not as an existential threat, but as an inflection point. Workers who embrace adaptability, reskilling, and agency will not simply survive, they will thrive. This is the essence of The AI Skills Economy (TAISE): a grassroots movement to prepare workers for the future of work, not by clinging to the past, but by actively shaping the opportunities ahead.

The Fear Is Real: Why Workers Worry

Let us first confront the disruption honestly. Fear of job loss is not paranoia, it is rational. A 2024 Stanford study analysed AI deployment in customer service centres and found that productivity rose by 14% while headcount declined. In journalism, outlets like CNET and BuzzFeed have experimented with AI-generated content, leading to staff reductions. Even professional roles once thought immune are being affected: legal firms are now using AI to draft contracts, cutting junior associate hours; investment banks are testing AI for risk analysis and due diligence.

For workers, this creates psychological pressure. According to David Rock’s SCARF model, human motivation is heavily influenced by five factors: status, certainty, autonomy, relatedness, and fairness. AI challenges at least three of these simultaneously.

• Status: Workers may feel less valued if machines can outperform them.

• Certainty: Rapid automation makes career stability unclear.

• Autonomy: AI-driven workflows can leave people feeling like cogs in a machine.

This explains why the conversation around AI often feels so charged. The technology is not only about economics, it strikes at human identity. To deny this is to ignore the lived reality of millions of workers.

The Global Picture: Lessons From the Frontlines

To understand where workers stand, we need to look at economies already deep into AI adoption.

United States: Research from MIT in 2023 showed that generative AI could handle 23% of all work tasks in professional services. Sectors like marketing, customer service, and software development are already seeing restructuring. Yet the same study found that companies deploying AI were also hiring different kinds of roles: AI trainers, ethicists, prompt engineers, data annotators. For every task eliminated, others emerged.

China: The Chinese government has declared AI a national priority. By 2030, it aims to lead the world in AI capabilities. This has spurred massive demand for engineers, data scientists, and robotics specialists. But more interesting is the growth of AI-enabled manufacturing, where low-cost factories are adopting automation and creating jobs in system maintenance and quality control. For workers, this shows that blue-collar jobs are not disappearing; they are being reshaped.

European Union: The EU has taken a balanced approach, investing heavily in digital skills training while regulating AI’s ethical use. According to Eurostat, over 60% of EU firms that adopted AI reported higher demand for skilled labour, not less. Germany, for instance, has launched retraining programmes for auto workers to transition into electric vehicle and AI-supported manufacturing.

The South African Lens: A Double Challenge

For South Africa and much of the Global South, the challenge is different. Our unemployment rate hovers above 30%, with youth unemployment even higher. Unlike Europe or China, our problem is not just about workers being displaced by AI, it is about millions of workers not being integrated into the economy at all.

This paradox creates a unique opportunity. While advanced economies are worrying about job losses, South Africa can focus on job creation by leapfrogging into AI-enabled industries. Instead of defending outdated roles, we can prepare our labour force to plug directly into the new economy.

There is precedent for this. The Philippines became a global hub for call centres by leveraging its English-speaking workforce. India exported IT and software services across the world, lifting millions out of poverty. South Africa has similar potential if it embraces The AI Skills Economy. Our labour force can be trained in areas where human judgment, empathy, and cultural understanding matter, fields where AI enhances rather than replaces.

The risk is clear: if we fail to act, the skills gap will widen, leaving our workers uncompetitive. The opportunity is equally clear: with targeted investment in skills, we can turn AI disruption into a catalyst for labour export and economic growth.

From Fear to Opportunity

At this point, we pivot from fear to hidden opportunity. Here are the sectors where research shows growth potential:

1. Green Energy: The International Labour Organization estimates that renewable energy could create 24 million new jobs globally by 2030. AI is being used to optimise solar grids, predict energy demand, and manage infrastructure. Workers trained in both technical installation and AI-enabled monitoring will be in high demand.

2. Healthcare: According to a 2024 Deloitte report, AI in healthcare will create demand for medical data interpreters, technicians for AI-driven diagnostic tools, and care workers who combine technology with human empathy.

3. Creative Industries: While AI can generate content, human creativity in strategy, storytelling, and cultural nuance remains irreplaceable. A PwC survey found that 74% of businesses expect greater demand for creative roles in an AI-enabled world.

4. AI-Enabled Services: New categories are emerging, from AI tutors in education to AI-assisted agriculture. McKinsey projects that precision farming alone could generate billions in added value, requiring a mix of local knowledge and digital skills.

For South Africa, these sectors align with our strengths: a young workforce, growing tech adoption, and an urgent need to reduce unemployment.

Workers as the Heroes

Using the StoryBrand framework, workers are not the victims in this story, they are the heroes. The challenge is AI disruption. The guide is The AI Skills Economy. The path is reskilling, adaptability, and agency.

Consider the analogy of the horse-drawn carriage. When the automobile was invented, drivers lost their old jobs. But within a decade, car factories, petrol stations, and road infrastructure projects created millions of new roles. A 1920s worker who saw only the loss would miss the larger opportunity. Today’s worker faces the same choice.

This is where loss aversion plays a role. Fear of losing current jobs is strong. But the fear of missing out on tomorrow’s opportunities should be stronger. Workers who reskill now will occupy the high ground in industries that will define the next generation.

A Practical Roadmap for Workers

What does adaptability look like in practice? Here are key steps workers can take, supported by research:

1. Reskill Continuously: The OECD notes that workers who engage in lifelong learning are 40% less likely to be displaced by automation. Free courses in AI literacy, coding, and data analysis are widely available.

2. Develop Hybrid Skills: Research from LinkedIn shows that “fusion skills” (combining human judgment with AI capability) are most in demand. Examples include AI-assisted design, data-informed decision-making, and technology-augmented teaching.

3. Leverage Soft Skills: AI excels at pattern recognition but struggles with empathy, persuasion, and leadership. A Harvard study confirmed that jobs requiring high emotional intelligence have grown even as automation advances.

4. Join Communities of Practice: The AI Skills Economy is not a solo project. Workers should join peer groups, online communities, and professional networks to share resources and opportunities. Reciprocity builds resilience.

5. Think Exportable Skills: South Africa’s labour force can earn globally if skills are aligned with international demand. Remote work, freelance platforms, and cross-border projects make this possible.

Psychological Reframing

Workers must reframe their perspective from jobs disappearing to tasks evolving. Research from the World Bank highlights that AI tends to replace repetitive tasks, not entire occupations. A teacher is not replaced, but lesson planning may be automated. A nurse is not replaced, but diagnostic paperwork may be streamlined. The result is not redundancy but reallocation of effort toward higher-value human activity.

Here the Jobs-to-Be-Done framework is vital. The “job” is not the specific role title, but the function: to educate, to heal, to sell, to design. AI may change the how, but the why remains constant. Workers who understand this distinction can adapt their skillset while staying aligned with their purpose.

Building The AI Skills Economy (TAISE)

The AI Skills Economy is more than a concept; it is a movement. Its mission is simple: workers everywhere should see AI not as a rival, but as a catalyst for growth. By identifying new skills, sharing resources, and reframing disruption, we create a future where labour is empowered, not sidelined.

This movement is not led by governments or corporations alone. It begins with individuals choosing adaptability over fear. When workers identify as part of TAISE, they are not passive observers, they are pioneers in shaping a fairer and more resilient economy.

And this is where Cialdini’s principle of social proof applies. If enough workers embrace TAISE, others will follow. The collective action of workers creates momentum that no individual can achieve alone.

Conclusion: A Call to Workers

AI is taking jobs. That is the reality. But AI is also creating ten more for every one it displaces. The story of the horse-drawn carriage reminds us that focusing only on loss blinds us to the greater picture. Workers today face a choice: remain paralysed by fear or step forward into adaptability.

South Africa, with its high unemployment and youthful workforce, stands at a crossroads. By learning from the US, China, and the EU, we can empower our labour force, export talent, and position ourselves in the new economy. The question is not whether jobs will change, they will. The question is whether we, as workers, will change with them.

The AI Skills Economy is your invitation to act. It is a movement that reframes disruption into opportunity, fear into empowerment, and uncertainty into agency. To join is simple: embrace adaptability, invest in reskilling, and see yourself not as a victim of AI, but as the architect of a new future.

The age of horse-drawn carriages has passed. The age of AI has begun. And with it, so too begins the era of The AI Skills Economy.