Total Artificial Intelligence (AI) Job Displacements By 2030

The integration of AI models and quantum computing technologies will lead to significant job losses and displacement across various sectors, potentially impacting up to 555 million jobs globally by 2030. 555 million jobs are affected by AI globally by 2030.555 million jobs are affected by Ai globally by 2030.

Global Job Displacement Estimates and Sector-Specific Impacts Due to Ai

Global Job Displacement Estimates by 2030

• North America: Up to 80 million jobs

• Europe: Up to 80 million jobs

• Asia: Up to 250 million jobs

• Africa: Up to 70 million jobs

• Latin America: Up to 50 million jobs

• Middle East: Up to 25 million jobs

Sector-Specific Job Displacement Estimates

Manufacturing

• Estimated Job Losses: 20 million

• Estimated Salary Saved: $600 billion

• Sources: McKinsey, World Economic Forum

• Computer vision plays a crucial role in automation by enabling machines to analyze visual information and perform tasks with high precision. Integrating machine learning capabilities with computer vision enhances automation in manufacturing by allowing systems to adapt to new data and respond to changes in processes.

Retail

• Estimated Job Losses: 15 million

• Estimated Salary Saved: $450 billion

• Sources: McKinsey, World Economic Forum

• Deep learning algorithms are used to analyze customer behavior, helping retailers to personalize shopping experiences and optimize inventory management.

Transportation and Logistics

• Estimated Job Losses: 15 million

• Estimated Salary Saved: $450 billion

• Sources: McKinsey, IMF

• Deep learning models are employed in route optimization to enhance delivery efficiency and reduce operational costs. The importance of AI governance in ensuring the ethical deployment of these models in transportation and logistics cannot be overstated.

Finance and Banking

• Estimated Job Losses: 5 million

• Estimated Salary Saved: $300 billion

• Sources: PwC, World Economic Forum, IMF

• Deep neural networks are utilized in fraud detection systems to identify suspicious activities and prevent financial crimes. Generative AI tools are also being used in financial applications to enhance processes such as fraud detection and customer service.

Healthcare

• Estimated Job Losses: 7 million

• Estimated Salary Saved: $210 billion

• Sources: McKinsey, World Economic Forum

• Machine learning is applied in diagnostics to improve the accuracy of disease detection and patient outcomes through the use of AI algorithms.

Customer Service

• Estimated Job Losses: 5 million

• Estimated Salary Saved: $150 billion

• Sources: McKinsey, World Economic Forum

• The effectiveness of AI chatbots heavily depends on the quality of training data, which enables them to understand and respond to customer queries accurately. Natural language processing (NLP) further enhances the performance of AI chatbots by enabling them to better understand and process human language, leading to more accurate and contextually relevant responses.

Agriculture

• Estimated Job Losses: 4 million

• Estimated Salary Saved: $120 billion

• Sources: McKinsey, World Economic Forum

Self-Serve Legal Services

• Estimated Job Losses: 1 million

• Estimated Salary Saved: $80 billion

• Sources: McKinsey, World Economic Forum

PPC & Digital Marketing

• Estimated Job Losses: 2 million

• Estimated Salary Saved: $100 billion

• Sources: Google, The Trade Desk

CRM and Call Centers

• Estimated Job Losses: 3 million

• Estimated Salary Saved: $90 billion

• Sources: Salesforce, Zendesk

Customer Support

• Estimated Job Losses: 1.5 million

• Estimated Salary Saved: $45 billion

• Sources: IBM Watson, Microsoft Azure

Design, SEO and Content Creation

• Estimated Job Losses: 3 million

• Estimated Salary Saved: $90 billion

• Sources: Adobe Sensei, NVIDIA

Video and Audio Production

• Estimated Job Losses: 2 million

• Estimated Salary Saved: $60 billion

• Sources: Adobe Premiere, Descript

Music Production and Voice Overs

• Estimated Job Losses: 1 million

• Estimated Salary Saved: $30 billion

• Sources: AIVA, Replica Studios

ADR and 3D Creation

• Estimated Job Losses: 0.5 million

• Estimated Salary Saved: $15 billion

• Sources: Adobe After Effects, Autodesk Maya

Fashion Design and Stylists

• Estimated Job Losses: 2 million

• Estimated Salary Saved: $60 billion

• Sources: Google, IBM

Makeup Artists and Nutritionists

• Estimated Job Losses: 1 million

• Estimated Salary Saved: $30 billion

• Sources: ModiFace, Nutrino

Interior Decoration

• Estimated Job Losses: 0.5 million

• Estimated Salary Saved: $15 billion

• Sources: Planner 5D, Autodesk

Production and Retail (Decoration)

• Estimated Job Losses: 1 million

• Estimated Salary Saved: $30 billion

• Sources: Amazon, Shopify

Teachers and Private Tutors

• Estimated Job Losses: 1 million

• Estimated Salary Saved: $30 billion

• Sources: Khan Academy, Coursera

Personal Trainers

• Estimated Job Losses: 0.5 million

• Estimated Salary Saved: $15 billion

• Sources: Peloton, Freeletics

Overall Impact of Ai on Job Displacement

While the integration of AI and quantum computing technologies offers substantial salary savings by reducing workforce requirements, this initial economic benefit may quickly become a significant strain. The millions of workers displaced will still need financial support, such as a universal basic income (UBI), to sustain their livelihoods. Implementing UBI would place an immense burden on national economies, potentially negating the financial benefits of AI-induced job cuts. Responsible AI practices are crucial in mitigating job displacement and ensuring ethical deployment of AI systems. AI governance plays a vital role in ensuring responsible AI practices and mitigating job displacement by establishing comprehensive regulations and frameworks.

Those who lose their jobs will no longer contribute to the tax base. This reduction in tax revenues could undermine public services and infrastructure, creating a gap that must be addressed. The decline in income tax and other contributions from a large segment of the population will necessitate new strategies to ensure the continuity of government functions and social services. AI aims to simulate human intelligence, performing complex problem-solving tasks and learning from data, which has significant implications for various industries.

To fill this tax revenue gap, governments may need to consider several approaches:

1. Taxing Automation and AI Systems: Implementing taxes on robots and AI systems that replace human jobs could help recoup lost tax revenue.

2. Corporate Tax Reforms: Increasing corporate taxes, particularly on companies that heavily utilize automation, could ensure that these businesses contribute their fair share to the economy.

3. New Economic Models: Developing new economic models that include digital and data economies, where value is created and taxed differently, can help balance the fiscal scales.

Immediate strategies and legislative actions are crucial to address these challenges before they escalate. Policymakers need to collaborate with industry leaders, economists, and technologists to draft comprehensive regulations that:

• Ensure fair distribution of the economic gains from AI.

• Provide robust support for reskilling and upskilling the workforce.

• Implement social safety nets, such as #UBI, in a sustainable manner.

• Explore innovative tax policies to offset the reduction in traditional tax revenues.

By proactively addressing these issues, we can create a balanced approach that harnesses the benefits of AI while mitigating its adverse economic impacts. It is imperative to act now, laying the groundwork for a future where technology enhances human potential without displacing the foundational economic structures. It is also important to recognize the distinction between AI and human intelligence, as true human reasoning and versatility remain benchmarks for evaluating AI technologies.

Modi Elnadi is a seasoned Performance Marketer and PPC/SEO consultant with extensive experience in developing, executing and optimizing high-impact campaigns across digital channels. Over the years, he has had the privilege of working with renowned brands and ecommerce products. Modi has driven significant growth and engagement through innovative digital strategies, activations and advanced AI technologies, making him a true early adopter in the digital marketing industry.

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