AI Job Displacement: 10 Careers at Risk (2025-2030) & Expert Analysis

Artificial intelligence is rapidly transforming the global labor market at an unprecedented pace. As we approach 2025 and look toward the next 3-5 years, the integration of AI into workplaces worldwide is accelerating, creating both opportunities and challenges for the global workforce. According to the International Monetary Fund (IMF), almost 40% of global employment is exposed to AI, with advanced economies facing greater risks—about 60% of jobs may be impacted by AI in these regions.

This comprehensive analysis examines the top 10 jobs most likely to be replaced by AI between 2025 and 2030, providing detailed explanations of why these roles are vulnerable, the technologies driving their replacement, and the varying impacts across different regions of the world. Understanding these trends is crucial for workers, businesses, and policymakers as they navigate the profound transformation of work in the AI era.

What distinguishes the current wave of technological disruption from previous industrial revolutions is AI’s unique ability to impact high-skilled jobs, not just routine tasks. As the World Economic Forum notes, while 92 million roles will be displaced by technological and other trends, 170 million new jobs will be created, resulting in a net employment increase of 78 million jobs. However, this transition will not be evenly distributed across sectors or regions, creating significant challenges for specific job categories.

2. The Global Impact of AI on Employment

Before examining specific at-risk jobs, it’s important to understand the broader context of AI’s impact on global employment. The scale and pace of this transformation vary significantly across different economies and regions.

Advanced vs. Emerging Economies

The IMF analysis reveals striking differences in AI exposure across economic development levels:

Economic Region	AI Exposure Rate	Key Factors
Advanced Economies	~60%	Higher technology adoption, digital infrastructure
Emerging Markets	~40%	Less immediate disruption but limited AI benefits
Low-Income Countries	~26%	Minimal short-term impact but risk of widening inequality

In advanced economies, approximately half of the exposed jobs may benefit from AI integration, enhancing productivity. For the other half, AI applications may execute key tasks currently performed by humans, potentially lowering labor demand, reducing wages, and decreasing hiring. In extreme cases, some jobs may disappear entirely.

Timeline of Displacement

According to McKinsey’s analysis, between 400 million and 800 million individuals could be displaced by automation and need to find new jobs by 2030 worldwide. Of this total, 75 million to 375 million may need to switch occupational categories and learn new skills. This transition will require significant reskilling efforts, with 77% of employers planning to prioritize reskilling and upskilling their workforce to enhance collaboration with AI systems by 2030.

Shifting Task Distribution

The nature of work itself is changing fundamentally. Currently, respondents to the World Economic Forum survey estimate that 47% of work tasks are performed primarily by humans, 22% are handled mainly by technology (including machines and algorithms), and 30% involve collaborative human-machine efforts. By 2030, these proportions are expected to shift significantly, with tasks nearly evenly divided between human, machine, and hybrid approaches.

With this global context established, let’s examine the top 10 jobs most vulnerable to AI replacement in the coming years.

3. Manufacturing and Production Jobs

Manufacturing jobs represent one of the sectors most immediately threatened by AI and automation technologies globally.

Key Vulnerable Roles

Manufacturing roles at high risk include:

• Machine operators
• Product handlers and assemblers
• Quality control testers
• Packaging workers
• Production line workers

Why These Jobs Are Vulnerable

Manufacturing jobs are particularly susceptible to AI replacement for several reasons:

1. Task Repetition: Manufacturing often involves predictable, repetitive physical tasks that can be easily programmed into machines and robots.
2. Precision Requirements: AI-powered robots can achieve higher precision and consistency than human workers, reducing error rates and improving product quality.
3. 24/7 Operation: Automated systems can operate continuously without breaks, increasing production efficiency.
4. Cost Efficiency: While initial investment in automation is high, the long-term operational costs are typically lower than human labor, especially in high-wage economies.

According to the Forbes analysis, manufacturing jobs involving “machine operation, product handling, testing, packaging, testing, etc.” are among the most likely to be automated. These roles typically involve “routine or repetitive actions that require a high degree of accuracy”, making them ideal candidates for automation.

Regional Impact Variations

The impact on manufacturing jobs varies significantly by region:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	Higher labor costs make automation more economically viable
Emerging Markets	Moderate	Lower labor costs may temporarily delay full automation
Low-Income Countries	Variable	May see manufacturing jobs shift from advanced economies before eventual automation

In countries with higher labor costs, the economic incentive to automate manufacturing is stronger. However, even in emerging economies with lower labor costs, the trend toward automation is accelerating as technology costs decrease and capabilities improve.

Technologies Driving Replacement

The key technologies replacing manufacturing workers include:

• Advanced robotics with improved dexterity and sensing capabilities
• Computer vision systems for quality control
• IoT sensors for real-time monitoring and predictive maintenance
• AI-powered workflow optimization systems

The combination of these technologies creates fully automated production environments that require minimal human intervention, primarily for oversight and maintenance rather than direct production tasks.

4. Data Entry and Analysis Roles

Data entry and basic analysis roles represent another category highly vulnerable to AI replacement globally.

Key Vulnerable Roles

Data-related positions at high risk include:

• Data entry clerks
• Basic data analysts
• Data visualization specialists
• Report generators
• Database administrators (routine functions)

Why These Jobs Are Vulnerable

Data-related jobs are particularly susceptible to AI replacement for several reasons:

1. Structured Tasks: Data entry and basic analysis follow clear rules and patterns that AI can easily learn and replicate.
2. Digital Nature: These tasks already occur in digital environments, making the transition to AI automation seamless.
3. Volume Handling: AI can process vast amounts of data much faster than humans without fatigue or errors.
4. Pattern Recognition: Modern AI excels at identifying patterns and anomalies in data, often outperforming human analysts.

According to Forbes, “basic data entry, analysis, and visualization jobs” are among the roles most at risk of automation. Indeed’s analysis defines automated roles as those that “may include simple tasks, such as making phone calls, or complex processes, such as running data analysis or processing transactions”.

Regional Impact Variations

The impact on data roles varies by region but is generally more uniform globally than manufacturing:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	High digital adoption and AI integration
Emerging Markets	High	Growing digital infrastructure and cloud services
Low-Income Countries	Moderate	Outsourced data processing roles increasingly automated

Even in regions with lower technology adoption, cloud-based AI services make it possible to automate data tasks without significant local infrastructure, accelerating the global impact.

Technologies Driving Replacement

The key technologies replacing data workers include:

• Natural language processing for data extraction from unstructured sources
• Automated data cleaning and preparation tools
• AI-powered analytics platforms with automated insight generation
• No-code/low-code visualization tools with AI assistance
• Large language models that can generate reports from raw data

These technologies not only replace routine data tasks but increasingly encroach on more complex analytical functions that previously required human judgment.

5. Administrative and Clerical Positions

Administrative and clerical positions represent one of the largest categories of jobs vulnerable to AI replacement globally.

Key Vulnerable Roles

Administrative roles at high risk include:

• Administrative assistants
• Executive secretaries
• Office clerks
• Filing and records management staff
• Scheduling coordinators
• Postal service clerks

Why These Jobs Are Vulnerable

Administrative jobs are particularly susceptible to AI replacement for several reasons:

1. Routine Workflows: Most administrative tasks follow predictable patterns and procedures that can be easily automated.
2. Digital Communication: Email management, scheduling, and document processing are increasingly handled by AI tools.
3. Standardized Documentation: Form processing, data entry, and records management can be automated with high accuracy.
4. Scheduling Optimization: AI can manage calendars and coordinate meetings more efficiently than human assistants.

According to the World Economic Forum’s Future of Jobs Report, clerical and administrative jobs are among those hardest hit by automation and AI technologies. Postal service clerks and bank tellers, for instance, are projected to shrink by over 25%, while positions such as administrative assistants and executive secretaries are facing substantial declines.

Regional Impact Variations

The impact on administrative roles varies by region:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	High digital adoption and cost pressure
Emerging Markets	High	Growing adoption of global business practices
Low-Income Countries	Moderate	Outsourced administrative functions increasingly automated

In advanced economies, the combination of high labor costs and widespread digital adoption makes administrative roles particularly vulnerable. However, the global nature of business means these trends are spreading rapidly to emerging markets as well.

Technologies Driving Replacement

The key technologies replacing administrative workers include:

• Email management AI that can categorize, prioritize, and draft responses
• Calendar management tools that automatically schedule meetings
• Document processing systems that can extract, categorize, and file information
• Virtual meeting assistants that can transcribe, summarize, and extract action items
• Workflow automation platforms that coordinate complex administrative processes

Microsoft 365 Copilot, for example, is already being used at nearly 70% of Fortune 500 companies to tackle repetitive and mundane tasks, such as sifting through email and taking notes during Teams meetings. By 2025, a new generation of AI-powered agents will do even more, handling certain tasks entirely on behalf of human workers.

6. Customer Service and Retail Roles

Customer service and retail positions represent another major category highly vulnerable to AI replacement globally.

Key Vulnerable Roles

Customer service and retail roles at high risk include:

• Retail salespeople (non-specialized)
• Customer service representatives
• Cashiers and checkout clerks
• Ticket clerks
• Inventory managers
• Fraud analysts

Why These Jobs Are Vulnerable

Customer service and retail jobs are particularly susceptible to AI replacement for several reasons:

1. Repetitive Interactions: Many customer inquiries follow common patterns that can be handled by AI chatbots and virtual assistants.
2. Transaction Processing: Payment processing and checkout can be fully automated through self-service systems.
3. Inventory Management: AI can track stock levels, predict demand, and automate reordering more efficiently than humans.
4. Fraud Detection: AI algorithms can identify suspicious patterns in transactions more effectively than human analysts.

According to Forbes, “retail and commerce roles (customer service, inventory management, fraud analysis)” are among the jobs most at risk of automation. The repetitive nature of many retail tasks makes them ideal candidates for automation.

Regional Impact Variations

The impact on retail and customer service roles varies by region:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	High digital adoption and labor costs
Emerging Markets	High	Rapid adoption of digital commerce
Low-Income Countries	Moderate	Growing e-commerce penetration

In advanced economies, the combination of high labor costs and consumer acceptance of self-service technologies accelerates automation. However, the global growth of e-commerce is driving similar trends in emerging markets.

Technologies Driving Replacement

The key technologies replacing customer service and retail workers include:

• Conversational AI and chatbots for customer inquiries
• Self-checkout and cashierless store technologies
• AI-powered inventory management systems
• Predictive analytics for demand forecasting
• Automated fraud detection systems

These technologies not only replace human workers but often improve service consistency and availability, providing 24/7 support that human staffing would make prohibitively expensive.

7. Financial Analysis and Accounting

Financial analysis and accounting roles, particularly at entry and mid-levels, face significant disruption from AI technologies globally.

Key Vulnerable Roles

Financial roles at high risk include:

• Financial analysts (junior to mid-level)
• Risk assessment specialists
• Credit analysts
• Insurance underwriters
• Investment analysts (quantitative)
• Accounting clerks

Why These Jobs Are Vulnerable

Financial analysis and accounting jobs are particularly susceptible to AI replacement for several reasons:

1. Data-Intensive Tasks: Financial analysis involves processing large volumes of structured data, which AI excels at handling.
2. Pattern Recognition: AI can identify trends, anomalies, and correlations in financial data more quickly and accurately than humans.
3. Regulatory Compliance: AI can track changing regulations and ensure compliance more comprehensively than human analysts.
4. Predictive Modeling: Machine learning models can forecast financial outcomes with increasing accuracy, replacing human judgment in many cases.

According to Forbes, “financial analysis and projection roles” are among the jobs most at risk of automation. The IMF analysis highlights that AI’s ability to impact high-skilled jobs is one of the factors that sets it apart from previous waves of automation.

Regional Impact Variations

The impact on financial roles varies by region:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	Sophisticated financial systems and high AI adoption
Emerging Markets	High	Growing integration with global financial systems
Low-Income Countries	Moderate	Less developed financial sectors but increasing automation

Financial centers in advanced economies will see the most immediate impact, but the global nature of finance means these trends will spread rapidly to emerging markets as well.

Technologies Driving Replacement

The key technologies replacing financial workers include:

• Machine learning models for risk assessment and credit scoring
• Natural language processing for financial document analysis
• Automated financial reporting systems
• Algorithmic trading platforms
• AI-powered fraud detection and compliance monitoring

These technologies not only replace routine financial tasks but increasingly encroach on areas that previously required human judgment and expertise, such as investment recommendations and risk assessment.

8. Transport and Logistics Jobs

Transport and logistics roles face significant disruption from AI and automation technologies globally.

Key Vulnerable Roles

Transport and logistics roles at high risk include:

• Truck and delivery drivers
• Warehouse workers
• Shipping and receiving clerks
• Logistics coordinators
• Route planners
• Freight handlers

Why These Jobs Are Vulnerable

Transport and logistics jobs are particularly susceptible to AI replacement for several reasons:

1. Route Optimization: AI can calculate optimal delivery routes more efficiently than human planners.
2. Autonomous Vehicles: Self-driving technology is advancing rapidly for both long-haul trucking and last-mile delivery.
3. Warehouse Automation: Robotic systems can pick, pack, and sort items with increasing dexterity and speed.
4. Predictive Logistics: AI can forecast demand and optimize supply chains more effectively than human planners.

According to Forbes, “transport and logistics jobs (human drivers being replaced through autonomous vehicles, such as what we’re already seeing with Waymo)” are among the roles most at risk of automation.

Regional Impact Variations

The impact on transport and logistics roles varies by region:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	High labor costs and technology adoption
Emerging Markets	Moderate to High	Growing logistics infrastructure
Low-Income Countries	Low to Moderate	Infrastructure limitations may slow adoption

In advanced economies with well-developed infrastructure and high labor costs, the economic incentive to automate transport and logistics is stronger. However, the global nature of supply chains means these trends will eventually impact all regions.

Technologies Driving Replacement

The key technologies replacing transport and logistics workers include:

• Autonomous vehicles for long-haul trucking and delivery
• Warehouse robotics for picking, packing, and sorting
• AI-powered route optimization and fleet management systems
• Predictive analytics for demand forecasting and inventory management
• Drone delivery systems for last-mile logistics

These technologies not only replace human workers but often improve efficiency, reduce errors, and enable 24/7 operations that would be impossible with human staffing alone.

9. Translation and Language Services

Translation and language service roles face significant disruption from AI technologies globally.

Key Vulnerable Roles

Translation roles at high risk include:

• Document translators
• Website localizers
• Subtitle creators
• Basic interpreters
• Multilingual customer support
• Technical translators (for standardized content)

Why These Jobs Are Vulnerable

Translation and language service jobs are particularly susceptible to AI replacement for several reasons:

1. Pattern Recognition: Neural machine translation has made enormous strides in understanding language patterns and context.
2. Data Availability: Vast parallel corpora of translated texts enable AI systems to learn from millions of examples.
3. Real-Time Processing: AI translation systems can now operate in real-time for both text and speech.
4. Consistency: AI translators maintain consistent terminology and style across large documents.

According to Forbes, “translators” are among the jobs most at risk of automation. The rapid advancement of neural machine translation has dramatically improved the quality of automated translations, particularly for common language pairs.

Regional Impact Variations

The impact on translation roles varies by region and language pair:

Region/Language	Impact Level	Contributing Factors
Major Languages (English, Spanish, Chinese, etc.)	Severe	Abundant training data and commercial focus
Regional Languages (Dutch, Swedish, etc.)	High	Sufficient data but smaller markets
Low-Resource Languages (Many African and Indigenous languages)	Moderate	Limited training data slows AI development

Translators working with major language pairs (e.g., English-Spanish, English-Chinese) face the most immediate threat, while those specializing in low-resource languages may retain their roles longer due to limited AI training data.

Technologies Driving Replacement

The key technologies replacing translators include:

• Neural machine translation systems
• Real-time speech translation tools
• Multilingual natural language processing
• Context-aware translation memory systems
• Specialized domain-specific translation engines

These technologies not only replace human translators for routine content but increasingly handle nuanced translations that previously required human judgment, such as marketing materials and technical documentation.

10. Legal Support Roles

Legal support positions, particularly those involving routine document processing and research, face significant disruption from AI technologies globally.

Key Vulnerable Roles

Legal support roles at high risk include:

• Paralegals
• Legal researchers
• Document reviewers
• Contract analysts
• Legal transcriptionists
• Compliance monitors

Why These Jobs Are Vulnerable

Legal support jobs are particularly susceptible to AI replacement for several reasons:

1. Document Processing: AI can review, categorize, and extract information from legal documents much faster than humans.
2. Pattern Recognition: Machine learning can identify relevant precedents and legal principles across vast databases of cases.
3. Standardization: Many legal documents follow standard templates and language that AI can easily process.
4. Research Efficiency: AI can search and analyze legal databases more comprehensively than human researchers.

According to Forbes, “paralegals” are among the roles at risk of expiration or being less in demand. The ability of AI to process and analyze large volumes of legal documents makes many paralegal tasks automatable.

Regional Impact Variations

The impact on legal support roles varies by region and legal system:

Region/Legal System	Impact Level	Contributing Factors
Common Law (US, UK, etc.)	Severe	Case-based system with digitized records
Civil Law (Continental Europe, Latin America)	High	Codified system amenable to rule-based AI
Mixed/Traditional Systems	Moderate	Varying levels of digitization and standardization

In regions with highly digitized legal systems and standardized procedures, the impact will be more immediate. However, the global trend toward legal tech adoption means these effects will eventually reach most legal systems.

Technologies Driving Replacement

The key technologies replacing legal support workers include:

• Natural language processing for legal document analysis
• Machine learning for case outcome prediction
• Automated contract review and generation systems
• Legal research platforms with AI-powered search and analysis
• Compliance monitoring systems that automatically track regulatory changes

These technologies not only replace routine legal tasks but increasingly handle complex functions that previously required legal training and judgment, such as contract analysis and compliance monitoring.

11. Content Creation and Editing

Content creation and editing roles, particularly those involving routine or formulaic content, face significant disruption from AI technologies globally.

Key Vulnerable Roles

Content roles at high risk include:

• Proofreaders and copy editors
• Basic content writers
• Social media content creators
• Entry-level graphic designers
• Template-based web designers
• Stock image photographers

Why These Jobs Are Vulnerable

Content creation and editing jobs are particularly susceptible to AI replacement for several reasons:

1. Pattern Recognition: AI can learn writing styles, brand guidelines, and editorial standards.
2. Error Detection: AI can identify grammatical errors, inconsistencies, and style issues with high accuracy.
3. Content Generation: Generative AI can produce original text, images, and designs based on prompts.
4. Efficiency: AI can create and edit content much faster than humans, at a fraction of the cost.

According to Forbes, “proofreaders” and “graphic designers” are among the roles at risk of expiration or being less in demand. The rapid advancement of generative AI tools like DALL-E, Midjourney, and GPT models has dramatically improved the quality of AI-generated content.

Regional Impact Variations

The impact on content roles varies by region and language:

Region/Language	Impact Level	Contributing Factors
English-Language Markets	Severe	Advanced AI models and commercial focus
Major Non-English Markets	High	Growing language model capabilities
Niche Languages/Markets	Moderate	Limited training data slows AI development

Content creators working in English face the most immediate threat due to the advanced state of English-language AI models, but the rapid development of multilingual models is extending this impact globally.

Technologies Driving Replacement

The key technologies replacing content workers include:

• Large language models for text generation and editing
• AI image generators for visual content creation
• Automated proofreading and editing tools
• Template-based design systems with AI customization
• Content optimization algorithms that predict audience engagement

These technologies not only replace routine content tasks but increasingly produce creative work that previously required human imagination and judgment, such as marketing copy, blog posts, and basic graphic design.

12. Tax Preparation and Bookkeeping

Tax preparation and bookkeeping roles, particularly at entry and mid-levels, face significant disruption from AI technologies globally.

Key Vulnerable Roles

Tax and bookkeeping roles at high risk include:

• Tax preparers
• Bookkeepers
• Accounts payable/receivable clerks
• Payroll processors
• Audit assistants
• Financial record keepers

Why These Jobs Are Vulnerable

Tax preparation and bookkeeping jobs are particularly susceptible to AI replacement for several reasons:

1. Rule-Based Tasks: Tax codes and accounting principles follow specific rules that can be programmed into AI systems.
2. Data Processing: These roles involve processing large volumes of structured financial data, which AI excels at handling.
3. Pattern Recognition: AI can identify anomalies and errors in financial records more efficiently than humans.
4. Automation Integration: Financial systems increasingly integrate directly with tax and accounting software, reducing the need for human data entry.

According to Forbes, “tax preparation and entry-level bookkeeping and accounting roles” are among the jobs most at risk of automation. The structured nature of these tasks makes them ideal candidates for AI replacement.

Regional Impact Variations

The impact on tax and bookkeeping roles varies by region:

Region	Impact Level	Contributing Factors
Advanced Economies	Severe	Digitized financial systems and regulatory frameworks
Emerging Markets	High	Growing adoption of global accounting standards
Low-Income Countries	Moderate	Less complex tax systems but increasing automation

In regions with highly digitized financial systems and standardized tax codes, the impact will be more immediate. However, the global trend toward financial technology adoption means these effects will eventually reach most economies.

Technologies Driving Replacement

The key technologies replacing tax and bookkeeping workers include:

• Automated tax preparation software
• AI-powered accounting platforms
• Optical character recognition for document processing
• Automated reconciliation systems
• Intelligent audit tools that flag potential issues

These technologies not only replace routine financial tasks but increasingly handle complex functions that previously required accounting training and judgment, such as tax planning and financial reporting.

13. Strategies for Workers in At-Risk Industries

For workers in industries facing AI disruption, proactive adaptation is essential. The World Economic Forum and other sources suggest several strategies for navigating this transition:

1. Skill Development Focus Areas

According to the World Economic Forum’s Jobs Survey Report, employers expect 39% of workers’ core skills to change by 2030. The most valuable skills to develop include:

Skill Category	Examples	Growth Potential
Technological Skills	AI/ML, Data Analysis, Cybersecurity	Highest Growth
Creative Thinking	Problem-solving, Innovation, Design Thinking	High Growth
Resilience & Adaptability	Change Management, Stress Tolerance	High Growth
Leadership & Social Influence	Team Management, Emotional Intelligence	Moderate Growth
Analytical Thinking	Critical Reasoning, Complex Problem Solving	Moderate Growth

The WEF report emphasizes that technological skills are projected to grow in importance more rapidly than any other skills in the next five years, with AI and big data at the top of the list.

2. Education and Reskilling Pathways

By 2030, 77% of employers plan to prioritize reskilling and upskilling their workforce to enhance collaboration with AI systems. Workers should consider:

• Formal education in high-demand fields
• Industry certifications in AI and related technologies
• Micro-credentials and online courses
• Employer-sponsored training programs
• Apprenticeships and mentorships in emerging roles

3. Career Transition Strategies

For workers in highly vulnerable roles, strategic career transitions may be necessary:

• Vertical Specialization: Develop deep expertise in a niche area that AI cannot easily replicate
• Horizontal Expansion: Combine multiple skill sets to create a unique value proposition
• Human-AI Collaboration: Focus on roles that involve overseeing, training, or working alongside AI
• Emotional Labor: Shift toward roles requiring high emotional intelligence and interpersonal skills
• Creative Problem-Solving: Move into positions requiring novel solutions to complex problems

4. Industry-Specific Adaptation

Different at-risk industries offer unique pathways for adaptation:

Industry	Adaptation Strategy	Example Roles
Manufacturing	Shift to AI oversight and maintenance	Robotics Supervisor, AI Quality Manager
Administrative	Develop strategic communication skills	Executive Relationship Manager, Cross-functional Coordinator
Customer Service	Focus on complex problem resolution	Escalation Specialist, Customer Experience Designer
Financial	Move toward advisory and relationship roles	Financial Advisor, Client Relationship Manager
Legal	Specialize in AI ethics and regulation	AI Compliance Officer, Legal Tech Specialist

As IBM vice president Justina Nixon-Saintil emphasized, “Learning does not just stop anymore. There’s a new technology all the time; it’s accelerating at a much faster rate than it ever did… today it’s AI, it could be quantum tomorrow. AI will impact almost every job role and will affect every industry”.

14. Conclusion: The Future Workforce Landscape

The impact of AI on the global job market between 2025 and 2030 will be profound but nuanced. While the 10 job categories analyzed in this report face significant disruption, the overall employment picture includes both challenges and opportunities.

Key Findings Summary

Aspect	Impact
Global Job Exposure	~40% of jobs exposed to AI globally
Advanced Economies	~60% of jobs impacted by AI
Emerging Markets	~40% of jobs exposed to AI
Low-Income Countries	~26% of jobs exposed to AI
Net Job Creation	78 million net new jobs globally by 2030
Skills Disruption	39% of key skills changing by 2030

The Dual Nature of AI’s Impact

The IMF analysis captures the dual nature of AI’s impact on employment: while it will replace some jobs entirely, it will also complement and enhance others. In advanced economies, roughly half the exposed jobs may benefit from AI integration, enhancing productivity, while the other half face potential displacement.

New Job Creation

According to the World Economic Forum, while 92 million roles will be displaced, 170 million new jobs will be created by these same trends, resulting in a net employment increase of 78 million jobs. The WEF also projects that by 2030, 85% of roles will be new jobs that don’t even exist today.

The largest growing jobs include:

1. Farmworkers (34 million additional jobs by 2030)
2. Delivery drivers
3. Software developers
4. Building construction workers
5. Shop salespersons

Additionally, care jobs—including nursing professionals, social workers, and counseling professionals—are projected to grow significantly over the next five years, driven by demographic trends, especially aging populations.

The Path Forward

For workers, businesses, and policymakers, navigating this transition requires a balanced approach:

1. Workers must focus on developing skills that complement rather than compete with AI, emphasizing creativity, emotional intelligence, and complex problem-solving.
2. Businesses need to invest in responsible AI adoption while supporting workforce transition through reskilling programs and creating new roles that leverage human-AI collaboration.
3. Policymakers must establish comprehensive social safety nets and offer retraining programs for vulnerable workers to make the AI transition more inclusive and protect livelihoods.

As the IMF concludes, “In most scenarios, AI will likely worsen overall inequality, a troubling trend that policymakers must proactively address to prevent the technology from further stoking social tensions”. By taking a proactive and collaborative approach, we can harness AI’s vast potential while ensuring that its benefits are widely shared across the global workforce.