AI is already changing the workplace, and yes, AI will take jobs. By 2030, 375 million workers worldwide may need to switch careers or retrain due to AI automation. Industries like manufacturing, customer service, and finance are seeing the biggest shifts, with AI taking over repetitive tasks and creating demand for new skills.
Key Takeaways:
- AI’s Impact on Jobs: AI is automating tasks, and in some cases, entire jobs. For example, IKEA uses drones for inventory, and Wendy’s employs AI for customer service.
- Industries Most Affected:
- Manufacturing: 20 million jobs could be automated.
- Customer Service: Chatbots are replacing basic inquiries.
- Finance: Transaction processing is being automated, but advisory roles are growing.
- Future of Work:
- 2025-2030: Routine tasks automated.
- 2030-2035: AI-human collaboration grows.
- 2035-2040: AI leads operations, humans focus on creativity and strategy.
- New Skills Needed: Critical thinking, emotional intelligence, data analysis, and AI system management.
- Job Creation: AI could generate 97 million new roles by 2025, including AI trainers, ethicists, and product managers.
AI is reshaping work, but it’s also creating opportunities. To stay ahead, focus on building skills that complement AI while businesses invest in worker support and retraining programs.
AI Will Take Jobs, Billions by 2030: How Can You Get Ready?
Timeline: Job Changes from 2025-2040
This timeline captures the transformative journey of AI in the workplace, from automating routine tasks to leading operations. It reflects how job roles and required skills will evolve alongside AI’s growing capabilities. Let’s break down this progression into three key phases.
2025-2030: AI Will Take Jobs Through Basic Task Automation
Between 2025 and 2030, AI will take jobs, including repetitive, routine tasks, across various industries. Machines will excel in functions that require consistency and speed, paving the way for humans to focus on more meaningful work. Here’s how this phase will unfold:
| Industry | Tasks Automated | Evolving Human Roles |
|---|---|---|
| Healthcare | Claims processing, documentation | Patient care and interaction |
| Finance | Transaction processing | Advisory and strategic services |
| Manufacturing | Quality control | Process improvement and innovation |
| Customer Service | Basic inquiries | Resolving complex customer issues |
For example, in March 2025, Thoughtful‘s RCM system revolutionized healthcare by automating claims processing with robotic process automation (RPA). This freed up workers to dedicate their time to patient care instead of administrative tasks [1].
2030-2035: Mixed AI-Human Teams
From 2030 to 2035, workplaces will see the rise of AI-human collaboration. These hybrid teams will require a massive wave of reskilling, impacting as many as 375 million workers globally [1]. At the same time, AI will drive job creation, with an estimated 97 million new roles emerging in areas like data analysis, software development, and cybersecurity [1].
As AI capabilities grow, these mixed teams will evolve further, setting the stage for AI to take on more leadership responsibilities in managing workflows.
2035-2040: AI-Led Operations
By 2035, AI will transition from being a collaborator to leading operations. This phase will redefine how businesses function, with AI taking charge of decision-making, resource management, and workforce planning. However, human oversight will remain critical to ensure ethical and effective outcomes. Key features of this phase include:
- AI-driven decision-making processes
- Automated management of resources
- Predictive workforce planning
- Human supervision of AI-led systems
As AI takes the lead, the demand for distinctly human skills will grow. The job market will prioritize abilities that machines cannot replicate, such as:
| Skill Category | Application Areas |
|---|---|
| Critical Thinking | Strategic planning |
| Creative Problem-Solving | Innovation and development |
| Emotional Intelligence | Leadership and team management |
| AI Systems Management | Overseeing technical operations |
To prepare for this shift, companies will need to invest heavily in training programs. These initiatives will help employees adapt to working alongside AI while focusing on high-value tasks that require human creativity, empathy, and strategic thinking.
How Jobs Will Change
Job Transition Examples
AI is reshaping jobs across various industries, both by eliminating roles entirely and by enhancing how tasks are performed. AI is becoming a tool that complements and amplifies human capabilities.
Octopus Energy, for example. In May 2023, the company introduced AI to automate email responses, handling over one-third of customer communications. This shift equated to the workload of about 250 employees. Even more impressive, AI-composed responses achieved an 80% customer satisfaction rate – outperforming the 65% satisfaction rate of their human counterparts[6].
Another case involves a Fortune 500 company that adopted an AI assistant for customer support in late 2020. The result? A 14% boost in productivity among customer service representatives. The AI system also helped less experienced employees perform at a level typically seen after six months of on-the-job training[5].
Here’s a snapshot of how specific roles are evolving with AI:
| Role | Current Tasks | AI-Enhanced Evolution |
|---|---|---|
| Customer Service Rep | Responding to emails, basic troubleshooting | AI-assisted message drafting, tackling complex issues |
| Healthcare Administrator | Scheduling, claims processing | Prioritizing patient care, streamlining coordination |
| Content Creator | Writing, editing | Strategic planning, utilizing AI for efficiency |
| Sales Representative | Cold calling, manual lead tracking | AI-driven lead analysis, improving client relationships |
These examples highlight the growing need for workers to adapt and develop skills to collaborate effectively with AI.
Required Skills for Future Work
As roles evolve, so do the skills required to succeed. Garry Kasparov, Chess Grandmaster and AI advocate, puts it succinctly:
“AI won’t replace you. A person using AI will”[3].
Though we know AI will take jobs, his perspective underscores the importance of learning to work alongside AI. According to the World Economic Forum, 44% of workers will need to reskill in the coming years[3]. Additionally, professionals with technical expertise are 25% more likely to secure roles that align with future workforce demands[3].
The skills needed for this shift fall into two main categories:
| Technical Skills | Human-Centric Skills |
|---|---|
| Data Analysis | Critical Thinking |
| AI Systems Management | Emotional Intelligence |
| Programming Fundamentals | Creative Problem-Solving |
| AI Tool Optimization | Strategic Planning |
| Machine Learning Basics | Team Leadership |
Duran Inci, CEO of Optimum7, captures the urgency of this transformation, stating the inevitable – that AI will take jobs:
“Think about your position and what your position will transform to in the next 12 to 24 months. Whether you like it or not, this is happening, and it is going to happen so fast that it will change the fabric of our society”[4].
To stay relevant, workers must take a proactive approach to skill development. Companies are increasingly seeking employees who can integrate AI into their workflows while still bringing uniquely human qualities to the table. Yuval Halevi, co-founder of GuerrillaBuzz, explains:
“We apply AI mainly to repetitive and time-consuming tasks, removing the monotony and freeing up time for more creative work”[4].
This shift allows workers to focus on higher-level, strategic responsibilities.
AI is also creating entirely new roles, including:
- AI Ethicist
- AI Product Manager
- Conversational AI Designer
- Machine Learning Engineer
- AI Trainer[2]
As these changes unfold, the ability to adapt and grow alongside AI will be crucial for both individuals and organizations. The future of work is not just about technology – it’s about how humans and AI can work together to unlock new possibilities.
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Managing the AI Transition
Worker Protection Programs
As AI continues to reshape industries, it’s crucial for organizations to put solid support systems in place for their employees. With many jobs evolving due to AI and automation, a large segment of the workforce will need to learn new skills. This means comprehensive worker protection programs are a must.
The U.S. Chamber of Commerce stresses the importance of taking proactive steps in workforce development. Cheryl Oldham, vice president of education policy at the Chamber, highlights this by saying, “We need to proactively lean into workforce development” [9]. This proactive approach includes several key initiatives:
| Program Type | Purpose | Implementation Strategy |
|---|---|---|
| Skill Development | Enhancing technical and soft skills | Company-sponsored training and partnerships with schools |
| Career Transition | Job placement and counseling | Career counseling and job placement services |
| Financial Protection | Providing economic security | Severance packages and stipends for retraining |
| Early Warning System | Advance notice of AI-related changes | 90-120 day notification periods for affected employees [7] |
To further protect workers, recommendations for updating the Worker Adjustment and Retraining Notification (WARN) Act include:
- Extending the notice period to 90-120 days
- Lowering the employee threshold to 25 workers
- Requiring companies to contribute to retraining funds [7]
These measures aim to support employees during transitions and set the stage for responsible AI adoption.
Company Requirements for AI Use
Beyond protecting workers, companies implementing AI need to follow specific guidelines to ensure ethical and effective use of these technologies. Dr. Marina Theodotou explains, “Preparing the workforce to work side by side with AI requires a strategic approach that encompasses reskilling and upskilling, promoting a learning culture, and emphasizing human-AI collaboration” [8].
Here’s what companies should prioritize:
- Governance and Oversight
Establish an AI Governance Council with executive sponsorship to oversee implementation and manage risks [10]. - Training and Development Programs
Invest in comprehensive training efforts that focus on:- Fundamentals of data analysis and machine learning
- Managing AI systems
- Critical thinking and problem-solving
- Skills for cross-functional teamwork [8]
- Privacy and Security Measures
Implement strict protocols for:- Protecting data and intellectual property
- Conducting privacy impact assessments before deploying AI
- Regularly auditing AI systems and their outputs [11]
The U.S. Chamber Commission on Artificial Intelligence Competition, Inclusion, and Innovation observes: “If developed and deployed ethically, [AI] has the ability to augment human capabilities and empower people to do much more” [9].
For a smooth integration of AI, companies should also focus on these areas:
| Requirement Area | Key Actions | Expected Outcomes |
|---|---|---|
| Skills Assessment | Regularly evaluate workforce capabilities | Targeted and effective training |
| Technology Integration | Gradual adoption of AI tools | Seamless transitions |
| Performance Monitoring | Continuously assess AI’s impact | Ongoing improvements |
| Employee Support | Offer resources for transition assistance | Greater employee confidence |
Balancing technological progress with employee well-being is essential. Companies must commit to guiding their workforce through this transformation while ensuring AI is implemented responsibly and ethically.
AI Will Take Jobs, So We Need New Ways to Measure Work Value
Performance Metrics for the AI Era
The rise of AI is reshaping the workplace, making many traditional productivity measures feel outdated. According to Deloitte‘s 2024 Global Human Capital Trends survey, 74% of respondents stress the importance of capturing worker value in ways beyond conventional metrics. Yet, only 17% of organizations believe they are ready to effectively assess individual contributions in this new landscape [13].
Why the shift? Traditional metrics often promote “performative” work, with studies showing that 32% of employee time is spent on tasks that fail to add real value [12]. Knowing that AI will take jobs, to stay relevant, organizations must transition from measuring outputs (like tasks completed) to focusing on outcomes that truly matter.
Here’s how performance metrics are evolving in the AI era:
| Metric Type | Traditional Measure | New AI-Era Measure |
|---|---|---|
| Productivity | Tasks completed | Value delivered to stakeholders |
| Quality | Error rates | Impact of innovation and problem-solving |
| Efficiency | Time spent | Resource use and meaningful outcomes |
| Development | Training hours | Skills gained and applied |
| Collaboration | Meeting attendance | Contributions to team success |
Sue Cantrell, Vice President of Products, Workforce Strategies at Deloitte Consulting LLP, highlights this shift:
“Outcomes over outputs: Why productivity is no longer the metric that matters most” [12].
This rethinking of metrics paves the way for real-world examples showcasing how AI and human teams can thrive together.
Success Stories: AI and Human Teams in Action
Organizations adopting outcome-focused metrics are already seeing results. Take Hitachi, for example. In February 2020, the company introduced a program using wearables and a mobile app to track and enhance employee well-being [12]. The results were striking:
- 33% increase in psychological capital
- 10% profit growth
- 34% improvement in call center sales per hour
- 15% boost in retail sales [12]
These numbers highlight a clear link between worker well-being and business success. Leaders are taking note – 79% acknowledge their role in creating value for employees as individuals. However, only 27% of workers strongly agree their employers are making meaningful progress in this direction [12].
To effectively measure work value in today’s world, organizations should focus on three key areas:
- Quality Indicators: Track customer satisfaction, innovation, and problem-solving impact.
- Human Development Metrics: Measure employee growth, skill acquisition, and overall well-being.
- Value Creation Measurements: Evaluate how teams contribute to achieving core business objectives.
With 71% of workers already taking on tasks beyond their official roles [12], it’s clear that businesses need to rethink how they measure contributions. By aligning metrics with both technological advancements and human potential, organizations can better capture the full scope of work value in the AI era.
Conclusion: AI Will Take Jobs. What are the Next Steps for AI Readiness
The shift to an AI-powered workforce isn’t just on the horizon – it’s already happening. According to Goldman Sachs, about two-thirds of current jobs face some level of exposure to AI automation [15]. In other words, AI will take jobs, so the time to act is now.
Organizations need to take proactive steps to navigate this transformation effectively. Here’s where the focus should be:
- Workforce Development: Start by identifying skill gaps within your teams where you think AI will take jobs. Offer targeted learning opportunities and encourage collaboration between AI systems and human employees through cross-functional projects.
- Strategic Implementation: As businesses evolve from merely adopting AI to leading with it, reskilling and upskilling employees becomes essential. Strengthening partnerships between humans and AI will be key to staying competitive.
- Worker Protection: Involve employees early in AI integration efforts. Define clear roles for unions and worker groups, and create incentives for retraining programs to minimize job displacement.
For individuals, the path forward lies in strengthening three core skill sets:
| Skill Category | Key Areas |
|---|---|
| Technical Skills | Data analysis, automation, AI literacy |
| Human Skills | Critical thinking, creativity, emotional intelligence |
| Strategic Skills | Cross-functional collaboration, ethical AI practices |
The future brings opportunities as well as challenges. AI is projected to generate 97 million new jobs by 2025 [1], particularly in fields like data analysis, software development, and cybersecurity. And while AI will undoubtedly reshape the workplace, it’s worth noting that 78% of the most in-demand jobs will still rely heavily on human skills [14].
FAQs
How can workers stay relevant as AI transforms the job market?
To stay competitive in a workforce increasingly shaped by AI, it’s crucial to build technical expertise in areas like data analysis, programming, and machine learning. At the same time, don’t underestimate the importance of soft skills – traits like creativity, flexibility, and strong communication are irreplaceable and continue to hold immense value.
Make lifelong learning a priority by taking advantage of training sessions, earning certifications, or attending workshops that focus on emerging technologies. Employers can also play a significant role by offering upskilling opportunities, helping their teams adapt to new challenges and excel in shifting roles.
How can companies help employees adapt to new roles as AI changes the workplace?
Companies can support their employees in navigating change by offering upskilling and reskilling programs that align with new demands, like data analysis, programming, and creative problem-solving. Giving employees access to ongoing learning opportunities not only helps them stay current but also boosts their confidence in meeting evolving job requirements.
Equally important is maintaining open and transparent communication about the company’s AI initiatives. Employees need to understand how AI might reshape their roles and what fresh opportunities could emerge. By outlining potential career paths within the organization and using AI tools to improve productivity and job satisfaction, businesses can ease the transition. Encouraging a workplace culture that values adaptability and innovation ensures employees are well-prepared to succeed in an AI-focused environment.
What are some new jobs created by AI, and what skills are needed for them?
AI is opening doors to exciting new careers, including roles like AI Ethicist, Prompt Engineer, AI Security Specialist, and Conversational AI Developer. These positions call for a variety of skills such as ethical judgment, crafting precise AI prompts, expertise in cybersecurity, and an understanding of natural language processing.
Other emerging opportunities include jobs like AI Solutions Analyst, AI Policy Advisor, and AI Trainer. These roles blend technical expertise with business strategy and knowledge of regulatory standards. As AI continues to advance, staying curious and ready to learn will be key to succeeding in these cutting-edge fields.