The Evolving Landscape of Work in the AI Era

This is a review of Main Themes and Key Insights from Recent Sources on AI, Green Jobs, and the Future of Work

Executive Summary:

The advent of Artificial Intelligence (AI) and the global transition to sustainable practices are rapidly reshaping labour markets, creating both significant opportunities and profound challenges. This briefing synthesises insights from recent research and expert commentary, highlighting a crucial shift from degree-based to skill-based hiring, particularly for AI and green jobs. While AI is poised to automate many routine tasks, it also creates new, high-demand roles that complement human capabilities, often commanding substantial wage premiums. The implications for education, workforce development, and societal well-being are far-reaching, necessitating proactive strategies from individuals, employers, and governments.

1. The AI and Green Job Revolution: Demand and Disruption

a: Surging Demand for AI and Green Skills: Both AI and green jobs are experiencing rapid growth and labour shortages. From 2018-2023, demand for AI roles grew by 21% as a proportion of all postings (and accelerated into 2024). Simultaneously, mentions of university education requirements for AI roles declined by 15%. The number of job postings in the UK requiring at least one green skill has grown by 67% between 2018 and 2023. In the US, job titles containing ‘AI’ have seen a huge increase of 7x in 2025 so far. Software developers are projected to see a 17.9% increase in employment from 2023 to 2033, and AI and data science specialists are among the fastest-growing job categories in 2025. Renewable energy technicians are projected for significant growth: solar photovoltaic installers by 22% and wind turbine technicians by 44% from 2022 to 2032.

b. Automation and Job Displacement: AI is automating routine and non-routine cognitive tasks, threatening a significant portion of existing jobs. 30% of current U.S. jobs could be automated by 2030; 60% will have tasks significantly modified by AI. 300 million jobs could be lost to AI globally, representing 9.1% of all jobs worldwide. 23.5% of U.S. companies have replaced workers with ChatGPT or similar AI tools. Tasks most vulnerable include clerical and administrative roles, bank tellers, cashiers, routine manufacturing, telemarketers, and medical transcriptionists. Entry-level roles could be increasingly at risk. Job roles in admin and support are disappearing. The impact of AI in his industry. Junior writers and creatives were let go. AI outperformed them in writing and ideation. One simple prompt replaced an entire day’s work of a junior writer.

c. Complementarity Outweighs Substitution (Net Positive External Effect): Despite job displacement, the overall impact of AI on labour markets appears to be net positive, driven by complementary effects. Complementary effects are up to 1.7x larger than substitution effects. Growth in AI roles is associated with an uptick in demand for non-AI complementary roles and a decline in demand for non-AI substitutable roles. A doubling of AI postings at the industry level aligns with a 5.4% increase in complementary non-AI roles, and regionally, it's a 3.0% rise in non-AI complementary roles versus a 5.8% decline in non-AI substitutable roles. The overall net job increase due to AI is estimated at 287,593 annually in the US for 2018–2023, with more than 1.5 to 1.7 complementary roles gained for each substitutable role lost in some occupations.

2. The Shift to Skill-Based Hiring and Wage Premiums

a. Declining Emphasis on Formal Degrees for AI Roles: Employers are increasingly prioritising specific skills over traditional qualifications, especially in high-demand AI fields. From 2018-2023... mentions of university education requirements for AI roles declined by 15%. Our regression analysis shows that university degrees have a significantly lower wage premium for both AI and green roles. For AI roles, the wage premium for formal education has nearly disappeared. Master's degree holders earn slightly more on average than other groups, but the difference across degrees is modest. Skillset and role type appear to matter more than degree level.

Job opportunities are spread evenly across all education levels, indicating that while advanced degrees can help, even an associate's or bachelor's degree can get your foot in the door—skills and experience are key differentiators. 49% of Gen Z job seekers believe AI has reduced the value of their college education.

b. Significant Wage Premiums for AI Skills: Specific AI skills command high wages, often surpassing the value of advanced degrees. AI skills command a wage premium of 23%, exceeding the value of degrees up until the PhD-level (33%). For AI roles, skill requirements surpass the wage impact of educational attainment up to the PhD level. Top-paying AI skills include C++ (~$170,000+ USD), CloudFormation (~$165,000), Kafka (~$160,000), and Terraform (~$155,000). AI-exposed industries are seeing 3x higher growth in revenue per employee and workers with AI skills now command a 56% wage premium. AI roles offer average salaries around £50k, significantly higher than the average job posting. Data scientists... are offered 5–10% higher salaries if they also possess resilience or ethics capabilities.

c. Green Skills and Wages: Green roles also offer higher salaries, though the educational premium is less pronounced than for AI roles. Green roles tend to offer higher salaries, with an upward trend reaching towards £40k by the end of the time series. For green roles, the educational gradient appears to have flattened.

3. Essential Skills for the Future of Work

a. AI-Complementary Human Skills (Epoch Skills): Skills that enable effective human-AI collaboration and leverage AI tools are increasingly valuable. AI-focused roles are nearly twice as likely to require skills like resilience, agility, or analytical thinking compared to non-AI roles. These economic power tools are categorised in the EPOCH framework: Empathy, Presence, Opinion (or Ethics), Creativity, and Hope (or Leadership). Other critical complementary skills include digital literacy, teamwork, technical proficiency, and self-efficiency. Communication, leadership, metacognition, critical thinking, collaboration, and character skills each appear in ~15 million U.S. job postings annually. Employers expect creative thinking, resilience, flexibility, and agility to rise sharply in importance by 2030.

b. Pattern Recognition and Creation: Beyond specific skills, the ability to discern and create patterns is highlighted as a fundamental meta-skill for navigating rapid change. Pattern recognition...if you start recognizing patterns fear disappears. The ability to use the patterns and ultimately pattern creation are essential for mastery and innovation.

c. Technical AI Skills: Core technical skills remain highly in-demand for building and implementing AI solutions. Top 10 most in-demand skills: Python, SQL, TensorFlow, Kubernetes, Scala, PyTorch, Linux, Git, Java, GCP. Specific AI skills like Generative Adversarial Networks (GANs) and chatbot development are showing strong growth. Data literacy is now considered 'the new workplace currency'. Cybersecurity professionals are in growing demand (32% growth in information security analyst jobs from 2022 to 2032).

d. Skill Intensity: AI and green roles require a broader and more diverse skill set than average jobs. AI roles are three times more skill-intensive, and green roles twice as skill-intensive, compared to the labour market average. The average job posting in the broader labour market demands around five skills, while green roles require approximately 10, and AI roles average 15 to 16 skills per position.

4. Addressing the Workforce Transition: Policy and Education

a. Need for Reskilling and Alternative Education: Traditional education systems are struggling to keep pace with rapid technological change, necessitating new approaches. The conventional alignment of training with labour market demands struggles to remain relevant. 59% of workers will require upskilling or reskilling by 2030. Recommended alternative skill-building formats include "apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps. Singapore's "Rise" program successfully reskilled thousands from traditional roles into digital roles, with over 80% finding jobs. Ikea reskilled 8,500 call centre employees into interior design consultants after deploying an AI bot for routine inquiries.

b. Role of Governments and Employers: Proactive strategies are crucial for managing the transition, including data-driven policy and incentivising skill development. Policymakers, academia, and employers should increasingly work together to recognise emerging occupations and anticipate employers’ needs. Governments can leverage online job vacancy data to align educational, employment, economic, and migration policies. Singapore created a national job database and incentivised companies to hire reskilled talent, steering academia towards continuous learning. Employers could benefit from resetting their hiring and talent management approaches, moving towards skills-based recruitment.

c. High-Velocity Careers and Lifelong Learning: The traditional long arc of career is being replaced by shorter, more dynamic career paths. We're going to go into a high velocity economy where rather than this long arc of career that lasts 45 years we're going to have these very fast careers that last 10 months to 36 months. Lifelong learning and upskilling are now a top priority for 75% of U.S. employers. The problem of hyper-novelty—the rate of change outpacing human adaptation—is a significant challenge to well-being.

5. Societal and Ethical Implications

a. Inequality and Disproportionate Impact: The AI revolution risks exacerbating existing inequalities and creating new divides. Women are disproportionately affected by automation... 79% of employed women in the U.S. work in jobs at high risk of automation, compared to 58% of men. Jobs requiring only a high school diploma have an automation risk of 80% while those requiring a bachelor's degree have an automation risk of just 20%. Workers aged 18–24 are 129% more likely than those over 65 to worry AI will make their job obsolete. The gap between those who leverage AI and those who don't is widening, creating more inequality.

b. The Crisis of Meaning and Purpose: Abundance generated by AI might lead to a crisis of meaning if work, a primary source of purpose, is diminished. If there is at all going to be a crisis of meaning, a mental health problem. Humans are built like all organisms to find opportunity and figure out how to exploit it, and a world of abundance without striving is problematic. Universal Basic Income (UBI), proposed by some AI leaders like Sam Altman, suggests an anticipated need for a system to provide basic income to displaced workers, which also raises questions about human purpose.

c. Risks of Misuse and Autonomous Agents: The power of AI, particularly autonomous agents, presents significant security and ethical concerns. AI agents can work indefinitely until they achieve a goal or they run into an error, raising fears about misaligned objectives. The potential for absolute devastation to arise out of a miscommunication is highlighted when AI acts autonomously. Deepfakes and AI-powered scams are already widespread, eroding trust and causing financial harm. The development of autonomous weapons and cyber warfare is a major concern, potentially leading to new high-tech organized crime and government subjugation.

6. High-Income and AI-Proof Roles

a. Human Connection Powerhouses: Roles requiring complex judgment and human interaction are highly resistant to AI displacement and often high-paying. Lawyers (100% AI resistance score), medical professions (93%), HR managers (87%). Personal financial advisors are projected to grow by 13% from 2022 to 2032.

b. Creators and Creative Directors: AI is seen as fuelling creativity, making creative careers more valuable as AI generates content but not culture or meaning. Creative directors ($140,000 to $220,000 a year), UX/UI designers working with AI ($110,000 to $170,000), content strategists ($90,000 to $145,000).

c. AI Human Hybrid Roles: New roles born from AI, focusing on implementation and collaboration with AI. AI prompt engineers ($130,000 to $200,000), AI ethics officers ($150,000 to $220,000), human-AI interaction designers ($140,000 to $190,000), AI implementation managers ($160,000 to $240,000).

d. Skilled Trades: Jobs requiring physical complexity, problem-solving in unpredictable environments, and customer interaction are highly AI-proof. Electricians (median $78,000 annually), plumbers ($72,000), HVAC technicians ($70,000+), renewable energy technicians ($85,000).

Conclusion and Recommendations

The transition to an AI-driven, greener economy is a defining moment for the labour market. While fears of widespread job loss are understandable, the evidence suggests a more nuanced picture of significant disruption balanced by new opportunities, particularly for those with complementary human and advanced technical skills.

Key Recommendations for Businesses:

Prioritise Skills-Based Development: Invest heavily in continuous upskilling and reskilling programmes focusing on AI-complementary "EPOCH" skills (Empathy, Presence, Ethics, Creativity, Leadership) and essential technical AI competencies (e.g., Python, Kubernetes, MLOps).

Rethink Talent Acquisition: Move beyond traditional degree requirements, especially for AI-intensive roles, to broaden the talent pool and focus on demonstrated skills, experience, and potential for rapid learning.

Proactive Workforce Planning: Implement ongoing analysis of job vacancy data and emerging skill trends to anticipate changes in demand and supply. This should inform internal training, external recruitment, and potential partnerships with educational institutions.

Foster Human-AI Collaboration: Design roles and workflows that leverage AI to augment human capabilities, "task lifting" mid-skill workers to higher-value activities, rather than solely as a labour-saving device.

Address Ethical and Societal Impacts: Contribute to industry best practices and policy discussions around responsible AI development, mitigating bias, ensuring data privacy, and addressing the social and ethical implications of AI adoption, including potential impacts on employee well-being and purpose.

Embrace "High-Velocity Careers": Prepare employees for a future of dynamic, shorter career arcs that require continuous learning and adaptability, supporting transitions between roles and even industries.

By strategically navigating these shifts, our organisation can harness the immense potential of AI and the green transition to drive innovation, productivity, and sustainable growth, while also contributing to a more resilient and equitable workforce.