Identifying and exploring the diversity and growth of green jobs

As economies transition toward sustainability, understanding green jobs is critical for policymakers, businesses, and educators. These roles are essential for aligning labor markets with sustainability goals and advancing the green economy.

However, existing occupational classification frameworks often fail to capture the dynamic and global diversity of green jobs. This limitation results in incomplete data, hindering workforce planning, policymaking, and industry adaptation.

With our co-researchers, we set out to address these gaps. Our study, Identification of an Expanded Inventory of Green Job Titles through AI-Driven Text Mining, leverages artificial intelligence (AI) to identify a more comprehensive and updated list of green job titles, describing trends, patterns, and alignment with existing occupational classification schemes.

We began with a keyword-based search of articles published between 2009 and 2024 in Scopus and Web of Science, two leading bibliographic databases for academic literature, which yielded 1,067 relevant articles. Next, we applied a retrieval-augmented generation (RAG) model—a cutting-edge tool that integrates advanced search capabilities with text summarization—to extract green job titles explicitly mentioned in the articles.

Findings: Green jobs are on the rise

Among the 1,067 articles analyzed, 10% explicitly mentioned job titles, leading to the identification of 695 unique green job titles. These roles encompass a diverse array of industries, underscoring the expanding presence of green jobs in the labor market.

Mentions of green jobs increased steadily over time, rising from 44 articles in 2009 to 162 in 2023. This growth reflects the increasing global focus on green jobs as essential to achieving sustainability goals.

Growth in green job mentions over time (2009–2024)

Early research on green jobs was concentrated in North America and Europe. Over time, coverage expanded to Asia, Africa, and Latin America, where roles such as urban afforestation specialists and decentralized-energy engineers have emerged to address localized environmental and economic challenges. The broadening geography highlights how diverse regions are responding to sustainability-related labor needs in ways unique to their contexts.

The 695 job titles span 25 sectors, including renewable energy, waste management, and sustainable agriculture. Emerging fields, such as green construction and green human resources, illustrate how sustainability principles are being integrated across traditional and evolving industries. Green jobs span a wide range of sectors, demonstrating how sustainability is reshaping both established and emerging fields.

A network diagram highlighting key areas of green job specialization

A comparison with the U.S. Department of Labor’s O*NET framework, which includes 202 green job titles, revealed that only 17% of the roles identified in our study matched existing classifications. New roles like carbon auditors and decentralized-energy engineers illustrate the need for regular updates to ensure classification systems remain relevant to the evolving green economy. Emerging roles challenge existing classification systems, underscoring the importance of updates to capture the full scope of green labor markets.

Implications for policymakers, educators and business leaders

For policymakers, the expanded inventory offers valuable insights into priority sectors such as renewable energy and sustainable manufacturing. By supporting roles such as carbon auditors and sustainable product designers, policymakers can better align workforce strategies with green transition goals. Targeted and tailored policies can help ensure workforce readiness in areas critical to driving environmental and economic outcomes.

For educators, universities and training institutions can revise curricula to prepare students for jobs in sustainability-oriented workplaces and roles within the green economy. Programs should combine technical expertise, such as renewable energy systems or waste management technologies, with socioemotional skills like adaptability and collaboration. This integrated approach equips graduates to succeed in sustainability-driven industries and emerging green sectors.

For businesses, companies can refine workforce strategies by leveraging these findings to anticipate demand for roles such as electric vehicle mechanics and renewable energy data engineers. Aligning hiring practices, training programs, and strategic planning with emerging trends can help businesses remain competitive. Addressing skill gaps proactively enables firms to adapt to the evolving economic landscape and capitalize on opportunities in the green economy.

Limitations

AI offers a scalable and efficient approach to identifying green job titles, but the study’s application has limitations. Reliance on academic literature may introduce bias, as publications from lower-income regions or informal economies are often underrepresented. These challenges underscore the difficulty of capturing the full diversity of global green job titles. To address this, researchers could broaden data sources by incorporating grey literature, job portals, industry reports, corporate sustainability disclosures, and publications from NGOs and international organizations, while actively collaborating with local experts to ensure more inclusive coverage.

Models like RAG still require careful human oversight to ensure accurate classification and avoid misinterpretation. Binary classifications (green vs. non-green), while simplifying analysis, may overlook roles with mixed or evolving responsibilities. For example, urban planners often work on projects that span both sustainable and conventional objectives, complicating their categorization. Addressing these challenges requires well-defined criteria and expert validation to contextualize findings and ensure accuracy.

Despite these constraints, AI enables faster updates and provides valuable insights into trends and patterns across regions and sectors. By combining AI-driven analysis with human expertise, stakeholders can derive actionable findings to support workforce planning, education, and policy development. These insights can contribute to restructuring labor markets to align with sustainability objectives, helping societies address the challenges and opportunities of the green transition.