Andela Research Finds That 53% of AI Job Postings Seek Skills That Don't Match Job Title; Also Identifies New Emerging Tech Roles
Andela's first-of-its kind skills taxonomy reveals mismatches in tech hiring while establishing new methodology to fix gaps, get ahead of emerging skills
Andela, the AI-native talent and services platform helping enterprises adopt and deliver AI at scale, today announced that its newly launched Emerging Skills Research found that the industry is inventing roles faster than companies can name them or accurately match skills to job titles.
Andela's Emerging Skills Research analyzed 47,101 technical job postings from Fortune 500 companies and scored 2,026 distinct skills. It found that:
Among the roughly 1,832 postings titled for roles like "AI Engineer" and "ML Engineer," 53% require skills drawn from at least two different established roles. For familiar titles like "AI Engineer," companies are seeking a different, unnamed role that includes skills such as LLM orchestration, autonomous agents, and vector databases. Or, companies hire "data scientists" but then ask them to ship LLM agents.
23 skill bundles were identified that recur across Fortune 500 hiring, but don't map to any standardized job title. Within these findings, Andela identified 8 genuinely new roles, 14 hybrids of old and new, and 1 discarded for accuracy. Two example new roles are MLOps Pipeline Engineer, which bridges five established roles, and LLM Application Engineer, a contemporary AI engineer who builds on foundation models rather than training them.
Of all the emerging skill combinations, 6,758 job postings carry the LLM Application Engineer skill bundle without naming it, reflecting a lag between the technology frontier and what companies know how to hire for.
The findings underscore the challenges companies face, driven by the unprecedented speed of change in the post-AI era, to accurately identify emerging skills, name them, and attach them to job roles. Mismatches result in lost time, money, and opportunity for both employer and employee. Job descriptions written for yesterday's roles filter out the candidates companies actually need. Companies that fail to see emerging needs for human skills, especially as AI changes what it can do, will continually chase the wrong thing, and companies who hire today for yesterday's roles will likely accrue "talent debt" alongside technical debt.
Getting Ahead of the Market
"AI is changing tech workflows faster than ever, and we need new ways to get ahead of those changes," said Carrol Chang, Andela CEO. "This groundbreaking research, based on our proprietary skills taxonomy updated for the AI world, provides a headlight, not a rear view mirror. With it, companies will identify emerging roles and skills ahead of the market, enabling both enterprises and employees to be more strategic and successful."
Most role research tracks job posting volumes over time, requiring years of data to see a trend. Andela's methodology, which is patent pending, detects emergence from a single snapshot of job data, catching roles as they form versus confirming already existing roles. We feel this is especially important now because, according to Gartner® analysts Neal Solanki, et al., "By 2030, the half-life of technical skills will dramatically shorten to two to five years, making workforce planning adaptivity a competitive differentiator.*"
Andela's core innovation in the research is the skill bleed graph, vintage scoring mechanism, and its proprietary skills taxonomy. Every skill has a home role. When a new role is forming, skills bleed into other areas. By mapping them as they cross boundaries, Andela surfaces skill bundles that travel together across old role boundaries, signaling the formation of a new role.
"Any gap between the role a company thinks it's hiring for and the role the work requires becomes a structural liability," said Cory Hymel, Andela's Head of Research and report author. "Our methodology of reading skills inside job postings enables us to see the gaps so customers and talent can better fill them."
The most emerging tech roles identified in the research include: MLOps Pipeline Engineer, LLM Application Engineer, FinOps Reliability Engineer, Docs-as-Code Engineer, Product Front-End Engineer, Lakehouse Analytics Engineer, DevSecOps Security Engineer, and SecOps Observability Engineer.
About Andela: Andela is an AI-native data and services company, powering AI transformation for global enterprises. By combining continuous assessment and always-on upskilling, Andela is the human layer that helps enterprises hire and deploy AI engineers at scale, build AI solutions, and assess and upskill teams on emerging technologies. Andela's diverse talent ecosystem spans over 135 countries and is highly skilled in advanced technologies to support Application Development, Artificial Intelligence, Cloud & DevOps, Data Engineering, and more. The world's best brands trust Andela, including GitHub, Mastercard, and Mindshare.
*Gartner Report, Get Started With Dynamic Workforce Planning for AI: Data-Driven Continuous Adaptation, By Neal Solanki, Lily Mok, etc., July 2026. Gartner is a trademark of Gartner, Inc. and/or its affiliates. SOURCE Andela
