AI Trace
Confirmed AI Use
12 sources cited·Reviewed and published by 1 editor·View edit history

AI Usage at a Glance

1Recommendation
2Data Analysis

Timeline

Sep 7, 2021

Data Analysis

Practice documented: Pearson uses Faethm, a workforce AI platform it acquired in 2021, to predict how technological change and economic shifts will affect jobs, skills, and hiring needs up to 15 years into the future. The platform is offered to governments, enterprises, and educational institutions in 21 industries and 26+ countries.

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Aug 5, 2022

Data Analysis

Practice documented: Faethm by Pearson offers an AI-powered Job Impact report that detects which specific jobs and tasks within an organization's workforce are most exposed to automation or augmentation by emerging technologies such as AI, robotics, and other digital tools. Enterprise customers use this feature to identify where workforce transformation is most urgent.

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Sep 15, 2023

Recommendation

Practice documented: Faethm by Pearson offers a feature called the Job Corridor that uses AI to match workers in roles at risk of automation to alternative roles — inside or outside their organization — based on skill similarity and future job demand. HR leaders and workforce planners at enterprise customers use this tool to design reskilling and internal mobility programs.

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Jan 1, 2024

Data Analysis

New evidence: Strategic Workforce Planning – Faethm by Pearson

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Jan 1, 2024

Data Analysis

New evidence: Faethm by Pearson – Labour Market Insights

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Jan 1, 2024

Recommendation

New evidence: An Overview of Job Corridor – Faethm Knowledge Base

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Jan 1, 2024

Recommendation

New evidence: The Data Science Behind Job Corridor Explained – Faethm Knowledge Base

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Jan 1, 2024

Recommendation

New evidence: Working with the Job Corridor report – Faethm Knowledge Base

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Jan 1, 2024

Recommendation

New evidence: Glossary – Workforce Classification – Faethm Knowledge Base

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Jan 1, 2024

Data Analysis

New evidence: Enterprise Platform Product Factsheet – Faethm by Pearson

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Jan 1, 2024

Data Analysis

New evidence: Working with the Job Impact report – Faethm Knowledge Base

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Jan 14, 2025

Data Analysis

New evidence: Pearson and Microsoft announce multiyear partnership to transform the future of learning and work with AI

Evidence AddedView practice →

Recent activity

Recommendation SystemVerified

Faethm by Pearson offers a feature called the Job Corridor that uses AI to match workers in roles at risk of automation to alternative roles — inside or outside their organization — based on skill similarity and future job demand. HR leaders and workforce planners at enterprise customers use this tool to design reskilling and internal mobility programs.

The Job Corridor uses Faethm's Occupation Ontology — which defines jobs by 244 standardized attributes spanning 26,620 discrete work tasks — to compare any current role against all other roles and calculate job fit scores. It receives as input an organization's workforce role data and a selected reference job, then produces a ranked list of recommended target roles ordered by job fit tier, along with skill gap breakdowns and automation risk ratings. The model filters out low-demand and high-automation-risk target roles before surfacing recommendations, and supports two modes: moving workers away from at-risk roles, or identifying internal candidates to fill planned future vacancies.

Faethm by PearsonFaethm Enterprise PlatformJob Corridor
5 sources · Faethm by Pearson · Jan 1, 2024Read full entry →
Data AnalysisVerified

Faethm by Pearson offers an AI-powered Job Impact report that detects which specific jobs and tasks within an organization's workforce are most exposed to automation or augmentation by emerging technologies such as AI, robotics, and other digital tools. Enterprise customers use this feature to identify where workforce transformation is most urgent.

The Job Impact feature takes an organization's workforce role data as input, cross-referenced against Faethm's technology taxonomy, and produces role-level and task-level breakdowns of automation likelihood and augmentation rates. It distinguishes between full automation — where technology replaces a task — and augmentation, where technology assists a worker to perform a task faster or better. Outputs include the total number of full-time equivalents (FTEs) likely to be automated within a selected timeframe, percentage risk ratings per role, and identification of which technology types drive the most impact. This analysis is used as a precursor to the Job Corridor career pathway matching feature.

Faethm by PearsonFaethm Enterprise PlatformJob Impact ReportAutomation Impact Report
4 sources · Faethm by Pearson · Jan 1, 2024Read full entry →
Data AnalysisVerified

Pearson uses Faethm, a workforce AI platform it acquired in 2021, to predict how technological change and economic shifts will affect jobs, skills, and hiring needs up to 15 years into the future. The platform is offered to governments, enterprises, and educational institutions in 21 industries and 26+ countries.

Faethm uses machine learning and deep learning models run on employer workforce data, economic indicators, and technology adoption signals to produce scenario-based forecasts of employment growth or decline, skills gaps, and workforce readiness projections. The platform is actively referenced as Pearson's skills-intelligence backbone in partnerships with both Microsoft (announced January 2025) and IBM (announced December 2025), and serves clients including Adobe, KPMG, Rio Tinto, and HM Government.

Faethm by PearsonFaethm Labour Market InsightsFaethm Enterprise Platform
3 sources · Microsoft News · Jan 14, 2025Read full entry →

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3 practices

Cite this record

Trace Foundation. (2026). Faethm: documented AI practices (data as of 2026-07-20) [Data set record]. AI Trace. https://www.aitrace.org/r/company/a9adc3ab-c95c-4ec5-8100-c31556d1329d. Accessed October 5, 2026.

Stable link
https://www.aitrace.org/r/company/a9adc3ab-c95c-4ec5-8100-c31556d1329d
Data as of
July 20, 2026
Last verified
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