Read the full article: Net Effects: Balancing AI-Related Job Losses with AI-Created Roles by Sector and Region

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Net Effects: Balancing AI-Related Job Losses with AI-Created Roles by Sector and Region

Artificial intelligence (AI) is rapidly reshaping work. On one hand, many routine tasks – from data entry to customer support – can now be automated, leading firms to cut staff. On the other hand, new AI-intensive roles are emerging, such as data annotators, AI trainers, and machine-learning engineers. Analysts and surveys paint a mixed picture. For example, the World Economic Forum’s 2025 Future of Jobs report projected that by 2030 AI could create about 170 million new roles while displacing 92 million, yielding a net gain of ~78 million jobs globally (arstechnica.com). But most of those gains and losses are expected over many years. In the near term (through mid-2026), the effects are more modest and uneven by industry and region.

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Read the full article: Twenty Company Case Studies: Linking AI Deployments to Workforce Outcomes

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Linking AI Deployments to Workforce Outcomes

Companies across industries are now explicitly tying AI adoption to workforce changes. By mid-2026, firms large and small have reported productivity gains from AI while reshuffling their headcounts. For example, a Reuters analysis found that some 312,000 tech-sector jobs were cut from 2023–2026 even as AI was cited as the rationale in 78% of cases (www.aiexposure.org). In this article we profile 20 major companies — in banking, technology, retail, telecom and more — and document how each has quantified headcount changes linked to specific AI initiatives. We compare these outcomes to less-automated peers and highlight how companies are reallocating talent. (Figures and quotes below come from earnings calls, filings and news reports through June 2026.)

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Read the full article: G7 Comparison: AI-Attributed Job Losses in April–May 2026

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G7 Comparison: AI-Attributed Job Losses in April–May 2026

The early 2026 data show that many advanced economies saw a mix of growth and adjustment in employment. To compare AI-related job losses in the G7 (United States, Canada, UK, France, Germany, Italy, Japan), we use the latest labour-force releases for April–May 2026. We align each country’s industry and occupation codes (using international standards like ISCO/NACE) and apply a common AI exposure index (measuring how much tasks involve digital intensity versus human/tacit skills). We also account for differences in GDP growth and labour policies, since faster-growing economies tend to add more jobs overall, and strong welfare systems can affect layoff timing.

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