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External research on AI and professional work, selected and annotated by 1LAB.

Microsoft & LinkedIn

Work Trend Index 2024

In the report

  1. 75% of global knowledge workers reported using AI at work.
  2. 78% of AI users reported bringing their own AI tools to work.
  3. 59% of leaders worried about quantifying AI productivity gains.
  4. 39% of people using AI at work said their company had provided AI training.

1LAB commentary

Adoption is no longer the useful measure. The work now is to turn scattered use into better workflows, stronger capability and evidence of real improvement.

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Anthropic

Economic Index 2025

In the report

  1. 57% of observed Claude interactions showed augmentation rather than automation.
  2. Software and technical work featured heavily in observed use.
  3. AI use was concentrated in specific tasks rather than whole occupations.
  4. The index tracks how AI is used in the economy, not only what it can do in a benchmark.

1LAB commentary

The useful unit of change is usually the task, not the job title. Start by improving work around professional judgement before pursuing broad automation.

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World Economic Forum

Future of Jobs Report 2025

In the report

  1. 39% of workers’ core skills are expected to change by 2030.
  2. Analytical thinking remains the most sought-after core skill.
  3. Resilience, flexibility and agility are among the skills rising in importance.
  4. Employers expect training, upskilling and redeployment to shape their response to change.

1LAB commentary

The skills question is not separate from workflow design. New capability sticks when people have real work in which to practise it, with the right support around them.

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Stanford HAI

AI Index Report 2025

In the report

  1. 78% of organisations reported using AI in 2024, up from 55% the year before.
  2. Research reviewed in the report found productivity gains across several work contexts.
  3. Inference costs for GPT-3.5-level performance fell more than 280-fold between late 2022 and late 2024.
  4. Responsible-AI evaluation and implementation remain uneven across industry.

OECD

Generative AI and the SME Workforce 2025

In the report

  1. The survey covered more than 5,000 SMEs across seven countries.
  2. 39.1% of AI-using SMEs with a skills gap said generative AI helped compensate for it.
  3. The most common barrier to adoption was that AI was not suited to the work the SME did.
  4. The report found little effect on overall staff need for most SMEs using generative AI.

1LAB commentary

Fit matters more than novelty. For smaller organisations especially, the right question is whether AI improves a real constraint in the work — not whether it can be added everywhere.

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