Founders’ takes: Why we need European AI employees
Summary
Lucas Spreiter of Venta AI argues that AI is shifting work from human labour to AI labour and that Europe must build its own “AI employees” rather than import them from the US or China. The piece traces Europe’s deep research roots (LeCun, LSTM, DeepMind, Stable Diffusion) and contrasts that legacy with the current commercial dominance of American and Chinese players. Spreiter highlights startups such as Mistral, Black Forest Labs, Langdock and Venta AI as examples of Europe trying to keep research, models and workflows local. He stresses that Europe’s rule-based industries (manufacturing, logistics, finance, insurance, sales) are prime candidates for AI employees, but warns the continent must act quickly or risk outsourcing the economic value creation that comes with AI labour.
Key Points
- AI is evolving from a tool into colleagues that can execute end-to-end workflows — “AI employees” that perform complex, rule-based tasks.
- OpenAI, Google, Meta and Anthropic currently dominate model development and infrastructure; China is rapidly closing the gap with state-backed efforts.
- Europe invented many foundational AI technologies but often loses out on commercialisation to US and Chinese firms.
- European startups (Mistral, Black Forest Labs, Langdock, Venta AI) are building local solutions that respect EU norms, GDPR and industry-specific workflows.
- Sales automation is a clear early use case: highly process-driven, high value, but requiring localised approaches due to compliance and cultural differences.
- If Europe fails to train, deploy and scale AI employees domestically, it risks importing AI labour and losing the associated economic value creation (Wertschöpfung).
Context and Relevance
This article is important because it reframes the AI competition as one about labour and economic sovereignty, not just models. For European businesses and policymakers, the piece highlights a strategic inflection point: owning the AI labour stack — from models to applied workflows — is necessary to capture productivity gains and retain economic value. The analysis ties into broader trends: rising AI agent capabilities, geopolitical competition over compute and models, and enterprise demand for compliant, localised solutions.
Why should I read this?
Short and real: if you care about who gets paid when AI runs your company (and who controls the data, rules and profits), this explains why building AI workers in Europe matters. It’s a quick reality check — research talent alone won’t win the race unless startups and industry actually commercialise local, compliant AI that fits European workflows.
Source
Source: https://thenextweb.com/news/europe-needs-build-ai-employees
