What we're learning about AI in production.
Written clearly. Naturally, our articles are partly researched and written with automation; a human reviews them and publishes them.
AgentsAn AI employee is not a chatbot. This is the real difference
A chatbot answers your question; after that you still do all the follow-up steps yourself. An AI employee takes on the work from start to finish, connected to your CRM, ERP, email and calendar, while a human stays in control. The real difference between responding and doing, with examples and when a chatbot is in fact enough.
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Our approachWhy your AI pilot never reaches production (and how to break the cycle)
The demo succeeded, the steering committee was enthusiastic, and yet six months later your AI pilot is still not in production. Four structural reasons why pilots stall (integration, governance, ownership and adoption), backed by figures from McKinsey, MIT, KPMG and others, plus how to actually get it live.
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AI in the marketShadow AI: what it is, what it costs, and how to prevent it
Three quarters of employees already use AI at work, often beyond IT's view. What Shadow AI is, what it costs (GDPR exposure, data breaches, reputational damage), what regulators such as the Dutch DPA and the EDPS expect, and how to curb it with approved, transparent AI rather than a ban.
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Saving time & moneyHow much time do you really save with an AI employee? The numbers by role
What does an AI employee really deliver, in hours and euros? The measurable real-world figures by role: customer service, financial administration, HR and quotations. Plus an honest view of when AI delivers less than hoped, and how to estimate a realistic payback period.
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Documents & dataWhat is RAG? The technology behind an AI that truly understands your documents
The knowledge exists, scattered across thousands of documents, but finding it takes hours. RAG (Retrieval-Augmented Generation) is the technology behind a knowledge-base agent that searches your own documents and answers with sources. What it is, how it works, and when it does or does not make sense.
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