AI market intelligence
The AI market, read with data — not hype.
Who really builds AI, whether we are in a bubble, how to tell genuine AI from AI-washing, and how to invest in it — for operators, analysts and investors.
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View all articlesAgentic engineering vs. agentic washing: how investors tell the difference
"Agentic" is on every pitch deck now. A practical framework for investors and decision-makers to separate real agentic-engineering competence from marketing relabeling, grounded in 2026 adoption data.
AI abuses and scandals: the patterns
From deepfake fraud and voice cloning to data scraping and overstated AI claims — the recurring categories of AI abuse in 2026, and the concrete lessons each one holds for users and investors.
AI bubble vs the dot-com bubble: 5 comparisons
Is 2026 a rerun of 2000? Five concrete comparisons between the AI boom and the dot-com bubble — valuations, profits, concentration, capex and breadth — and what each one tells you.
AI Act Article 50: an investor's lens on AI-washing
From 2 August 2026, the AI Act's Article 50 transparency duties become a real regulatory risk. How investors and boards can gauge a company's exposure, where AI-washing starts, and which detection tools help.
AI startup due diligence: a checklist for angels and operators
Before you wire money into an 'AI startup', work through this checklist — data, model, team, moat and the AI-washing red flags. Adapted from professional due-diligence practice.
AI-washing: how to verify whether a company really does AI
A practical, source-based guide to telling genuine AI from marketing. Built on the CFA Institute's due-diligence framework, with a checklist, red flags and the filings to read.
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Company verification
We report facts with sources and dates. We never label a named company as fraudulent or "AI-washing" as a statement of fact — we present verifiable data and the questions an investor should ask.