Insights on AI research for regulated domains
Three tax questions, two AI tools, one clear lesson: for professional research, verifiability beats confidence.
The era of making models bigger is ending. Five paradigms are replacing brute-force scaling — hybrid architectures, inference-time reasoning, world models, self-improvement loops, and hardware co-design. What each means for AI in regulated industries.
Federal law is published in Dutch and French. Regional codes exist in one language only. Rulings follow the language of the procedure. A monolingual AI tool misses half the corpus.
$8 billion. $1.8 billion. $133 million. The world's best-funded legal AI companies are proving the model works. They're also proving what it can't do for Belgian tax.
79% of legal professionals now use AI. Tax firms tripled adoption in one year. But the real story isn't the average — it's the widening gap between strategic adopters and everyone else.
Harvey raised $760M. Blue J raised $133M. Neither can answer a question about erfbelasting in Brussels. Here's why that creates an opportunity.
When Belgian tax sources disagree, the worst thing an AI tool can do is pick one and act confident. Here's what honest uncertainty looks like.
Accuracy claims without published metrics are marketing. Here's what it takes to measure legal AI honestly, and why the industry avoids it.
When AI-assisted tax research leads to wrong advice, Belgian law is clear: the professional pays. But that's actually the strongest argument for using transparent AI — not against it.
When Belgium's programme law amends 47 provisions overnight, what happens inside the AI tool you rely on? A transparent look at the ingestion pipeline.