AI may make legal organisations faster while quietly making them more similar.

The threat isn’t that AI will take the legal function’s job. It’s that it may train the legal function to stop doing the part of the job that cannot be delegated: thinking.

Most organisations treat AI law as a reading assignment.

An EU Regulation is supposed to apply uniformly.

AI liability is not waiting for the EU to invent an entirely new tort system.

The copyright fight over AI isn’t theoretical anymore.

If you’re still reading AI risk as “what the AI Act says,” you’re optimizing for the wrong thing.

Most investment research processes fail because they are improvisational. You download two annual reports, skim a chart, ask a chatbot for a “bull case,” and call it diligence.

The goal of this phase is not to ask the AI to predict next quarter’s EPS or generate a generic “buy/sell” rating. Long-term investors need a structured, comparative judgment on business quality, financial durability, capital allocation, and valuation.

Company filings tell you what management chooses to disclose. Market data and independent sector research tell you what those disclosures meant in practice: how accounting earnings translated into hard cash, how leverage behaved through economic cycles, and whether the underlying industry economics actually support a decade-long hold.

In long-term investing, failures rarely stem from weak financial models; they stem from weak inputs. If your source documents are incomplete, outdated, or scattered across dozens of browser tabs, no amount of clever AI prompting will save your analysis.