AI automation that does the work software should be doing — for Professional Services

Professional-services firms — accounting, tax, law, audit, management consulting — share an unusual operational pattern: their product is hours of expert time, their cost base is people, and their margin lives or dies on utilisation, write-offs, and pricing discipline. Most mid-size firms in DACH and the wider EU still run on a mix of a 15-year-old practice-management system, a fleet of Excel spreadsheets, and the personal organising systems of senior partners. The buying pattern is conservative — partners are also owners, and they spend their own money — but increasingly forced by talent attrition: younger associates and managers will not stay at firms where the tooling is 20 years behind their consumer experience.

• ▸Document-classification and extraction (contracts, invoices, financial statements) is the highest-ROI starting point — saves senior-time on grunt work.
• ▸Legal/tax research summarisation must use retrieval-augmented generation grounded in firm-licensed databases — never raw LLM "knowledge" for opinion work.
• ▸Confidentiality first — every AI tool must have EU residency, no-training defaults, and per-matter logical isolation.
• ▸Time-capture intelligence — assistants that propose timesheet entries from calendar + email + document activity recover 15–25% of lost billables.
• ▸Drafting assistants tied to the firm's own templates — generic LLMs produce plausible but unusable first drafts for regulated jurisdictions.
• ▸Audit trail for every AI-touched deliverable — clients are starting to ask which parts of advice were AI-assisted.

For a DACH tax advisory boutique, we built a contract-extraction agent that classifies and structures incoming client documents — reducing administrative time per engagement by 9 hours on average, freeing senior associates from intake grunt-work.