6 min read
EU AI Act for professional services: what changed
The deadline everyone was watching just moved to December 2027. Two others already took effect in August. Here is what an expert service firm actually needs to do.
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Practical guidance for consultancies
Source-backed client work, connected knowledge, reusable workflows, and models at a cost you control - written for the people who own delivery.
AI access control for firms: what should carry over
An AI tool that ignores your firm's existing permissions is a new access problem, not a productivity win. What should carry over, and how to check.
AI cost visibility for firms, by team and client
A single AI bill tells you spend went up. It cannot tell you which client the increase came from, or whether a fixed-fee engagement is quietly losing money to usage nobody priced in. Cost visibility is the fix.
How to match the right AI model to each task
The model that runs a task should be chosen for what the task needs, not inherited from whichever tool someone had open. Here is a framework for making that choice on purpose.
How to build an AI assistant for consultancies
An assistant is a workflow with enough of a firm's own methods and sources built in that someone can hand it a brief and get a first draft that already looks like the firm's work. Here is what to define before building one.
How to turn a working method into a reusable workflow
A method becomes a workflow the moment someone writes down what stays the same every time it runs. Here is what belongs in that document, and what a real one looks like.
Connecting your firm's tools and data to AI
A firm's real knowledge lives in SharePoint, Google Drive, Slack, and a dozen other places, not in a folder someone remembered to upload. Here is what connecting AI to that stack actually means.
Why AI drafts still need review before delivery
A fast AI draft is not the same as a finished one. Here is what review of AI-generated client work should actually check, and why the firms that skip it end up slower, not faster.
Approved sources for AI: how to choose them
The open web is not a source, it is everything at once. Approved sources are the specific material a team has chosen to trust, and choosing them well is most of the work.
How to tell a sourced claim from an assumption
Every AI draft reads with the same confidence, whether a line is backed by a real source or filled in by the model. Here is how to tell the two apart before review.
AI security and trust for client work
When AI touches client work, the data questions stop being abstract. Here is what to hold any AI tool to, and how Hebno handles each one.
Reusable AI workflows for expert service teams
One person figures out a good way to do a piece of client work, and the knowledge leaves with them. Reusable workflows turn a proven method into a process the team can run.
Connected knowledge: putting your firm's work behind AI
AI that only knows what a public model was trained on writes generic drafts. Connected knowledge is how you make it work from what your firm actually knows.
See how the consultancies pulling ahead are working.
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