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AI adoption roadmap

From scattered experiments to a governed capability.

AI adoption roadmaps from Aun & Co.: a phased, workflow-level plan for bringing AI into a professional practice — built by a firm that has done it in its own.

Most AI adoption fails in one of two ways: a ban nobody obeys, or a free-for-all nobody controls. A roadmap is the third path — a phased plan that starts from your actual workflows, ranks them by value and risk, and sequences adoption so capability and control grow together. Aun & Co. builds these roadmaps from practice, not theory: the firm adopted AI across its own operations — intake, document preparation, administration — with human approval gating every output, and the roadmap method is that experience made transferable.

The work spans
  • Workflow inventory: where AI genuinely helps, where it should not go
  • Value-and-risk ranking to sequence what gets adopted first
  • Tool selection criteria matched to each workflow tier
  • Phase design: pilot, sandbox, supervised live, governed scale
  • Milestones, owners and the review gates between phases
  • Leadership approved 'adopting AI' and no one owns turning the sentence into a plan.
  • Teams are already experimenting tool by tool and the experiments are diverging.
  • You want the efficiency gains without betting sensitive workflows on an untested tool.
  • A previous AI initiative stalled and the second attempt needs structure the first lacked.

The roadmap is built bottom-up from tasks, not top-down from technology: each workflow is scored for the time AI saves against the damage an error costs, and adoption is sequenced along that curve — high-value, low-consequence work first. Every phase ends at a gate: results reviewed, controls tested, and only then the next tier. The document names owners and dates, because a roadmap without either is a slide.

04 · What you get

Built from lived adoption

The method comes from the firm's own AI rollout in a working legal practice — the failure modes in the roadmap were encountered, not imagined.

Sequenced by consequence

Adoption ordered along the value-risk curve, so early wins fund confidence while high-stakes workflows wait for proven controls.

Gates, owners, dates

Each phase closes with a review gate and a named owner — the difference between a roadmap and a wish.

A typical engagement: a professional office of a dozen people wants AI in its document and intake work. The roadmap sequences four workflow tiers over two quarters, with a sandbox phase and approval gates; by the second gate, the informal tool sprawl has been replaced by three vetted systems under one policy.

Described in abbreviated, anonymised form to preserve client confidentiality.

Where should a professional practice start with AI adoption?

With the workflows where AI saves real time and an error costs little: internal summaries, first drafts of routine documents, administrative processing. Client-facing and judgment-heavy work comes later, behind proven review gates — sequence is the safety mechanism.

How long does structured AI adoption take?

A meaningful first phase — pilot workflows live under supervision — typically lands within one to two months; a practice-wide governed capability takes two to four quarters depending on size. Slower than a ban, faster than a failure.

What does the roadmap engagement deliver?

A written plan: the workflow inventory and ranking, the phase sequence with gates, tool criteria per tier, and named owners with dates. It is designed to be executed by your team — with the firm reviewing at the gates, not resident in the building.

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