Building a Realistic AI Roadmap for Your Firm

Many firms now have a handful of partners who are enthusiastic about AI — and a much larger group who are:

curious but cautious;
sceptical of hype; and
already stretched on time and budget.

The missing piece is often a simple, realistic AI roadmap: not a 50‑page strategy deck, but a clear 12–18 month plan that says:

what you will try;
how you will manage risk; and
how you will know if it was worth it.

This article sets out a practical approach to building a realistic legal AI roadmap for a small or mid‑sized UK firm.

1. Start with outcomes, not tools

Before you talk about products or models, answer a more boring question:

“If AI quietly worked well here in 18 months, what would actually look different?”

Typical answers might be:

supervisors spend less time reconstructing what has happened on files;
fewer time write‑offs due to missing or poor time records;
less partner time on first‑draft letters or chronologies;
support staff able to handle more drafting and organisation.

Write down 3–5 concrete outcomes tied to pain you already feel. They will anchor every decision that follows.

2. Inventory your existing systems and data

Your roadmap lives in reality, not on a blank sheet. Briefly map:

your current case management, DMS and email stack;
where documents actually live;
how matters are opened, supervised and closed;
any AI or automation already in place.

This helps you avoid:

buying tools that duplicate what you already have; or
designing workflows that assume a clean data environment that does not exist.

It also reveals obvious prerequisites, such as:

“We cannot sensibly do AI summarisation until emails are routinely linked to matters.”

3. Pick a small number of flagship use cases

A good roadmap focuses on a few flagship workflows, for example:

email thread summaries for supervision and handovers;
matter chronologies as a single source of truth;
AI‑assisted time capture from emails and documents;
drafting short client updates and internal notes.

For each, sketch:

where the data comes from;
who will use it (partners, juniors, PAs);
what “good” looks like (for example, “cut average time to first draft by 30%”).

These become your pilot projects in the first 6–12 months.

4. Build governance and risk thinking into the roadmap

An AI roadmap without governance is just a wish list. To keep risk under control, include in your plan:

a firm‑wide AI policy written in plain language;
a basic AI risk assessment organised by use case (research, drafting, summarisation, time capture, etc.);
a logging and supervision model (how AI use will be recorded and reviewed).

You do not need perfection on day one, but you do need:

to know which tools are approved; and
to be clear that lawyers remain responsible for advice, documents and time records.

Governance items should have owners and deadlines like any other project tasks.

5. Phase the roadmap: 0–6, 6–12, 12–18 months

A practical way to structure your roadmap is in three phases.

Phase 1 (0–6 months): Foundations and quick wins

tidy the basics (matter data, email filing, templates);
run one or two tightly scoped pilots (for example, email summaries + time capture) with a small group;
implement your first AI policy and simple logging;
choose or confirm your core platform (for many firms, that will be case management with AI built in).

Phase 2 (6–12 months): Expand successful workflows

extend pilot workflows to more users and practice areas where they work;
refine prompts, templates and supervision patterns based on feedback;
add one or two new workflows (for example, chronology building or client updates);
start collecting simple metrics (time saved, satisfaction, write‑off trends).

Phase 3 (12–18 months): Consolidate and integrate

decide which AI features are “business as usual” and document them accordingly;
integrate AI logs and metrics into management information;
review vendor relationships and pricing now you know what you actually use;
revisit your AI policy and risk assessment with real experience behind you.

The roadmap should remain flexible, but this rough phasing keeps you honest about what can be achieved when.

6. Plan for change management, not just procurement

A roadmap that assumes everyone will spontaneously adopt new tools is fantasy. Include explicit steps for:

training (short, workflow‑based sessions rather than abstract AI lectures);
support routes (who people ask when something does not work or looks wrong);
identifying and supporting internal champions in each team.

Be realistic: some partners will move faster than others. That is fine as long as:

experiments are controlled; and
you do not end up with an ungoverned patchwork of personal tools.

7. Budget with uncertainty in mind

AI‑related costs can come from:

licensing case management or DMS features;
cloud AI usage (per‑document / per‑token charges);
consulting or integration work;
time spent on training and governance.

Your roadmap should:

prioritise investments that support multiple workflows (for example, matter‑level summarisation) over niche experiments;
favour pricing models that are predictable for small and mid‑sized firms;
include a small experimentation budget for trying new ideas within governance boundaries.

Document your assumptions so you can revisit them after 6–12 months with real data.

8. Keep the roadmap visible and revisited

Finally, avoid the classic fate of strategies: written once, then forgotten.

Put the AI roadmap on one page for partners and practice heads.
Review progress quarterly in management meetings.
Adjust based on usage, risk incidents and external developments.

Treat it like any other operational plan: living, revisited and tied to actual behaviour.

Where OrdoLux fits

OrdoLux is being designed to make a sensible AI roadmap easier to execute:

common target workflows — email summaries, chronologies, time capture, task extraction, simple drafting — are built into the matter file;
AI activity is logged and visible at matter level for supervision and audit;
prompts and templates can be treated as firm precedents, not hidden configuration;
pricing is intended to be predictable for small and mid‑sized firms, so you can plan rather than guess.

That way, your roadmap is not about chasing every new tool. It is about making your existing work sharper, with AI quietly supporting the way your firm already practises law.

This article is general information for practitioners — not legal advice, management consulting or procurement advice for any particular firm.

Looking for legal case management software?

OrdoLux is legal case management software for UK solicitors, designed to make matter management, documents, time recording and AI assistance feel like one joined‑up system. Learn more on the OrdoLux website.