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selection · ai for legal practice

Integration and workflow fit.

A tool that lives in another tab, needing documents pasted into it, will lose to the tool that is already where the work is — even if it is worse.

begin here

Where is your firm?

Start a conversation with the AI Adoption Concierge, already scoped to integration & workflow fit. Pick a starting point, or describe your situation directly.

AI Adoption Conciergeintegration & workflow fit · orientation, not legal or ethics advice
Tell me what systems the firm runs on — document management, practice management, and where drafting actually happens. I'll help you assess whether a tool will sit inside that or beside it.

The strongest predictor of whether a firm's people use an AI tool is not how good it is. It is how far it sits from where the work already happens. A capable system that requires opening a separate application, locating a document, copying it across and pasting the result back will be used enthusiastically for two weeks and then quietly abandoned, because each of those steps is friction repeated dozens of times a day. Integration also determines whether the firm can see and govern usage at all: a tool inside the document management system leaves a record, and a browser tab does not. Selection decisions that weigh capability heavily and integration lightly are the ones most often regretted.

mechanisms

What integration actually means.

Several distinct things, frequently conflated in vendor conversations.

Document system

Whether it reaches matter files where they live, or requires documents to be moved to it.

Practice management

Whether it knows about matters, clients and time — the context that makes output useful rather than generic.

Where people work

Email and the word processor, which is where most legal work is actually produced.

Permissions & ethical walls

Whether access honours matter-level restrictions, or exposes anything indexed to anyone who asks.

Visibility

Whether the firm can see what is being used and how, which governance depends on entirely.

Identity

Single sign-on and provisioning, so access ends when someone leaves.

methodology

What the evidence shows — and what we examine.

How fit is assessed before committing.

Map the existing workflowWatch how the task is actually done now, step by step, before deciding where a tool would sit.
Count the added stepsEvery context switch is friction paid repeatedly. Two extra clicks per use is a large annual number.
Test the permission modelConfirm ethical walls hold inside the tool, not just in the system it draws from.
Check what usage data existsIf the firm cannot see usage, it cannot govern, measure or support it.
what's at stake

What integration decides.

Mostly whether the investment produces anything at all.

whether anyone keeps using it whether usage is visible to the firm whether ethical walls hold friction paid on every single use whether shadow tools fill the gap return on the licence

Poor fit produces shadow AI.

When the approved tool is awkward and a consumer chatbot is one tab away, people use the chatbot — with client material, outside anything the firm can see. Integration is a confidentiality control, not just a convenience.

common questions

Integration — practical questions.

How much does integration really matter against capability?

More than most selection processes assume, and the asymmetry is worth stating plainly: a moderately capable tool that is already where people work will out-deliver an excellent one that is not, because it gets used. Capability differences narrow as the market matures; friction does not. This does not mean choosing a weak tool for convenience, but it does mean that a large capability advantage should be discounted heavily if it comes with a separate application and manual document movement.

What about ethical walls?

This deserves specific attention and is often discovered late. A tool indexing firm documents to answer questions can surface material across matters unless it honours the firm's access restrictions, and not every product models matter-level permissions properly. The question to put to a vendor is not whether they "support permissions" but how restrictions are enforced at retrieval — and it should be tested rather than accepted on assurance, using a document that a test user should not be able to reach.

Does it need to integrate with practice management?

It depends on the task, and the benefit is larger than it first appears for anything client-facing. A tool that knows which matter it is working on, who the client is, and what the engagement covers produces output requiring far less correction than one operating on a document in isolation. For firms running an integrated practice system, that context is the difference between a generic assistant and one that behaves as though it works there. For purely internal research tasks it matters much less.

Should we build or buy?

Most firms should buy, and the ones that should build usually already know it. Building requires sustained engineering capacity, not a project — models change, integrations break, and the thing needs an owner indefinitely. The realistic middle path for firms with real technical capability is configuring and connecting bought components rather than building from scratch, which captures workflow fit without taking on a product roadmap the firm has no business maintaining.

related

Related specialization areas & resources.

Will it fit where people work?

Describe your document and practice systems. The Institute will help you assess fit before you commit.

AI adoption conciergeorientation · not legal or ethics advice
Tell me what systems the firm runs on — document management, practice management, and where drafting actually happens. I'll help you assess whether a tool will sit inside that or beside it.