How to Evaluate AI Tools for Your Firm (Without Getting Sold)

Every professional services firm is being pitched AI tools. Vendors email the partners. Conferences are full of exhibitors who each claim to be the one you need.

Two things go wrong. Some firms buy several tools and adopt none properly. Others buy nothing and wait for clarity that does not arrive. Both come from the same gap: no agreed way to judge a tool. This post gives you one.

A disclosure first. BriefingHQ also sells services and builds software for professional services firms. Run this checklist on us too.

Start with the problem

The common mistake is browsing tool directories and attending demos, then working out where a tool might fit. Reverse that order.

Pick one task that is painful, repetitive or error-prone. Describe it clearly before you look at a single product.

Examples of good problem statements (the numbers are placeholders, so use your own):

• Our research team spends days per project turning industry reports into a market overview.
• Junior consultants spend a large share of each week formatting slides instead of analysing.
• Lawyers read hundreds of pages of due diligence documents on every deal.
• Recruiters screen every CV by hand and worry about missing good candidates.

Examples of weak ones:

• We need to be more innovative.
• Our competitors use AI, so we should too.
• We want to improve efficiency. (Which efficiency, and where?)

Once the problem is clear, you have a filter. Every tool gets one question: does it solve this problem better than what we do today?

The five criteria

1. Use case fit

This is the most important criterion and the one most often judged badly. Vendors demo on their own prepared data. What matters is whether the tool works on your data, in your workflow, on your task.

• Ask the vendor to demo your use case, not theirs.
• Ask for a trial where your team works on real material.
• Decide what “good enough” looks like before the trial starts.
• Judge the quality of the output, not only the speed.

Signal	Strong fit	Weak fit
Demo relevance	Run on your use case with your type of data	Prepared scenarios from other industries
Output quality	Mostly usable with light editing	Needs major rework or is often wrong
Workflow	Fits how the team already works	Needs the whole process changed
Edge cases	Handles unusual inputs sensibly	Breaks or invents things on non-standard input
Learning curve	Usable after a short session	Needs days of training before basic competence

2. Data security

You handle confidential client information, sometimes privileged material. Any tool you use has to protect it.

What to require:

• A data processing agreement that meets your UK GDPR duties.
• Written confirmation about whether your inputs are used to train or improve the vendor’s models.
• Independent security assurance, such as SOC 2 Type II or ISO 27001.
• A clear answer on where data is processed and stored.
• Deletion of your data on request, with confirmation.
• Access controls, so you can limit who uses the tool on which matters.

Questions to put to every vendor:

• Where is our data processed and stored?
• Is our data used to train or improve your models?
• Can we see your data processing agreement before the trial?
• What happens to our data if we cancel?
• Have you had a data breach, and what changed afterwards?

A vendor who hesitates on these questions has told you something. The good ones have answers ready.

3. Ease of adoption

The best tool is worthless if nobody opens it. Adoption depends on how easy the tool is to learn, how well it fits the existing workflow and whether people trust what it produces.

Measure these during the trial:

• How long a new user takes to finish a first task.
• How often users ask for help or give up.
• Whether people keep using it voluntarily after the trial ends.
• What workarounds they invent. Workarounds are a sign the tool does not quite fit.

A tool that is slightly less capable but much easier to use will often beat a stronger one that nobody can figure out.

4. Total cost

The licence fee is rarely the whole cost. Ask what else the tool will cost you.

Cost	What to ask	Often overlooked?
Licence	Price per seat or per volume, and what happens at renewal	No
Setup	Who configures it, and what does that cost	Sometimes
Training	Hours per person, multiplied by their hourly rate	Usually
Admin	Who owns the tool day to day, and for how many hours	Usually
Integration	What it must connect to, and who builds that	Often
Transition dip	How much output you lose while people learn it	Almost always

Add these up for your own firm before you compare prices.

5. Vendor stability

The AI market moves fast. Products change, get acquired or close.

Ask:

• How long has the vendor operated?
• How are they funded?
• How many customers do they have in your sector?
• Is the roadmap realistic?
• Can you export your data and configuration if you leave?

The last question matters most. If you build workflows in a tool that shuts down, you want to take the work with you.

Run a proper trial

Once you have one or two tools on the shortlist, run a structured trial. A casual “have a play” does not count.

Set the success metrics before you start. Good ones are specific: “contract review time falls by the amount we agreed in advance”, or “most testers want to keep using it”. Poor ones are vague: “the team likes it”, “we see improvement”.

Testers tell you what they think you want to hear. If leadership is visibly keen, ratings drift upward. Use anonymous feedback and ask for specifics: “How many minutes did it save you today?” produces data. “Did you find it helpful?” produces politeness.

Watch behaviour as well as answers. If testers stop using the tool halfway through, that is a stronger signal than any survey.

Red flags in the sales process

Red flag	What you hear	What it may mean
No trial	We need custom setup before a trial is possible	The product may struggle outside controlled conditions
Vague on data	We take security very seriously	Data controls may not be fully built
Claims everything	Research, analysis, writing and more	It may do none of them particularly well
Urgency	This price ends on Friday	A sales tactic. Ask what the price is next month
No references	Happy clients we cannot name	They may not have references in your sector
Long lock-in	A better rate for three years	They may need the commitment because customers leave

A good sign is a vendor who says: “We are strong at X and not suited to Y.”

Score the shortlist

After the trial, score each tool from 1 to 5 on the five criteria, weighted to suit your firm. The weights below are an example, not a rule.

Criterion	Example weight	Tool A	Tool B
Use case fit	30%	Score 1 to 5	Score 1 to 5
Data security	25%	Score 1 to 5	Score 1 to 5
Ease of adoption	20%	Score 1 to 5	Score 1 to 5
Total cost	15%	Score 1 to 5	Score 1 to 5
Vendor stability	10%	Score 1 to 5	Score 1 to 5

A law firm handling privileged data might raise the weight on security. A consultancy in a crowded market might raise the weight on fit. The score does not produce a mathematically correct answer. It makes the discussion about evidence instead of the most persuasive demo.

Build or buy

For most mid-market professional services firms, buy. Building means design, testing, security review and maintenance, and it needs a named owner for as long as the tool exists.

Buy when:

• An existing tool covers most of your use case.
• You have no in-house technical capability.
• Speed matters more than customisation.
• The vendor has a track record in your sector.

Build when:

• Your workflow is unusual and nothing existing covers it.
• You have the technical capability and budget to maintain it.
• The tool will become a real point of difference for the firm.
• You need control over the whole data pipeline.

After you buy

Buying is the start. Firms that get value invest in adoption, not only procurement.

• Name an internal owner for the tool.
• Run training sessions, not just a link to the documentation.
• Set usage targets for the first 90 days.
• Review adoption monthly.
• Measure the same metrics you set in the trial.
• Decide at the six-month mark, on actual use, whether to renew or cancel.

For a wider plan, see the 90-day AI adoption roadmap and the AI readiness checklist. If you want a quick read on where your firm stands first, the free AI readiness assessment takes about three minutes.