By now, your team is definitely using ChatGPT. Some of them are probably using it in ways you don't know about. And you're probably wondering: which AI tools should we officially support? Which ones should we avoid? How do we evaluate this without hiring a consultant?
Here's a simple framework I use when evaluating AI tools for professional services firms. It's not fancy, but it works.
The Five Criteria
Every AI tool should be evaluated on five dimensions. Give each one a score from 1-10 (or just describe it in terms of high/medium/low). Then look at the pattern.
1. Security & Data Privacy
The question: Where does our data go, and who has access to it?
This is table-stakes. If the tool sends data to a third-party server, can you trust that vendor with client information? Is the data encrypted in transit and at rest? Is there a Data Processing Agreement? Can you audit what happens to your data?
For regulated firms (healthcare, law, finance), this is non-negotiable. For others, it's still critical.
Red flags: Vendor won't answer your data security questions. No DPA. No audit trail. Vendor uses your data to train models.
2. Accuracy & Reliability
The question: Can we trust the output?
Some AI tools are very good at specific tasks. ChatGPT is decent at email drafting but unreliable at contract analysis. Some tools work great for 90% of inputs and fail catastrophically on the remaining 10%.
Run the tool on real work. Measure accuracy. Be honest about the failure modes. Then ask: is this failure rate acceptable for how we want to use it?
Red flags: Vendor claims 95%+ accuracy with no nuance. Your testing shows different. Tool fails silently (produces plausible-sounding wrong answers).
3. Integration & Ease of Use
The question: How hard is it for our team to actually use this?
The best AI tool in the world doesn't help if your team has to log into a separate portal, paste content, wait for results, and copy-paste the output back into their workflow. That's friction.
Good tools integrate into how people already work. Word integration. Slack integration. API so you can build your own workflow.
Red flags: Requires new app. Requires learning new workflows. Doesn't integrate with tools you already use.
4. Cost & ROI
The question: Do the time savings or value delivered justify the cost?
ChatGPT is $20/month or free. That's obviously cost-effective for experimentation. Enterprise tools can cost thousands per month. Be honest about whether the ROI justifies it.
Run a pilot. Track hours saved. Calculate whether saved hours exceed the tool cost.
Red flags: Vendor can't quantify the value. You run a pilot and can't measure time saved. Cost is high relative to benefit.
5. Adoption & Team Readiness
The question: Will your team actually use this?
This is often overlooked, but it's critical. A tool that's perfect technically but requires your team to change how they work won't get adopted.
Can you explain it in one sentence? Can your team understand what job it's doing for them? Are they willing to learn it? Do they see the value?
Red flags: Team is skeptical. Tool requires significant retraining. Nobody can articulate the value clearly.
How to Use This Framework
Create a simple spreadsheet. List the tools you're evaluating (ChatGPT, Bard, Claude, whatever your team is curious about). Rate each one on the five criteria.
Then look at the pattern:
- High on security, accuracy, integration, cost, and adoption? Approved tool. Support it.
- High on security and accuracy but low on integration and adoption? Experimental tool. Let people use it but don't mandate it.
- Low on security? Don't use it with client data, period.
- Low on accuracy? Only use it on tasks where errors are easy to catch and fix.
A Real Example
ChatGPT today (January 2023):
- Security: Medium (data goes to OpenAI, no DPA available yet, improving)
- Accuracy: High for drafting, Medium for analysis, Low for regulated domain knowledge
- Integration: Low (separate web interface, copy-paste workflow)
- Cost: High ROI for experimentation (free or $20/month)
- Adoption: Very high (team already wants to use it)
Conclusion: Great for testing and drafting work. Not approved for confidential or regulated work. Good for pilots and ops improvement.
The Point
You don't need AI expertise to evaluate these tools. You need a consistent framework and honest assessment of your firm's needs.
Use this one. It works.