Frank Ramos recently shared something that caught my attention: "Client communications is crucial for a vibrant, healthy, and professional relationship. Join us as we discuss how AI can help facilitate and improve client communications." I agree with the premise, and I think it is worth expanding because client communication is not a soft skill that sits on the sidelines. It is often the product.

In law, consulting, and other professional services, clients remember responsiveness, clarity, and consistency long after they forget a specific sentence in a memo. Frank is pointing to a competitive advantage that is surprisingly operational: the way we communicate day to day. The good news is that AI can help, not by replacing relationships, but by reinforcing them with better systems.

"Client communications is crucial for a vibrant, healthy, and professional relationship." - Frank Ramos

Why client communication is where trust is built

Frank Ramos’s point lands because communication is the visible surface area of your competence. Even when the work is excellent, clients can feel anxious if they do not understand what is happening, what happens next, and what you need from them.

In my experience, communication breaks down in predictable ways:

Response-time gaps: A client emails at 4:30 pm, hears nothing until the next afternoon, and assumes the worst.
Unclear status: The matter might be progressing, but the client cannot see the milestones.
Inconsistent tone: One message is warm and helpful, the next is curt and overly technical.
Too much legalese or jargon: You know what a motion means, but your client may not.
No proactive updates: The client is forced to ask, and every ask chips away at confidence.

AI can help address each of these without turning communication into robotic templates.

Where AI actually helps (and where it should not)

When Frank says AI can "facilitate and improve" communication, I hear two buckets: speed and quality.

Speed: getting to a good draft faster

AI can reduce the time between receiving a client message and sending a thoughtful response. Not by auto-sending, but by preparing a solid first draft that you review.

Useful examples:

Drafting a reply that acknowledges the client’s concern, summarizes the issue, and outlines next steps.
Turning a quick bullet list from you into a polished client update.
Creating a meeting recap email with action items and deadlines.

Quality: clarity, tone, and structure

A fast response that confuses the client is not a win. AI can act like an editor that improves readability and tone.

Practical uses:

Rewrite a paragraph in plain English.
Produce two versions of the same message: one formal, one conversational.
Check for missing pieces: timeline, responsibilities, decision points, attachments, and requested documents.

Where AI should not lead

AI should not be the decider, the signer, or the confidant.

Do not let AI invent facts, deadlines, or legal conclusions.
Do not paste sensitive details into tools that are not approved for confidential data.
Do not outsource judgment. The relationship is still yours to own.

A simple AI-assisted communication workflow

If you want to put Frank Ramos’s idea into practice, here is a workflow that stays realistic for busy professionals.

1) Build a "client update" template that fits your practice

Create a standard structure for updates so clients always know what to expect:

What changed since the last update
Where we are now
What happens next
What I need from you
Risks, timing, and costs (when relevant)

AI can help generate and refine this template, but you should tailor it to your matter types.

2) Use AI to draft, then you edit for accuracy and empathy

A good prompt might be:

Draft a client email update. Use a calm, professional tone. Explain in plain English. Include next steps and what we need from the client. Do not add facts.

Then you review:

Are all facts correct?
Are any promises implied?
Is the tone aligned with the client’s emotional state?
Does the email answer the question the client is really asking?

3) Add a "tone pass" before sending

This is where AI can shine as a final editor. Ask it to:

Remove jargon
Shorten long sentences
Add a brief acknowledgment of the client’s concern
Ensure the message is respectful and confident

Small changes here can prevent misinterpretation.

4) Log the communication and set the next touchpoint

Communication is a system, not an event. After sending, capture:

What you told the client
What you requested
When you will follow up

AI can help summarize the email into a CRM or matter note. The key is consistency.

Concrete ways AI can improve the client experience

Frank Ramos’s post is short, but the implication is big: AI can help you deliver a better experience at scale.

Proactive updates that reduce inbound stress

A client who is updated weekly is less likely to send daily "Any news?" emails. AI makes it easier to generate those updates without starting from scratch.

Better intake and issue spotting

AI can help turn raw client intake into a structured summary:

Parties, dates, and key events
Client goals
Open questions
Missing documents

That means fewer back-and-forth messages later.

Meeting preparation and follow-up that feels polished

Clients notice when you come prepared and when you follow through. AI can help you:

Draft a meeting agenda based on prior emails
Generate questions to clarify goals and risk tolerance
Produce a clean recap with action items

Guardrails: confidentiality, accuracy, and compliance

To keep AI as an asset rather than a liability, set guardrails that match your ethical and regulatory environment.

Data rules

Use firm-approved tools for any client-related content.
Minimize sensitive details in prompts when possible.
Store drafts appropriately and avoid copying confidential attachments into unapproved systems.

Accuracy rules

No AI-generated facts. Ever.
Verify citations, dates, and procedural statements.
Treat AI output as a draft, not an answer.

Disclosure and expectations

You may not need to announce every use of AI, but you do need to ensure the client receives accurate, human-reviewed communication that meets professional standards. If a client asks, be transparent about the role AI plays in supporting your workflow.

What to measure so this becomes a competitive advantage

If the goal is a "vibrant, healthy, and professional relationship," measure signals of trust and clarity.

Consider tracking:

Response time to client messages
Frequency of proactive updates
Number of follow-up clarification questions (fewer can mean clearer communication)
Client satisfaction signals: referrals, repeat engagements, positive feedback
Internal efficiency: time spent drafting routine emails

AI’s value shows up when clients feel informed and when your team avoids communication debt.

Getting started this week (without overhauling everything)

If you are motivated by Frank Ramos’s point, start small:

Pick one recurring message type (status update, document request, meeting recap).
Create a standard outline and a tone guideline.
Use AI to draft one message per day, then edit and send.
Save what works as reusable snippets.
Review outcomes after two weeks.

The win is not using AI everywhere. The win is making client communication reliably clear, timely, and human.

Final thought

Frank Ramos is right to center communication. Relationships in professional services are built in the moments between milestones: the quick update, the steady reassurance, the clear explanation of what happens next. AI can support that rhythm, but only if we use it deliberately, with confidentiality and judgment as non-negotiables.

This blog post expands on a viral LinkedIn post by Frank Ramos, Best Lawyers - Lawyer of the Year - Personal Injury Litigation - Defendants - Miami - 2025 and Product Liability Defense - Miami - 2020, 2023 🔹 Trial Lawyer 🔹 Commercial 🔹 Products 🔹 Catastrophic Personal Injury🔹AI. View the original LinkedIn post →