Webinar Recap: AI in Legal Practice, Security Risks, Usage Rules, and the 6-Step Safe Path to AI Adoption

Artificial Intelligence has reached a point where it influences almost every digital interaction inside a law firm whether attorneys formally adopt it or not. From research tools to document editing, from email platforms to file management systems, AI now operates quietly in the background of everyday workflows. While this can create meaningful efficiencies, it also introduces new responsibilities related to confidentiality, risk management, ethics, and compliance.

The webinar “AI in Legal Practice, Security Risks, Usage Rules, and AI Readiness Checklist” was designed to give law firms a structured system for using AI safely. Instead of chasing buzzwords or feeling pressured to “keep up,” the session focused on building a secure foundation first. The framework at the center of the conversation was the Six-Step Safe Path, a practical roadmap that any law firm can follow to adopt AI responsibly.

What follows is a deeper, detailed, and fully enhanced recap of that discussion so your firm can use AI with confidence, clarity, and control.

 

Speakers

Matthew Kaing
Matthew Kaing

Data Security and IT Expert

IT and Cybersecurity Expert with 24+ years supporting small law firms. Founder of eSudo, a Silicon Valley IT consulting firm focused on secure, reliable technology systems that help law firms work more efficiently.

Sharon Means, CPA

Fractional Integrator

With a background as a CPA and 5+ years as a Fractional Integrator, Sharon focus exclusively on helping law firms (running on EOS, The Entrepreneurial Operating System) perform more effectively.

Why AI Adoption Needs a Thoughtful Strategy

Many firms feel caught between two extremes. On one hand, they see competitors using AI and worry about being left behind. On the other, they worry about confidentiality breaches, ethical implications, and potential exposure if staff upload the wrong information into the wrong tools.
The problem is not AI itself. The real issue is the absence of structure. When firms jump into AI without a plan, they often:

The webinar “AI in Legal Practice, Security Risks, Usage Rules, and AI Readiness Checklist” was designed to give law firms a structured system for using AI safely. Instead of chasing buzzwords or feeling pressured to “keep up,” the session focused on building a secure foundation first. The framework at the center of the conversation was the Six-Step Safe Path, a practical roadmap that any law firm can follow to adopt AI responsibly.

What follows is a deeper, detailed, and fully enhanced recap of that discussion so your firm can use AI with confidence, clarity, and control.

  • Purchase tools they do not need

  • Use AI inconsistently across departments

  • Upload sensitive data without safeguards

  • Allow staff to experiment in risky ways

  • Overlook the security settings inside the tools they already use

In short, the risk does not come from AI, but from poor implementation, unclear rules, and missing oversight.

The Safe Path addresses these risks directly by helping firms build a strong foundation before turning to tools.

The Six-Step Safe Path to Secure AI Adoption

1. Start With Workflow Clarity Instead of Browsing for Tools

The first step asks a simple but often overlooked question:
What do you actually want help with?

AI is not a strategy. It is a tool that should be aligned with your real workflows. That means understanding:

  • Where time is being wasted

  • Which tasks are repetitive or tedious

  • Which tasks require original legal analysis

  • Which steps rely heavily on drafting

  • Where long documents or case files need summarization

  • Where human oversight is essential, regardless of how advanced AI becomes

Mapping your workflow first ensures you are not buying features you will never use. It also ensures the firm chooses tools that genuinely solve problems rather than ones that add new complexity.

This step reduces cost, increases adoption, and sets the foundation for a more secure rollout.

2. Classify Your Data Before Entering Anything Into AI

This is the step that prevents most compliance breaches before they happen. Data classification puts guardrails around what staff can and cannot share.

A simple structure includes:

 

Public Data

 

Information that is already shared publicly, including website text, blog articles, FAQs, and social media content. This can usually be safely used with AI tools because it carries no risk.

 

Internal Data

 

The operational backbone of the firm, including SOPs, onboarding scripts, internal processes, training materials, and internal communications templates. Sharing this information requires secure, enterprise-grade tools because it reveals how the firm operates.

 

Confidential Data

 

The most sensitive category, including client intake forms, case files, evidence, medical information, financial data, PII, employee HR information, and anything covered by ethical or regulatory duties.
This data should never be entered into AI tools that do not explicitly guarantee isolation, non-training, strict privacy, and administrative oversight.

To strengthen this step, firms that use Microsoft 365 can apply Sensitivity Labels, which automatically enforce rules such as blocking external sharing, preventing document forwarding, or requiring encryption.

This step empowers staff to make safe decisions without guessing.

3. Select AI Tools With True Enterprise-Level Protections

After clarifying workflows and data types, firms can begin evaluating tools. The key is not which tool is trendy, but which tool aligns with your security, workflow, and ethical obligations.

Enterprise-grade AI tools should have:

  • A clear non-training policy

  • The ability to prevent model learning from your prompts

  • Documented data retention rules

  • Administrative dashboards for visibility

  • Permission controls for managing access

  • Private or isolated environments

  • Compatibility with existing cybersecurity layers

  • Tools to monitor or restrict data sharing

One of the biggest dangers is assuming the tool is secure simply because it is popular. The real risk comes from misconfigurations. Even enterprise tools can expose data if the wrong settings are left unchecked or if access is too broad.

Choosing tools with strong defaults and transparent security documentation simplifies adoption and reduces exposure.

4. Create a Firm-Wide AI Usage Policy to Set Clear Expectations

A structured AI Acceptable Use Policy is essential. Without it, each attorney and staff member will interpret “safe AI use” differently.

The policy should clearly define:

  • Which AI tools are approved

  • Which tools are prohibited

  • What information may be entered into AI, based on data classification

  • What information is forbidden

  • What review steps must take place before sending AI-generated work to clients

  • How AI tools may connect to email, files, calendars, or shared drives

  • What security practices must be followed, including MFA and secure login methods

  • What staff should do if they are unsure about a tool or an action

  • How to report a potential misuse

Many firms are beginning to update their engagement agreements to disclose their use of AI tools when appropriate, especially when AI is embedded within their practice management or legal research platforms. This transparency helps maintain trust.

This policy provides clarity, protects confidentiality, and gives every person on the team a consistent set of expectations.

5. Use AI as a High-Speed Assistant, Not a Decision-Maker

This step reinforces the philosophy behind safe adoption: AI accelerates work, but it cannot replace legal reasoning.

AI is extremely effective at:

  • Drafting first-pass versions of documents

  • Summarizing long materials

  • Distilling statutes or regulations

  • Extracting key talking points

  • Suggesting alternative structures or phrasing

  • Organizing large amounts of information

AI is not reliable for:

  • Interpreting context

  • Applying legal nuance

  • Making ethical decisions

  • Understanding client history or strategy

  • Ensuring compliance with jurisdiction-specific rules

  • Validating its own accuracy

Human oversight is always required. Treating AI as a “super intern” keeps the relationship clear: it supports attorneys, but never substitutes judgment.

6. Monitor Usage, Train Continually, and Update Policies as AI Evolves

AI adoption is ongoing, not one-and-done. Once tools and policies are in place, the firm must maintain oversight.

This includes:

  • Training staff regularly on safe and unsafe practices

  • Ensuring team members understand how to classify data

  • Reviewing tool configuration to confirm settings remain aligned with policy

  • Using alerts that notify staff before they send sensitive information externally

  • Verifying MFA and secure authentication methods

  • Periodic audits of tool access, permissions, and integrations

  • Updating the policy when new features launch or new risks emerge

New AI browsers, for example, offer impressive productivity features such as automatic summarization of open tabs, tab organization, and video summaries. However, because they may read all visible content, many firms restrict their use until stronger privacy practices emerge.

Monitoring ensures that the firm stays ahead of risks instead of reacting to them after exposure occurs.

AI Readiness Checklist and Support

During the webinar, attendees received access to the AI Readiness Checklist, a structured assessment that helps law firms evaluate:

  • Workflow clarity

  • Data classification

  • Security posture

  • Policy readiness

  • Team training

  • Configuration of tools

  • Overall preparedness for AI adoption

You can access it here:

➡️ AI Readiness Checklist

This checklist includes 15 to 20 targeted questions designed to highlight strengths, identify vulnerabilities, and guide next steps. Many firms follow the checklist with a Personalized AI Readiness Call to review results and build an implementation plan.

Detailed Q and A Highlights

Should firms disclose their use of AI in engagement agreements?

Many firms now add disclosures, especially when using AI-supported drafting or research tools. It helps maintain transparency and avoids misinterpretation of how the firm uses technology.

Are enterprise AI tools completely safe?

Enterprise tools greatly reduce risk, but no tool is flawless. The biggest risks usually come from human error, overlooked settings, or overly broad permissions. Proper configuration is non-negotiable.

Can AI truly explain how it handles data?

No. AI models cannot verify their own internal operations. Their answers reflect training data, not actual system processes. Only vendor documentation and independent audits provide real clarity.

Is connecting AI tools to SharePoint or OneDrive safe?

Using Microsoft Copilot within the private Azure ecosystem is generally the most secure pathway. It keeps data within Microsoft’s protected environment rather than routing it to public AI services. Configuration must still be checked thoroughly.

Is zero data retention available?

Some tools offer shorter retention windows, but true zero retention is uncommon. Firms should review each vendor’s policies carefully to understand exactly what is stored.

Are AI-powered browsers safe for legal practice?

They improve productivity but can read everything on open tabs. This makes them risky for environments containing client information. Many firms restrict or fully block them until security standards mature.

Final Thoughts: Moving Forward with Confidence

AI is transforming legal work, and the firms that adopt it thoughtfully will gain significant advantages in productivity, responsiveness, and internal efficiency. The Safe Path provides a clear structure for secure adoption, and the AI Readiness Checklist helps firms assess where they stand before making decisions.

With the right foundation, law firms can enjoy the benefits of AI while keeping client trust, confidentiality, and ethical obligations at the center of their practice.