As artificial intelligence (AI) becomes increasingly embedded in legal operations from contract analysis to eDiscovery to client engagement, terms like “AI” and “generative AI” are appearing everywhere. But not all AI is created equal, and mislabeling technologies as “generative AI” is creating confusion among legal professionals, clients, and vendors alike.

This blog post aims to clear up the misconceptions, explain what generative AI truly is, how it differs from other AI types used in legal tech, and why accurate terminology matters more than ever.

What Is Generative AI?

Generative AI refers to systems designed to create new content—whether that’s text, images, audio, or even code. These models are trained on large datasets and use patterns in that data to generate original material.

Examples in Legal Context:

• GPT-4: Generates human-like text used to draft memos, summarize legal opinions, or rewrite documents.
• DALL·E: Creates images from textual descriptions.

These tools are inherently creative. Unlike traditional AI, which categorizes or analyzes existing content, generative AI produces something new.

Common Misuses of “Generative AI” in Legal Tech

Too often, tools that perform analysis, extraction, prediction, or classification are being incorrectly labeled as generative AI. Let’s break down where the confusion happens and what to call these technologies instead:

1. Applied AI ≠ Generative AI

• What It Does: Automates workflows, flags risk clauses, prioritizes tasks.
• Common Mislabel: Calling a contract review tool “generative AI.”
• Why It’s Wrong: The tool applies trained models, it doesn't generate new documents.
• ✅ Correct Term: Applied AI

2. NLP AI ≠ Generative AI

• What It Does: Extracts or interprets human language; powers tools that summarize, translate, or redact.
• Common Mislabel: Labeling a language translation tool as generative AI.
• Why It’s Wrong: It processes and transforms existing content, not creates new content.
• ✅ Correct Term: NLP (Natural Language Processing) AI

3. Predictive AI ≠ Generative AI

• What It Does: Uses historical data to forecast future outcomes, like the likelihood of a case settling.
• Common Mislabel: Referring to a predictive coding engine in eDiscovery as generative AI.
• Why It’s Wrong: It predicts relevance, it doesn't draft anything new.
• ✅ Correct Term: Predictive AI

4. Conversational AI ≠ Generative AI (Always)

• What It Does: Engages with users in a dialogue, often using scripted or decision-tree logic.
• Common Mislabel: Calling a rules-based FAQ chatbot generative AI.
• Why It’s Wrong: It’s not creating content; it’s retrieving and displaying predefined answers.
• ✅ Correct Term: Conversational AI
  (Note: Some advanced chatbots do use generative AI, but many don’t.)

Why Does This Confusion Happen?

Reason	Impact
Buzzword Appeal	Generative AI is hot, so vendors and marketers use the term liberally.
Technical Gaps	Non-technical users may not understand the distinctions between AI types.
Overlapping Functions	Some tools combine multiple AI capabilities, muddying the labels.

✅ Why Accurate Terminology Matters in Legal Tech

Clarity in language leads to clarity in outcomes. Mislabeling AI tools can cause a ripple effect of poor decisions, false expectations, and misallocated resources.

Reason	Why It’s Critical
Expectation Management	Ensures users understand what a tool can (and can’t) do.
Investment Alignment	Helps firms direct budget toward truly innovative technologies.
Regulatory Compliance	Supports accurate reporting, auditing, and data governance.
Vendor Transparency	Builds trust in legal tech procurement and implementation.

The Key Question: Is It Creating or Analyzing?

Whenever you encounter a legal tech tool labeled as “AI,” pause and ask:

Is this system creating something new, or is it analyzing and acting on what already exists?

The answer will guide you toward the correct classification:

• Creating something new? It’s likely generative AI.
• Interpreting, sorting, predicting, or organizing? It’s applied, predictive, NLP, or conversational AI.

Conclusion

Generative AI is transforming the legal industry but it’s just one piece of a much broader AI puzzle. In the high-stakes world of eDiscovery and legal operations, precision in language is just as important as precision in logic.

Using the right AI labels fosters better decisions, smarter investments, and more trust between vendors, attorneys, clients, and regulators.

Let’s keep the conversation clear and the tech transparent.

If you're exploring legal AI tools and want to understand what's really behind the buzzwords, we’re here to help.