What is conversational UI and how do AI-driven interfaces actually help users?

Reviewed by: Lazarev.agency AI UX & Product Design Team

Last updated: November 2025

Relevant case studies: Accern Rhea (AI research copilot), SaaS analytics assistants, fintech conversational flows

Conversational UI is a user interface that lets people interact with your product through natural language — text, voice, and increasingly multimodal inputs like images and files. Modern AI-driven conversational interfaces don’t just “chat”; they understand intent, navigate your system, and complete real workflows, which means they can lift activation, conversion, and resolution speed across your product.

Key takeaways

• Conversational UI ≠ chatbot toy. It’s a UX layer that turns natural language into actions and outcomes.
• There’s a ladder of capability: rule-based bots → AI-driven assistants → agentic interfaces that can actually do work.
• The market is exploding: both conversational UI and conversational AI are compounding, not trendy side projects.
• Winning products use patterns: anticipatory prompts, context carryover, smart fallbacks, rich visuals, consent-aware flows, and more.
• Real-world examples (Stripe, Duolingo, Shopify, Google Assistant, Notion, Sephora, Expedia, Accern Rhea) show how this looks in practice.
• Strategy matters more than tooling: start with clear jobs-to-be-done, design guardrails, connect to real actions, and measure impact on metrics.
• Lazarev.agency designs hybrid conversational systems where chat, actions, and interface elements merge into one high-performance experience.

Why conversational UI suddenly feels “human”

Picture this. It’s 11 p.m., you’re finally settling into the couch, doom-scrolling with the enthusiasm of a tired raccoon, when your banking app pings you. Not with the usual “suspicious transaction” pop-up but with something weirdly… thoughtful:

“Hey! Looks like your rent is due soon. Want me to move the money from your savings now or remind you tomorrow morning?”

You freeze. Not because this is creepy (well, a little), but because the experience feels oddly human. It’s as if the app is leaning over your shoulder and gives you the nudge you needed.

That’s conversational UI in action. If you’re building a modern digital product and still relying on robotic scripts, you’re leaving user satisfaction and actual revenue on the table.

In this guide, our design team breaks down what you need to know to build an intelligent conversational interface:

• why conversation has become the new UX layer
• which type of conversational system fits your product
• which patterns separate high-performing assistants from the outdated ones

What is conversational UI?

Conversational UI is an interface that lets users interact with your product through natural language. It could be through text, voice, or, as it’s increasingly the case, a mix of language, visuals, and gestures.

But a conversational interface is only as smart as the intelligence behind it. And that intelligence has a name. It’s conversational AI.

And if you’re wondering how big this shift really is, the data has the answer.

The conversational UI market jumped from $5.85 billion in 2023 to a projected $13.34 billion by 2030.

The conversational AI market expands even faster: $11.58 billion in 2024 and is expected to surpass $41.39 billion by 2030.

When the artificial intelligence layer grows nearly 4× in six years, you’re not looking at a trend. You’re staring at a tectonic shift in how digital products behave in the midst of the AI revolution.

Here’s why businesses care:

1. Users want conversations. They’d rather ask “Can you fix my payment issue?” than dig through a six-step support flow. In a perfect scenario, a good conversational UI design rewires intent into action in seconds.
2. AI finally understands nuance. Modern large language models (LLMs) parse tone, intent, context, and urgency. Your interface can now respond like someone who actually listened.
3. Conversation is the UX layer that accelerates everything else. It doesn’t replace your products’ user interfaces. Instead, it augments them by guiding the target audience, completing tasks for them, and handling the boring parts humans never enjoy.

Three types of conversational UI and how far they can really go

“Many teams lump all chatbots into one big bucket as if the pizza-ordering widget on a fast-food website belongs in the same species as an AI agent that can summarize analytics and generate a personalized financial plan. Well, it doesn’t. Not even close,”  shares Anna Demianenko, our Design Lead at Lazarev.agency.

“To design a conversational experience that works, you can’t treat them the same. Each type comes with different capabilities and constraints and follows specific UI best practices that shape how the interface should guide the user.”

Think of the three categories below as rungs on the intelligence ladder. The higher you climb, the more your interface shifts from merely replying to actually helping.

1. Rule-based chatbots

Rule-based bots are the OG of conversational interfaces. These are the “If-this-then-that” dinosaurs that still roam many enterprise help centers.

They rely largely on structured scripts and predefined paths, which, in turn, limit their contextual awareness and flexibility.

Yet, rule-based doesn’t automatically mean bad. It’s just often misused.

How they work: Rule-based chatbots follow a simple algorithmic pattern: “If the user says X, then respond with Y”.

Why teams use them:

• They’re cheap.
• They’re predictable.
• They’re easy to deploy.

🟥 Where they fall apart:

• Any phrasing that deviates from the script.
• Multistep logic.
• Real human intent.

🟩 Best use cases: Rule-based bots are fine for simple, fully deterministic tasks. But they are rigid calculators in a world that now expects agile copilots.

2. AI-driven conversational UI

This is where the conversational UI embeds innovative UI design principles to understand what users want.

How they work: Powered by natural language processing (NLP) and machine learning (ML), these assistants can interpret phrasing, extract intent, and respond based on context.

What makes them better:

• They adapt to user language.
• They can handle multi-turn conversations.
• They feel significantly more “natural”.

🟥 Where they still struggle:

• Ambiguous requests.
• Complex workflows that require action.
• Situations that call for more elaborate reasoning and judgment.

🟩 Best use cases: AI-driven UIs deliver solid conversational experiences. Still, they respond more than they autonomously perform.

3. Agentic interfaces

Welcome to the top of the ladder.

Agentic conversational interfaces understand and act on what users say. They can navigate your system, pull customer data, make updates, execute time-consuming tasks, and correct themselves if the first attempt didn’t succeed.

How they work: Large language models (like GPT-5.1) connect to tools, APIs, knowledge bases, and actions. The assistant can analyze context, reason through steps, choose the right action, and return results.

What makes them game-changing:

• They break complex workflows into solvable steps.
• They can learn from past interactions.
• They take initiative when appropriate (read more about anticipatory design).
• They reduce drag across the entire product experience.

🏅 Where they shine:

• SaaS (“Create a report based on last quarter’s churn drivers”).
• Fintech (“Dispute this charge and update my budget categories”).
• E-commerce (“Show me black boots under $200 that match my previous order”).

🟩 Bottom line: Agentic interfaces are product experiences powered by conversation, capable of doing real work.

So, which one should you build?

If your goal is to automate responses, any of these might do. But if your goal is to automate outcomes such as faster resolutions, user engagement, and higher conversions, AI-powered design is the only category worth considering.

12 conversational UI patterns every digital product should use

Patterns are the backbone of repeatable excellence. They prevent your conversational UI from degenerating into a fragile collection of “one-off responses” and instead make it a system that adapts and stays consistent as features grow.

Below is a pattern library we use at Lazarev.agency, top AI design agency. It also features examples and insider UX/UI design tips you’d typically only hear during internal reviews or design sprints.

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8 examples of conversational UI design done right: expert breakdown from Lazarev.agency

Most chatbots today feel like talking to a microwave with a speech module. They misunderstand unexpected phrasing and collapse the moment you step outside the script.

But every now and then, a conversational interface comes along that makes you think,
“Oh. So this is how it should work”.

Below are eight examples that get conversational UI right. And as always, we’ll break down why they work and what principles make them quietly brilliant.

1. Stripe’s billing and support assistant

Stripe’s assistant interprets technical queries, surfaces logs, shows the relevant documentation, and even recommends actions. It’s trying to be useful. And that’s exactly why it works.

UI and UX principles at play:

1. Contextual intelligence: it pulls logs before you even ask.
2. Documentation shortcuts: links appear exactly when needed.
3. Task-first design: every message leads to an action.
4. Predictive problem-solving: resolves issues before they become issues.

💡 Expert insight from Lazarev.agency: Conversational UI succeeds in technical products only when it mirrors expert mental models. Stripe’s assistant works because it thinks like the user before it speaks to the user.

2. Duolingo’s conversational practice bot

Duolingo’s chat experience is the closest you’ll get to speaking a new language (or multiple languages) without panicking in front of a real human. In many ways, it’s a perfect example of chat digital transformation done right. The bot adapts to your level, celebrates your wins, and gently corrects your mistakes without a hint of shame.

UI and UX principles at play:

1. Adaptive difficulty curves: the bot reacts to every mistake.
2. Micro-humor: keeps the tone light even when you butcher the grammar.
3. Tight feedback loops: immediate corrections.
4. Role-play scaffolding: scenarios mimicking real-world conversations.
5. Cognitive reinforcement: subtle nudges that shape habits.

💡 Expert insight from Lazarev.agency: In behavior-driven interfaces, emotional safety is part of the UX information architecture. Duolingo proves that conversational UI must manage cognitive load and reinforce progress through strategic tone and timing.

3. Shopify’s AI store assistant

Shopify understood the assignment: merchants don’t have time to click through 40 menus. The assistant writes product descriptions, helps customers, adjusts listings, and handles returns. It’s a Swiss army knife disguised as a chat bubble.

UI and UX principles at play:

1. Rich cards built for commerce: images, variants, CTAs.
2. Action-packed shortcuts: refund, duplicate, publish, restock.
3. Cross-session context: remembers catalog structure.
4. Conversion-first flow: every suggestion pushes revenue forward.

💡 Expert insight from Lazarev.agency: The real power of conversational UI is in compressing multi-step workflows into a single intent. Shopify’s assistant does this flawlessly. For any commerce or SaaS product, the takeaway is simple. Map what your users are actually trying to accomplish. Then let the assistant collapse the journey.

4. Google Assistant

Google Assistant is the rare interface where everything feels easy because the multimodal experience tackles complexity through voice, text, visuals, and contextual cues.

It hears you, interprets you, and then shows you exactly what you’ve been looking for. And that last part is where the magic is.

UI and UX principles at play:

1. Turn-taking logic: it never interrupts you like your overly chatty coworker.
2. Visual grounding: maps, lists, and cards instead of endless speech.
3. Mode switching: speak, type, gesture; the assistant adapts.
4. Memory-driven fluency: it remembers routines better than you do.

💡 Expert insight from Lazarev.agency: Multimodality means distributing cognitive load across senses. Google Assistant excels because it pairs the affordances of conversation with clear visual grounding. When designing conversational UI, treat visuals as a parallel information channel. That’s where true usability lives.

5. Notion’s AI assistant

Notion’s assistant feels like a second brain with AI-powered design. Ask it to summarize, restructure, tag, reformat, rewrite, or generate content, and it acts like the world’s most disciplined intern with a caffeine addiction.

UI and UX principles at play:

1. Agentic behaviors: performs actions.
2. Context sensitivity: understands everything around your cursor.
3. Structured output: clean, readable, scannable.
4. Smooth in-surface interaction with no context switching.

💡 Expert insight from Lazarev.agency: Conversational UI is indispensable when embedded into the workflow. If users need to go somewhere to use your assistant, you’ve already lost the adoption battle. The interface must feel co-located with the task.

6. Sephora’s virtual assistant

Sephora’s assistant actually consults. It blends augmented reality (AR) try-on features, product filtering, customer preferences, and friendly guidance into a single thread that feels shockingly close to an in-store expert.

UI and UX principles at play:

1. Visual-first responses: try-ons, swatches, comparisons.
2. Confidence scoring: “This shade may be too warm for your tone”.
3. Guided discovery: choices narrow as you go.
4. User modeling: remembers allergies, skin types, and tones.

💡 Expert insight from Lazarev.agency: Sephora succeeds because it mirrors the heuristics of a domain specialist by visually validating choices and personalizing the journey. For any brand, the lesson is that your assistant should behave like your best salesperson.

7. Expedia’s Trip Planning Assistant

Travel planning is usually a spreadsheet with emotional damage. Expedia flips that into a conversation that knows your dates, budget, loyalty points, hotel preferences, and tolerance for layovers that feel like camping trips.

UI and UX principles at play:

1. Multi-turn itinerary workflows: flights → hotels → activities.
2. Proactive constraint warnings: “Prices spike after this date”.
3. High-density information cards: times, prices, maps, filters.
4. Preference-driven shortcuts: nonstop flights, flexible dates.

💡 Expert insight from Lazarev.agency: Expedia transforms an inherently chaotic process into a coherent flow. This is the hallmark of advanced conversational design: the interface capable of structuring the entire decision-making process for the user.

8. Accern.Rhea by Lazarev.agency

Most conversational UIs handle small talk. Accern.Rhea handles financial research, cross-dataset analysis, complex workflows, and multi-modal inputs. All of this within one interface.

It’s a research companion with enough intelligence and flexibility to replace an entire toolkit of dashboards, filters, and clunky search systems financial analysts used to wrestle with.

Designed by Lazarev.agency in 2022–2024, Rhea pioneered several UI/UX patterns now adopted by industry leaders like Anthropic and OpenAI.

UI and UX principles at play:

1. Multi-purpose conversational input: Accepts prompts, files, URLs, and commands in one field.
2. Adaptive natural language system: Clarifies intent, handles ambiguities, and supports multi-turn reasoning.
3. Hybrid GUI and prompt interface: Conversational flows supported by filters, cards, tables, and visual cues.
4. Agentic task execution: Generates reports, synthesizes data, summarizes PDFs, compares companies.
5. Integrated datasets and file intelligence: Connects financial datasets, reads documents, and cross-references information.
6. Memory and context awareness: Remembers the conversation thread, maintains continuity, and adapts output.

💡 Expert insight from Lazarev.agency: Rhea shows that conversation can be the backbone for analytical reasoning, data navigation, and knowledge synthesis. It proves that conversational UI is an interaction layer for complex systems. When conversation becomes the gateway to advanced workflows, the entire product strategy shifts from pages to processes.

Why your conversational UI strategy matters more than ever

The companies winning right now are building interfaces that understand user intent and quietly (yet strategically) automate the annoying parts of user workflows.

Meanwhile, teams clinging to static UI patterns are discovering (often painfully) that users no longer have the patience to navigate outdated screens and dropdowns.

This is where the opportunity lives.

At Lazarev.agency, we design AI-driven conversational systems that become the backbone of your product. Be it through pioneering hybrid conversational interfaces like Rhea or helping SaaS products raise millions in funding, we know first-hand how to engineer digital products ready for growth.

So if you’re ready to make conversational UI a strategic asset, let’s talk.