Remember when login forms were just two input fields and a button? Those days are long gone. As we navigate 2025, users expect their apps to be smarter, more personalised, and more helpful. I’ve been experimenting with AI-enhanced login experiences lately, and I want to share what I’ve learned about building a login form that feels like it’s actually from this decade.
In this guide, I’ll walk you through creating a React Native login form that incorporates several AI features that users are starting to expect:
- Smart email suggestions that make sense
- Voice input for hands-free login (perfect for multitasking)
- Intelligent password strength feedback that goes beyond the typical colour bar
Let’s build something to impress your users and make your app stand out.
What You’ll Need
Before we dive in, make sure you have:
- React Native environment set up (either Expo or React Native CLI)
- Node.js is installed and ready to go
- An OpenAI API key (for the smart suggestion features)
- For voice features: react-native-voice package
Starting with the Basics
First, let’s create a simple login form as our foundation. Nothing fancy yet — just the bare essentials:
// LoginForm.js
import React, { useState } from 'react';
import { View, TextInput, Button, Text, StyleSheet } from 'react-native';
export default function LoginForm() {
const [email, setEmail] = useState('');
const [password, setPassword] = useState('');
return (
<View style={styles.container}>
<Text style={styles.label}>Email</Text>
<TextInput
value={email}
onChangeText={setEmail}
placeholder="Enter your email"
keyboardType="email-address"
autoCapitalize="none"
style={styles.input}
/>
<Text style={styles.label}>Password</Text>
<TextInput
value={password}
onChangeText={setPassword}
placeholder="Enter your password"
secureTextEntry
style={styles.input}
/>
<Button
title="Login"
onPress={() => console.log('Login attempt with:', email)}
/>
</View>
);
}
const styles = StyleSheet.create({
container: {
padding: 20,
},
label: {
marginTop: 12,
fontWeight: '500',
},
input: {
borderBottomWidth: 1,
borderColor: '#ddd',
padding: 10,
marginBottom: 15,
}
});
I’ve seen way too many tutorials stop here, but this is just our starting point. Nothing special yet.
Adding AI-Powered Email Suggestions
The first AI feature we’ll add is smart email suggestions. This feature is particularly useful during sign-up flows or when a user logs in on a new device. Instead of basic autocomplete, we’ll use GPT to generate contextually relevant email suggestions.
const fetchEmailSuggestion = async (nameHint) => {
try {
const response = await fetch("https://api.openai.com/v1/chat/completions", {
method: "POST",
headers: {
"Authorization": `Bearer ${YOUR_OPENAI_API_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
model: "gpt-4",
messages: [
{
role: "system",
content: "You are a helpful assistant that suggests professional email addresses based on names. Respond with just the email, no explanations."
},
{
role: "user",
content: `Suggest a professional email for someone named ${nameHint}`
}
],
max_tokens: 60
})
});
const data = await response.json();
return data.choices[0].message.content;
} catch (error) {
console.error("Error fetching email suggestion:", error);
return null;
}
};
Now, let’s add a button that will trigger this suggestion feature. I like to place it near the email input:
<View style={styles.emailContainer}>
<TextInput
value={email}
onChangeText={setEmail}
placeholder="Enter your email"
keyboardType="email-address"
autoCapitalize="none"
style={styles.input}
/>
<Button
title="Suggest"
onPress={async () => {
// In a real app, you might get the name from previous signup steps
const name = "Alex Rivera"; // Example
const suggestion = await fetchEmailSuggestion(name);
if (suggestion) {
setEmail(suggestion.trim());
}
}}
/>
</View>
What I love about this approach is its flexibility. During testing, I found that prompting GPT to generate contextually relevant emails (like company-specific formats) works surprisingly well when you customise the system message.
Voice Input: Because Typing is So 2023
Next, let’s add voice input functionality. This is particularly useful for accessibility and those moments when users have their hands full. First, install the voice package:
npm install --save @react-native-voice/voice
Then, integrate it into your component:
import React, { useState, useEffect } from 'react';
import Voice from '@react-native-voice/voice';
export default function LoginForm() {
// Existing state...
const [isListening, setIsListening] = useState(false);
const [voiceInputField, setVoiceInputField] = useState(null); // 'email' or 'password'
useEffect(() => {
// Set up voice recognition listeners
Voice.onSpeechStart = () => setIsListening(true);
Voice.onSpeechEnd = () => setIsListening(false);
Voice.onSpeechResults = (e) => {
if (e.value && e.value.length > 0) {
if (voiceInputField === 'email') {
setEmail(e.value[0].toLowerCase().replace(/\s+/g, ''));
}
}
};
// Cleanup
return () => {
Voice.destroy().then(Voice.removeAllListeners);
};
}, [voiceInputField]);
const startListening = (field) => {
setVoiceInputField(field);
Voice.start('en-US');
};
const stopListening = () => {
Voice.stop();
setIsListening(false);
};
// Now add a microphone button next to your input fields
Now, let’s add the UI elements for voice input:
<View style={styles.inputGroup}>
<TextInput
value={email}
onChangeText={setEmail}
placeholder="Enter your email"
keyboardType="email-address"
autoCapitalize="none"
style={[styles.input, styles.flexGrow]}
/>
<TouchableOpacity
onPress={() => startListening('email')}
style={styles.micButton}
>
<Text style={styles.micIcon}>{isListening && voiceInputField === 'email' ? '🔴' : '🎤'}</Text>
</TouchableOpacity>
</View>
When I implemented this in a recent project, users were genuinely surprised by how natural it felt. One important lesson: make sure to provide clear visual feedback during recording (the red dot in this example).
Intelligent Password Strength Feedback
Last but not least, let’s implement a password strength checker that provides helpful feedback. While you could use a simple regex-based approach, combining pattern matching with AI can give more nuanced suggestions:
const checkPasswordStrength = (password) => {
// Basic checks first
if (!password) return { strength: 'empty', message: 'Enter a password' };
if (password.length < 8) return { strength: 'weak', message: 'Too short! Use at least 8 characters' };
// Check for common patterns
if (/^123/.test(password) || /password/i.test(password)) {
return { strength: 'weak', message: 'Avoid common patterns like "123" or "password"' };
}
// Check for variety
const hasUppercase = /[A-Z]/.test(password);
const hasLowercase = /[a-z]/.test(password);
const hasNumbers = /[0-9]/.test(password);
const hasSymbols = /[^A-Za-z0-9]/.test(password);
const varietyScore = [hasUppercase, hasLowercase, hasNumbers, hasSymbols].filter(Boolean).length;
if (varietyScore <= 2) {
return {
strength: 'medium',
message: 'Mix uppercase, lowercase, numbers, and symbols for a stronger password'
};
}
if (password.length >= 12 && varietyScore >= 3) {
return { strength: 'strong', message: 'Great password! 💪' };
}
return { strength: 'medium', message: 'Decent, but could be stronger' };
};
Now, let’s integrate this into our password field:
const [passwordFeedback, setPasswordFeedback] = useState({ strength: 'empty', message: 'Enter a password' });
// Update in the password input
<TextInput
value={password}
onChangeText={(text) => {
setPassword(text);
setPasswordFeedback(checkPasswordStrength(text));
}}
placeholder="Enter your password"
secureTextEntry
style={styles.input}
/>
// Display feedback below the input
<Text style={[
styles.feedbackText,
passwordFeedback.strength === 'weak' ? styles.weakText :
passwordFeedback.strength === 'medium' ? styles.mediumText :
passwordFeedback.strength === 'strong' ? styles.strongText :
styles.neutralText
]}>
{passwordFeedback.message}
</Text>
For a truly AI-powered approach, you could even send anonymised password patterns (never the actual password!) to an API that generates personalised feedback. I’ve experimented with this using a custom endpoint that analyses password structure without seeing the actual password.
Putting It All Together
When you combine these features, you end up with a login form that feels genuinely helpful rather than just a barrier to entry. Here’s a snippet of how the final component might look:
export default function LoginForm() {
// All the state and functions from above...
return (
<View style={styles.container}>
<Text style={styles.title}>Welcome Back</Text>
<Text style={styles.label}>Email</Text>
<View style={styles.inputGroup}>
<TextInput
value={email}
onChangeText={setEmail}
placeholder="Enter your email"
keyboardType="email-address"
autoCapitalize="none"
style={[styles.input, styles.flexGrow]}
/>
<TouchableOpacity onPress={() => startListening('email')} style={styles.micButton}>
<Text style={styles.micIcon}>{isListening && voiceInputField === 'email' ? '🔴' : '🎤'}</Text>
</TouchableOpacity>
</View>
<View style={styles.suggestContainer}>
<Button
title="Suggest Email"
onPress={async () => {
const name = "Alex Rivera"; // Example
const suggestion = await fetchEmailSuggestion(name);
if (suggestion) setEmail(suggestion.trim());
}}
/>
</View>
<Text style={styles.label}>Password</Text>
<TextInput
value={password}
onChangeText={(text) => {
setPassword(text);
setPasswordFeedback(checkPasswordStrength(text));
}}
placeholder="Enter your password"
secureTextEntry
style={styles.input}
/>
<Text style={[
styles.feedbackText,
passwordFeedback.strength === 'weak' ? styles.weakText :
passwordFeedback.strength === 'medium' ? styles.mediumText :
passwordFeedback.strength === 'strong' ? styles.strongText :
styles.neutralText
]}>
{passwordFeedback.message}
</Text>
<TouchableOpacity style={styles.loginButton} onPress={handleLogin}>
<Text style={styles.loginButtonText}>Login</Text>
</TouchableOpacity>
</View>
);
}
Final Thoughts
What I’ve found most interesting about building AI-powered login forms is how quickly user expectations are shifting. Just two years ago, these features would have seemed excessive. Now, they’re starting to feel standard.
A few lessons I’ve learned along the way:
- Always provide traditional input methods alongside AI features
- Be transparent about what’s happening with user data
- Make sure the AI features actually save time rather than creating friction
There’s so much more we could add here — facial recognition for biometric login, anomaly detection to identify suspicious login attempts, or even sentiment analysis to adjust the UI based on user frustration levels.
The future of authentication is not just about verifying identity—it’s about creating a personalised entry point to your application.
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