Artificial intelligence powers the modern customer journey for many brands, spanning every industry from fintech to entertainment. AI tools drive powerful personalized experiences for individuals, inspiring customer loyalty and retention. When leveraged well, supportive AI tools can raise customer satisfaction by up to 20%.
We’ve gathered some fantastic examples of brands using AI to make their customers’ experiences better. Before we jump in, let’s first discuss the types of AI these technologies are using: traditional and generative AI.
Traditional vs. Generative AI
When we think about AI, it’s easy to lump all forms of AI into one category. In reality, though, there are two types of artificial intelligence: traditional AI and generative AI. You can use both forms of AI to personalize the customer experience.
Traditional AI
Traditional AI powers the algorithms we’ve become accustomed to. It’s trainable machine learning that focuses on data aggregation and task execution. In other words, the use of AI in a traditional sense means the AI is collecting metrics and will then act on that data in a specific way.
Brands train AI algorithms to act on various factors, including buying behavior and customer feedback. They use technologies such as natural language processing (NLP) for customer feedback and sentiment analysis, market research, user authentication, customer support and more.
Here are some places where you’ll see traditional AI in action:
- Personalized recommendations on streaming platforms
- Website and social media chatbots
- Product recommendations on your favorite shopping app
- Spelling and grammar tools such as Grammarly
- Social media algorithms that deliver personalized content recommendations
- Automation for marketing campaigns
Generative AI
Unlike traditional AI, generative AI creates something new for the user. Generative AI advancements have overtaken the tech world over the past few years.
Tools such as ChatGPT, Claude, Gemini and many others help users create on a large scale. You can use generative AI to make everything from artwork and videos to written content and marketing strategies.
CASE STUDY
Ubisoft Drives Player Reactivation With Personalized Video
How Brands Personalize the Customer Experience With AI
Brands of all sizes and across industries leverage AI hyper-personalization for their audiences.
We’ve gathered some excellent use cases demonstrating how the world’s top brands use AI to improve the customer experience. Let’s jump in.
AI Personalization in Personal Finance
Personal finance companies, particularly fintech platforms, have adopted AI technology to make money management and financial transactions faster, easier and more affordable. AI slashes the time it takes a customer to get an online bank account, apply for a loan or make an online purchase.
PayPal Ads, the company’s advertising platform, uses PayPal’s extensive customer data to give shoppers personalized recommendations based on their behavior. Merchants can then
Upstart, an AI-powered lending platform, uses over 1,000 data points in combination with machine learning to match customers with personalized loan recommendations.
The technology moves users through the application process quickly. This saves time, money and frustration in a historically stressful and time-consuming process.
Financial brands are using AI to help explain complex information too, guiding customers through moments that once got lost in the fine print. Here’s a video we created with our AI video agent, Lucas, for PenFed Credit Union, clearly walking members through their individual homeowner services.
AI for Personalized Customer Support
Building a strong customer relationship starts with the first point of contact. These days, many brands use AI-powered chatbots to spark customer engagement or provide customer support. Some use personalized emails to take communication a step further.
Brands use chatbots in a variety of ways on social media, websites and mobile apps. Bank of America’s chatbot, Erica, helps banking customers navigate their finances. Erica is an AI-powered financial assistant. Customers can use the app to manage their money, reducing the time they might typically spend waiting on hold or speaking to a representative.
Dom by Domino’s is another great example. This AI-powered chatbot helps you order the perfect pizza. Users can place a new custom order, reorder an old favorite and even track their order once they’ve placed it.
Chatting with Dom gives the process more of a conversational feel than simply filling out an online order form.
AI for Personalized Onboarding
Customer onboarding is another touchpoint AI can personalize. All it takes is a text prompt — or an existing onboarding doc or webpage if you have it — to create an engaging video that welcomes new customers and helps them get the most out of your service.
At Idomoo, our AI video agent, Lucas, creates on-brand videos like this in minutes. See the example below, which we created with our AI agent in just 4 days, including personalization for every customer.
Thanks to AI, the project launched 3 months ahead of schedule.
You can read all about it in our case study.
CASE STUDY
Longboat Launches Personalized Onboarding Video 3 Months Early With AI
Personalized Video makes concepts easier to understand, especially when the subject matter is complex or people are busy — as your customers most certainly are. But video cuts through the noise, adding a human touch to the first step of your customer’s journey.
And data shows it’s what people want. According to a 2026 study, 80% of consumers want more video content from brands. Scaling video creation has historically been expensive, reserved for big businesses or big campaigns, but AI makes it easy. You don’t need any tech skills, and the right AI video agent can learn your brand so you can get up and running quickly.
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Lucas also learns your Brand DNA — design, narrative, and assets — so every video is automatically on brand. And he can even learn from human designers, going way beyond just matching fonts and colors.
Hyper-Personalized TV and Music Streaming
Streaming apps are recommendation engines that use AI tools to cater to customer preferences. We’ve all opened a streaming app to find fresh new recommendations waiting for us. This style of content personalization creates a uniquely tailored customer journey for individual users.
Netflix’s personalization strategy relies on AI tools like machine learning algorithms to track customer behavior. The result is fine-tuned optimization based on your individual viewing history. Viewers get recommendations based on comparable titles, genre, sub-genre and more.
Regarding personalization efforts, Spotify is well-known for its custom playlists. Spotify relies on AI algorithms to build playlists and artist recommendations based on your listening activity. It’s a fantastic way for customers to get more of the music they love from their favorite artists — and discover new favorites along the way.
Spotify has also widely rolled out an AI playlist tool for Premium users. This tool lets customers build a playlist based on an idea or spark of inspiration.
Brands beyond entertainment are borrowing the streaming playbook, too. This data-rich year-in-review Idomoo created for Orum gives each user their own personalized recap. It’s the same idea as Spotify Wrapped, built for a tech company.
Personalizing Retail
It’s no surprise to anyone that AI algorithms are deeply embedded in modern retail and ecommerce.
Over 60% of retail companies use AI to enhance the customer experience. Retailers today leverage a combination of traditional and generative AI tools across multiple touchpoints in their businesses.
For instance, machine learning systems study customer behavior and purchase history. Then, they recommend products based on specific data points, such as items you’ve bought.
Stitch Fix is one great example of an AI-driven recommendation system. Shoppers can input their preferred styles for the Stitch Fix algorithm to learn. Then, just like a personal stylist, the AI makes product recommendations tailored to your preferences and shopping habits.
Generative AI technology has made its way onto the ecommerce scene, too. Amazon recently rolled out Alexa for Shopping, a conversational AI tool for personalized product recommendations.
Shoppers can interact with Alexa like they might a personal shopping assistant, such as asking Alexa to compare products for you.
Product recommendations are a game changer for online shoppers, but Walmart is taking personalization a step further. AI powers its new virtual try-on tool and uses pictures of each customer to create a virtual shopping experience.
Rather than browsing through images of models on Walmart’s website, customers become their own model. What better way to offer hyper-personalized recommendations than by giving users a virtual dressing room?
Personalization can be part of advertising too. While it won’t be 1:1 — after all, you don’t know your future customer’s name yet — you can personalize ads based on shoppers’ location, interests, online actions and more. With this data, you can generate thousands of ad variants, showing the most relevant version to each micro-segment.
We call it Dynamic Video Ads. AI makes this process faster than ever. Got a gallery of online images for your products? You can animate those with AI and turn them into an ad, just like we did for Elan with the video ad below.
Next AI Personalization Example: Your Brand
AI-powered personalization is a powerful way to build stronger customer relationships, boost satisfaction, and drive sales and retention. Depending on your customers’ specific needs, many different avenues exist to explore. You have a world of possibilities to explore from recommendation engines to custom AI video.
Want to know more about how AI-generated video can enhance your user experience? At Idomoo, our Enterprise AI Video solution helps brands create hyper-personalized, on-brand video content at scale. It’s a great way to incorporate studio-quality video into your content marketing and get more eyes on your brand.
