Many digital products today still do what they were originally built to do: solve specific problems, automate tasks, or provide services. But that’s table stakes now. A simple, functional model is not enough today.
Businesses outpacing the competition are embedding AI into their digital products for many good reasons- to predict user behavior, automate smart decisions, and surface patterns the human eye might miss. These AI-enabled digital products are intelligent partners in their growth. But it matters more to your customers than you. Why? Users are more informed, so their product expectations are higher, and competitors adopting changes fast is grabbing their attention. If you fail here, you lose the market. So, the conversation isn’t just about upgrading features. It’s about evolving your product into an intelligent system that proactively improves user outcomes. This is the entry point to understanding how digital products using AI can shift your entire customer experience.From Data Graveyards to Strategic Goldmines
Now that we understand why digital products need a rethink, let’s discuss what makes them truly valuable: data. Every click, message, form fill, and interaction creates a digital breadcrumb. But what happens to all of that information? In most cases, it’s just stored. It sits in the system, untouched, unused as a digital graveyard.
By using AI tools for digital products, you can change these scattered bits of activity and start connecting the dots, helping your product learn from patterns such as what kinds of users typically convert, which behaviors indicate churn, and when a user is ready to upgrade or disengage. Suddenly, your product transformed from a passive interface to a system that can learn and guide. This is the foundation we need before diving into the “how.” Because once your digital product starts recognizing the value in your data, everything that follows, from automation to insights, gets more powerful.How Well-Known Brands are Using AI in Their Digital Products
1. Canva Uses AI to Enhance User Experience
The most recent and impressive AI feature Canva introduced is Canva code. Users can create interactive experiences for the customers without writing codes. This new feature helps users design faster and more creatively, regardless of their skill level. Another standout feature is Magic Design, which uses AI to generate design templates based on user-uploaded content. Users can simply upload an image or enter a prompt, and Canvas AI suggests layout options, font pairings, and color palettes that align with the content’s tone and purpose. Canva also uses AI in tools like Magic Eraser and Magic Edit, which enable users to remove or replace elements in images with simple brush gestures powered by generative AI. These features make advanced design capabilities accessible to non-designers, increasing user engagement and content quality. 2. Salesforce Uses AI to Power Smarter CRM Salesforce’s Einstein AI is a real example of how AI can enhance digital products. This AI engine makes customer relationship management more intelligent and proactive. Einstein analyzes customer data to recommend next steps, predict lead conversion, and personalize communication, helping sales and marketing teams make data-driven decisions. For example, Einstein Lead Scoring ranks leads based on their likelihood to convert, using past interaction data. Einstein Bots handles customer support queries using natural language understanding, reducing the workload on human agents and improving response time.<>/p 3. Adobe is Making Creativity Faster with AI Adobe integrated its generative AI engine, Firefly, into tools like Photoshop and Illustrator to make creative work more intuitive. Users can generate images, textures, and text effects simply by typing a prompt, cutting down on hours of manual design. Features like Generative Fill let users extend images, remove objects, or create entirely new elements with just a few clicks. This allows professionals and non-designers to create high-quality visuals without deep editing skills. Adobe’s AI tools streamline workflows, support ideation, and make creative exploration more accessible. 4. Shopify Made E-commerce Smarter with AI Shopify is using AI to support merchants with everyday operations and growth. One key feature is Shopify Magic, which helps sellers auto-generate compelling product descriptions based on keywords or images. This saves time for small businesses and ensures content is optimized for sales. Shopify also integrates AI for fraud detection, inventory management, and smart search, giving store owners powerful tools that scale with their business. These features help create a seamless experience both for sellers and their customers.Where to Add AI to Your Digital Products: Your Strategic Hitlist
So you have got the “why” and the “what” down. Now, let’s dive into the “where.” The truth is that not every feature or module in your digital product needs AI. But certain areas? They are ripe for this transformation.
Start with user intelligence. AI can help segment users based on behavior, personalize experiences, or prioritize support tickets based on urgency or sentiment. Next, use AI for predictive analytics, whether forecasting demand, highlighting content relevance, or anticipating user churn. You can also integrate conversational AI to enhance onboarding, guide through features, or handle FAQs, saving your team hours each week. Automated content recommendations? A win. Fraud detection, anomaly alerts, or behavior scoring? Even better. These aren’t just “nice-to-haves.” They turn your product from a tool into a proactive, AI-enabled digital product that continuously delivers more value.Red Flags: Where NOT to Use AI in Digital Products
AI is good at many things, but it’s not a silver bullet. There are a few areas where using AI in digital products can do more harm than good.
Billing, contracts, or anything that involves legal compliance? These should always have a human in the loop. AI can assist, but you don’t want it making final calls in high-risk zones. Likewise, if you are dealing with regulated data like health or financial records, be very clear on governance and privacy compliance. And here’s a big one: don’t try to automate all human interactions. Especially in B2B or sensitive use cases, people still want people. Use AI tools in your digital products to free up your team, not replace them. Think of AI as salt in cooking: a little can enhance the flavor, but too much can ruin the dish.So, How Do You Build an AI-enhanced Digital Product? Here's the Blueprint
You have identified where AI can help; how do you implement it now? Here’s a 3-step roadmap for transforming your software into an AI-enabled digital product.
Step 1: Lay the Data Groundwork First, make sure your product’s data is well-structured and accessible. Think of every email, click, and form as a puzzle piece. Without quality data, your AI foundation will be shaky. Tag your data, label it, and ensure it’s cleaned regularly. Step 2: Develop Models, Smartly Start with models that solve a specific, measurable problem. You don’t need a massive AI buildout from day one. Work with what’s proven. Test early. Learn fast. And never forget to retrain; your product evolves, and so should your models. Step 3: Make AI Feel Native This is where user experience matters. If your AI predicts churn, explain it. If it recommends content, show why. The more transparent your AI is, the more your users will trust it.Finding the AI Sweet Spot: A Hands-On Playbook
Feeling a bit overwhelmed? Let’s simplify. Here’s a practical framework to find where AI fits best in your digital product:
- Run a Data Discovery Workshop: Gather your product, support, and analytics teams to identify users’ pain points.
- Map to Use Cases: If your customers struggle to get personalized experiences, timely support, or reasons to stay engaged with your product, those are strong indicators of where AI can make a difference.
- Prototype, Don’t Perfect: Build quick pilots. Even a basic content recommender or sentiment detector can prove ROI.
- Assign Ownership: Make sure someone’s watching over model performance and retraining.
- Track Business Outcomes: AI should save time, increase conversions, or improve engagement. Quantify it.
Final Word: Think Long-Term, Act Today
To navigate this evolving landscape, both clients and consultants must adopt a future-focused, adaptable mindset:
- Invest in upskilling teams and leadership on AI capabilities
- Establish scalable data governance and architecture
- Prioritize ethical, explainable, and auditable AI models
- Use agile approaches to rapidly iterate and refine solutions
- Monitor and adapt to regulatory and technology shifts proactively
Final Thoughts
Digital AI products have a competitive edge in speed, personalization, and decision-making. Whether adding AI features or designing digital AI products from scratch, the potential impact is enormous.
Your competitors may already be experimenting. That’s okay. What matters is how intentionally you approach AI, aligning it with business outcomes, building trust with users, and evolving as you learn. So start today. The opportunity window is open. Take one intelligent step forward, and your product will never be the same again. We can help you in developing AI features for your mobile app, CRM software, or any digital product you have or we can build one from the scratch.