In today’s AI-driven world, Intelligence at scale: Data monetization with Gen AI is reshaping business models. Traditional models focused on selling raw or aggregated data are faltering. Instead, companies are turning to generative AI (Gen AI) to push beyond analytics and build intelligence-rich data products. This strategic shift enables organizations to unlock deeper insight, automate action, and create new revenue streams.
With Gen AI, businesses no longer need to stop at dashboards or reports. Intelligence emerges when AI transforms raw data—especially unstructured sources like documents, voice transcripts, or social media—into contextual recommendations, integrated directly into business workflows. This move from “insight” to “intelligence” drives more impactful decisions and unlocks higher value.
Take Walmart’s Scintilla (formerly Luminate): a data product built on shopper behavior. In just one year, the product’s revenue grew 80% quarter over quarter, with a 173% year-on-year growth in customers and a perfect renewal rate—all thanks to AI-powered intelligence embedded in supplier workflows.
The classic DIKW (Data → Information → Knowledge → Wisdom) model illustrates progression:
Data: Raw, unorganized inputs.
Information: Cleaned, organized summaries and charts.
Knowledge: Patterns and trends with context.
Wisdom: Judgment-driven, actionable insights.
Gen AI propels organizations up this pyramid rapidly—especially by unlocking unstructured data and connecting it in real time to drive intelligent outcomes.
Raw data is becoming commoditized, privacy regulations are tightening, and synthetic data options are emerging. By 2026, it’s predicted that 75% of businesses will leverage Gen AI to create synthetic customer data—up from under 5% in 2023. These shifts put pressure on old-school data resale models and force innovation.
Gen AI enables companies to create intelligent data products—for example:
Personalized content: Automotive firms, using Gen AI, built lead engines that boosted qualified leads by 15–25% and increased parts/service sales by 25–30%.
Real-time decision-making: In banking, AI tools optimize collections—identifying who to contact, when, and how—improving prompt-to-pay outcomes.
Agentic AI: Fully autonomous systems embedded into workflows can coordinate real-time actions (e.g., e-commerce upsells, intelligent API-based knowledge services) with human oversight.
Organizations follow a typical maturity curve:
Internal Optimization: Use Gen AI internally for automation and efficiency.
Opportunistic Monetization: Offer AI-generated insights externally in tailored formats.
Full Marketplace Monetization: Launch standalone intelligence products with strong GTM models.
To succeed, organizations need six foundational pillars:
Define what makes your data uniquely valuable—whether proprietary access, domain expertise, or customer context. Build your intelligence strategy grounded in competitive advantage.
Adopt flexible pricing models—usage-based, outcome-based, or tiered—and shift customer success from support to strategic partnership. Embed Gen AI products into partner ecosystems for broader reach.
Leverage cloud-native, scalable infrastructure with modular design. Support both structured and unstructured data, multi-agent systems, and robust governance frameworks for trustworthy AI delivery.
Assemble cross-functional teams—engineers, product leads, commercial strategists—and invest in talent development. Internal upskilling and clear career paths are key.
Plan for LLM governance, versioning, observability, and regulatory compliance. Ensure operational readiness across support, legal, finance, and risk functions as your AI products scale.
Be mindful of compute costs, model retraining, and performance degradation over time. Align capital deployment with product maturity and adoption levels, while embedding ethical frameworks and monitoring mechanisms.
Looking ahead, we can expect:
Self-learning assets that dynamically adapt to market trends.
AI agents negotiating in data marketplaces, prioritizing value-driven pricing rather than volume.
Synthetic data exchanges, where AI-generated datasets reduce regulatory risk and open new avenues for safe data monetization.
Intelligence—not raw data—will be the defining competitive asset of the digital economy.
For a deeper understanding of modern data architecture and how to prepare for next-gen data products, check out McKinsey’s insights on revisiting data frameworks: Read more
Explore intelligent digital transformation and AI services via Infozion: Learn more
AI for E-commerce Platforms have become a game-changer in the way online stores function. Have you ever noticed how online stores seem to know exactly what you want? Whether it’s a product you looked at before, a chatbot helping you instantly, or even being able to search by image — it’s all made possible with Artificial Intelligence (AI).
AI is becoming a big part of e-commerce. It helps online shops work faster, understand customers better, and sell smarter. In this blog, we’ll explain how AI is changing the world of e-commerce in a simple way — so even a 5th grader can understand!
Artificial Intelligence (AI) means teaching computers to think and learn like humans. AI can:
Understand what people say
Make smart decisions
Recommend things
Answer questions
Help with tasks
When you shop online, AI is working in the background to suggest products, talk to you via chatbots, and help you find what you need quickly.
AI tracks what customers like, search for, or buy. It then shows them products they are most likely to be interested in. It’s like a personal shopping guide on your screen.
AI chatbots can help customers 24/7. They answer questions, guide people through checkout, and provide delivery updates — all without needing a human.
AI gives suggestions based on a customer’s activity. This helps them discover things they didn’t even know they wanted — increasing chances of purchase.
AI learns from your activity and compares it with others. It then recommends products you might like.
If you bought a cricket bat, it may recommend gloves, balls, or a kit bag. This keeps customers engaged and boosts sales.
AI allows customers to upload a photo to search for similar items. This is helpful when you don’t know the name of a product.
Big brands like Amazon and ASOS use this to improve customer experience.
AI-powered chatbots help users:
Ask questions
Find products
Track orders
Get help instantly
They’re always online, making support easier and faster for businesses.
Many people use Alexa, Siri, or Google Assistant. E-commerce websites now allow voice search, where customers can speak to find what they need.
This makes shopping easier for kids, elderly users, or people who find typing hard.
AI helps businesses track what’s selling and what’s not. It predicts demand and even places restocking orders automatically.
This prevents stock issues, saves money, and keeps customers happy.
With better suggestions and faster service, customers are more likely to buy. AI boosts conversion rates and grows revenue.
AI handles customer queries, stock tracking, and suggestions — freeing up human time and reducing workload.
AI can send targeted emails, offers, and product suggestions to the right people at the right time.
AI reduces human mistakes. It processes data and orders more accurately.
When users enjoy browsing and get help quickly, they return more often. This builds loyalty and brand trust.
Imagine a clothing store that sells online. With AI, it can:
Suggest matching clothes
Help customers find their size
Answer style-related questions
Offer visual and voice search
Track what’s trending and restock automatically
This makes the business smarter and more customer-friendly — just like what Infozion Technologies helps companies achieve through tech-driven e-commerce solutions.
The future is exciting with AI evolving every day. Here’s what we can expect soon:
Advanced virtual try-ons for clothes or glasses
Full voice-based shopping experiences
Better fraud detection and safe payments
AI-generated content and product listings
Hyper-personalized homepages and dashboards
Want to know why experts believe AI is the future of e-commerce? Read more in this Bloomreach article.
Here’s a quick table to remember how AI helps e-commerce:
AI Feature | How It Helps |
---|---|
Product Suggestions | Helps users discover products they’ll like |
Chatbots | Always-on support for customers |
Visual & Voice Search | Makes finding items easier and faster |
Smart Inventory | Tracks and manages product stock |
Marketing Automation | Sends targeted messages and offers |
AI for E-commerce Platforms isn’t just a trend — it’s a smart way to run modern online stores. It helps businesses:
Sell more
Save time
Provide better customer experiences
If you’re planning to build or improve your e-commerce site, now’s the time to embrace AI. From personalized shopping to automated customer support — it’s a game-changer.
Need help creating your AI-powered store? Visit Infozion Technologies to see how we bring smart ideas to life.