By Raviteja Dodda, CEO & Cofounder, MoEngage
India has become one of the world’s fastest adopters of artificial intelligence. An IBM report shows that nearly 59% of Indian companies already use AI—outpacing the US, UK, and even China. From chatbots to campaign copy, businesses are experimenting with Generative AI at scale.
But let’s be honest: most of these efforts fall flat.
Why? Because brands are treating Generative AI as a shiny new add-on, not a core part of their customer engagement strategy. The result? A flood of generic, AI-written messages that may look impressive at first but fail to resonate. Consumers tune them out.
So here’s the uncomfortable truth: Generative AI, when used in isolation, is ineffective for customer engagement.
The real potential of Generative AI is only when it is integrated with customer data. When AI comprehends a customer’s history and preferences, it can craft messages that are genuinely helpful and personalized.
Why AI Must Live Within Your Engagement Platform
When Indian brands first started using Generative AI, many followed a flawed approach. They treated it as a separate, standalone tool, disconnected from their core customer engagement platforms. When Generative AI is bolted externally, it operates in a vacuum. It overlooks the vast amount of intelligence embedded within your marketing platforms.
The correct approach is to integrate the AI directly into their customer engagement platform. This allows them to generate content based on what they know about their customers. When the AI is embedded, it can automate tasks like content creation and making recommendations. Embedding Generative AI automates tasks like content creation, recommendations, and more while maintaining a unified customer view. According to a recent report, the most common use of Generative AI among marketers is content creation, writing copy and generating image assets. This boosts efficiency and helps build stronger relationships, driving loyalty and growth.
When Generative AI is native to the customer engagement platform, it has instant access to the rich context needed to be truly smart:
- Unified Customer Data: It sees a complete, 360-degree view of every customer by combining purchase history, browsing behavior, and customer interactions into one profile.
For example, a retail brand can seamlessly connect online and offline experiences by identifying customers who browse products online but prefer to purchase in-store..
Similarly, a bank can improve ad suppression by recognizing existing customers across multiple devices. This helps avoid showing them acquisition ads for products they already have, ensuring that marketing spend is efficiently allocated to new customers and preventing redundant ad exposure to current customers.
- Past Campaign Performance: Generative AI can analyze historical campaigns to learn what messaging, channels, and timing drive the best results, and then apply those learnings to future interactions.
For example, when crafting a promotional email, AI will review the best ones that include similar subject lines, words, and calls to action. By analyzing these successful campaigns, it identifies the patterns that consistently drive high engagement. This data-backed insight helps to provide actionable suggestions, helping you optimize your campaigns for better open rates and a stronger impact. - Dynamic User Segments: Instead of relying on static lists, Generative AI can identify segments based on real-time behavior, such as predicting which customers are most likely to convert, and engage them instantly.
For example, when launching a new loyalty program, brands can leverage Generative AI to find a segment of users who’re likely to convert in the next 15 days. It can then dynamically refine this group in real-time. This means the offer reaches the best customers at exactly the right time.
With this native intelligence, the platform can close the gap between insight and action. It moves beyond simply generating content to finally delivering on the long-held promise of true one-to-one personalization.
From Efficiency to Hyper-Personalization
Generative AI allows brands to identify and engage precise “micro-segments” with highly customized communications and offers that align perfectly with individual needs. This directly helps create a hyper-personalized experience for customers.
Furthermore, since Generative AI understands a brand’s unique voice, it can generate content that is not only personalized but also consistently on-brand, ensuring every campaign feels authentic. This powerful combination of relevance and authenticity is what drives higher campaign ROI. It leads directly to brand’s increased engagement and click-through rates because customers receive content they genuinely find valuable.
This focus on genuine engagement fosters deeper emotional connections, boosting loyalty and retention, and ultimately turning marketing into a more efficient and profitable engine for growth.
Empowering, Not Replacing, Marketers
The goal of AI is not to replace marketers, but to empower them. When AI is built into the customer engagement platform, it handles the repetitive, time-consuming tasks, unlocking significant productivity gains for the entire team. Brands can launch sophisticated, multi-channel campaigns faster than ever before, freeing their teams from manual execution. This newfound efficiency allows marketers to elevate their focus to what matters most: creativity, strategic thinking, and deep customer analysis.
Looking ahead, the line between marketing, technology, and customer service will only continue to blur. The brands that will win in this new era are not those who simply adopt Generative AI, but those who truly integrate it.
By investing in customer engagement platforms with built-in Generative AI, Indian brands can move beyond simple automation and finally build the genuine, at-scale customer relationships that drive sustainable growth.