Infosys TechCompass

Digital engagement platforms

Trend 14: Content platforms shift to intelligent orchestration

Content platforms are moving beyond managing content and assets to coordinating end-to-end content operations. AI enables predictive content creation, automated tagging, translation, and intelligent retrieval, helping teams operate with less manual effort and more consistency across channels. AI agents increasingly orchestrate content, and marketing operations end to end.

This shift also addresses fragmentation. Many enterprises are bringing together disconnected CMS, DAM, and marketing tools into a unified content environment where workflows, governance, and delivery are centrally managed. This reduces duplication, improves turnaround times, and creates a clearer operating model for content management at scale.

Infosys worked with a leading European bank to address fragmented content systems that led to duplication, siloed workflows, and delays in time to market. The bank implemented an AI-enabled content orchestration solution to centralize governance, streamline workflows, and reduce operational overheads. This improved efficiency while enabling more consistent and seamless customer experiences across channels.

Digital engagement platforms

Trend 15: Personalization moves to real-time, intent-led engagement

Personalization is moving beyond predefined segments toward more dynamic, real-time interaction. AI systems analyze behavior, context, and intent signals to tailor experiences at an individual level, reducing the overhead of prebuilt variations and improving engagement relevance.

As third-party cookies decline, organizations are relying more on consent-driven first-party data, behavioral, transactional, and preference data, to support compliant personalization. Personalization engines optimize continuously, shaping content, recommendations, offers, and next-best actions based on microbehaviors and context. Interactive video, AR try-ons, and immersive formats are also gaining traction as higher-engagement personalization approaches.

The above mentioned European bank brought together fragmented customer data and digital touchpoints into a single, AI-powered view of the customer. The engagement combined ML-driven segmentation, generative AI-enabled content and interaction models, and centralized journey orchestration across channels - shifting from reactive, channel-centric marketing toward predictive, customer-focused engagement. This improved digital onboarding, conversion rates, and customer satisfaction, while supporting scalable personalization and faster time to market.

Digital engagement platforms

Trend 16: From search to intelligent assistance across channels

Search is shifting from link-first discovery to AI-led answers across a multiplatform ecosystem. Users increasingly search with conversational and multimodal queries and expect immediate, context-aware responses. This means brands must focus on traditional search rankings and build authority and visibility across social platforms, AI engines, and AI-powered browsers.

Within the enterprise, retrieval-augmented generation is reshaping search by combining generative AI with trusted internal data to deliver accurate, grounded answers in natural language. As discovery becomes more AI-orchestrated, being part of the answer can matter as much as where a link appears.

Infosys worked with a leading American wholesale food company to improve search relevance on its B2B e-commerce platform and support AI-driven product discovery. The solution used AI models to generate personalized recommendations based on browsing behavior, along with autosuggestions and continuous model updates. This improved search accuracy, response times by 30%, and user engagement, while positioning the platform for more data-driven commerce and revenue optimization.

Digital engagement platforms

Trend 17: Retail media expands data-driven advertising across touchpoints

Retail media networks are becoming a major channel for data-driven advertising, allowing brands to reach customers across a retailer’s digital and physical touchpoints, including websites, apps, email, in-store screens, and connected TV.

By using retailer first-party data such as browsing behavior, purchase history, loyalty insights, and in-store signals, brands can target audiences closer to the moment of purchase and measure outcomes more effectively.

As the ecosystem grows, retail media is moving toward stronger interoperability and more consistent measurement approaches to scale across platforms and geographies. It also deepens the intersection of commerce and advertising, with in-store retail media emerging as a larger growth area alongside offsite placements and connected TV expansion.