Infosys and Adobe are joining forces to help brands move from generic communication to truly personal, data-driven experiences. At the center of this collaboration is AI in marketing, turning signals from websites, apps, and offline touchpoints into timely, relevant actions that customers actually value.
Why this collaboration matters
Modern buyers expect helpful content, not hype. With AI in marketing, teams can predict intent, tailor messages in real time, and measure lift across the entire funnel. That means fewer wasted impressions and more moments that feel natural, useful, and human.
What each partner brings
Infosys brings engineering scale, integrations, and domain expertise; Adobe offers a mature experience stack and a thriving ecosystem. Together, they make AI in marketing practical—bridging data pipelines, identity resolution, content supply chains, and activation across channels.
Joint capabilities you can expect
From audience discovery to journey orchestration, the stack is designed to operationalize AI in marketing without adding complexity. Expect faster experimentation, automated insights for creatives and media planners, and governance that keeps everything compliant and on brand.
Data, privacy, and trust
Responsible deployment matters. Models should respect consent, minimize bias, and protect PII. When done right, AI in marketing blends first-party data with privacy-first analytics, producing accurate segments and recommendations without over-collecting or over-targeting.
Real-world use cases
Imagine connecting product feeds, inventory, and loyalty data with creative variations that adapt per audience. With AI in marketing, a single campaign can localize messaging, rotate offers by propensity, and throttle spend toward the best-performing journeys—automatically.
Retail: from browse to buy
Retailers can pair behavioral signals with dynamic content: size, color, or bundle suggestions that update in real time. By applying AI in marketing, you can suppress promos for low-inventory items, spotlight fast-moving SKUs, and personalize post-purchase care at scale.
BFSI: relevance with rigor
Banks and insurers need precision plus compliance. Journey rules can guide advice, eligibility checks, and next-best actions. Using AI in marketing, messages shift with risk thresholds and life-event triggers, improving relevance while honoring regulation and consent.
What this means for marketers
Creative teams get briefs backed by insights. Media teams see budget move to winning audiences automatically. CRM teams unlock lifecycle moments that used to be manual. Above all, AI in marketing helps align brand promise with customer reality—consistently and measurably.
A practical roadmap to start
Begin with clean first-party data, consent, and clear objectives. Stand up a pilot with a single journey, define success metrics, and iterate weekly. As AI in marketing proves lift, expand to adjacent use cases, templatize your playbooks, and industrialize content operations.
Looking ahead
As models improve and guardrails mature, expect creative production to become more modular and measurement more granular. With AI in marketing, teams will move from isolated campaigns to living programs that learn continuously and compound results over time.
Partner with Digilogy for faster outcomes
If you want the results of enterprise-grade personalization without enterprise-grade complexity, Digilogy can help—from data strategy and tool stitching to creative ops and experimentation. Ready to translate AI in marketing into revenue and retention? Get started with Digilogy today.
