How retail marketing pioneers will use AI to redefine their value

Retailers are under intense pressure as a result of huge changes in how consumers behave and what they expect.

For example, digital consumers visit bricks-and-mortar stores far less and now want fast, personalized experiences when they interact with brands.  

Any growth strategy must be underpinned by cutting-edge marketing capable of producing high-quality, attention-grabbing, and measurable content.

According to Attentive, 81% of consumers ignore irrelevant messages, while 96% say they’re more likely to purchase when a brand gets personal.¹

However, large, multi-brand retailers can struggle to keep pace with consumer demands.

David Billings, Global VP of Marketing Services at Empathy Lab by EPAM, explains: “As digital becomes the primary touchpoint, the ability to anticipate, personalize, and scale becomes the defining challenge for retail marketers. At the same time, with AI agents set to recommend products and transact on consumers’ behalf, retailers must be ready for a profound shift in how they approach both demand creation and fulfilment.”

GCP tools for marketing excellence

To meet these challenges, IT leaders and marketers need to unify consumer transactions as well as business data, build predictive models, and generate and distribute content efficiently.

Google Cloud Platform (GCP) offers tools to support these needs. Google Cortex, for example, aggregates sales and marketing data in real time without extensive custom integration. Vertex AI can be used to train and deploy machine learning models that predict preferences and recommend products. Creative tools like Veo 3 assist in generating content quickly, while integrations with ad platforms and CMS systems help ensure that personalized messages reach consumers through the right channels.

Now, agentic AI is unlocking new opportunities. Billings explains: “Agentic AI and Agent-to-Agent protocols mark the transition from marketers automating individual tasks to orchestrating entire workflows. Rather than just improving efficiency, marketers can collaborate with AI agents that coordinate across functions – marketing, supply chain, and finance – to spot threats and opportunities, and respond with assets, campaigns and promotions in near real time.”

Smoothing AI integration

Deploying AI at scale is far from plug-and-play, however. Success depends on pairing high-value use cases with substantial groundwork including robust data engineering, integrating disparate systems, and managing organizational change. Each enterprise must tailor AI applications to its tech stack and business context, which often demands significant transformation.

As CIOs set about this work, capabilities such as EPAM’s Empathy Lab can help ensure investments deliver sustainable value for the CMO. Bringing together marketing practitioners, consultants, data scientists, and engineers, it defines, develops, and scales AI solutions end-to-end – delivering enterprise-grade use cases that drive growth. This capability is complemented by accelerators built on Google technologies such as Gemini and Vertex AI, which turn raw generative AI capabilities into scalable, on-brand, and business-ready workflows.

 Creating high volumes of compliant, on-brand promotional video content across multiple platforms—often spanning thousands of possible and offers—is a clear example of an AI-addressable challenge for retailers. Empathy Lab by EPAM’s Veo 3 Video Shorts integration tackles this by building on Google’s video generation capabilities and adding governance features, brand assets, pre-configured prompts, and platform integrations to support efficient, scalable content production and distribution.

Modernizing customer experience

So where should retail marketers start? Billings provides three crucial steps:

1. Orchestrate for value: Focusing on task automation delivers diminishing productivity gains. The bigger opportunity lies in orchestrating across tasks and functions—using AI to connect data, decisions, and execution in ways that create scaled, sustainable value.
2. Build for scale: Use an enterprise-grade platform like Google Cloud to host multiple AI use cases in one environment for seamless integration.
3. Prioritize change management: Technology alone won’t deliver value. Organizational restructuring, role redesign, and cultural adoption are critical to unlocking AI’s full potential.

Businesses getting this right stand to remain competitive in the digital-first retail environment that’s rapidly taking shape while those that don’t risk falling rapidly behind.

^{1 Attentive, “New Global Study Reveals Consumers Demand More Personalization in Marketing; 81% Ignore Irrelevant Messages, While Personalized Experiences Drive Loyalty and Sales,” April 2025}