From creative AI to smart commerce: Turning business intelligence into real-time impact

In a 40-minute live session, industry experts dived into real-world use cases, architectural insights and future-forward strategies to scale personalization and operationalize intelligence. 

Here’s how modern retailers are turning AI into a competitive advantage — across marketing, customer engagement, operations and loyalty — with real-world examples to bring each capability to life:

Insight-driven creativity

One of the biggest challenges for today’s marketers is making sure every piece is on-brand, relevant and backed by insight. 

Traditional performance reporting often lags behind decisions. Marketing teams wait for analysts, dashboards or weekly reviews, by which time the opportunity has passed. 

Valtech’s conversational analytics demo tackled this head-on. Powered by Google Cloud’s Conversational Analytics API, it lets marketers ask questions in plain English, like “Which campaigns drove the most engagement last week?” and receive instant, contextual answers. No dashboards, no SQL. 

This kind of real-time, conversational intelligence turns analytics into a daily creative partner — fueling quicker, more confident decisions. It represents a broader shift: from “data as reference” to “data as dialogue.” 

“Data is most powerful when it's in dialogue, not hidden behind layers of reports.”
— Gabriel Laliberté, Head of Strategy, Retail/CPG, Valtech Americas

AI-powered discovery

As customer expectations rise, product discovery must evolve from generic filtering to intuitive guidance. The future isn’t search bars — it’s sales conversations at scale. 

“Conversational touchpoints are now part of the journey, not just a support function.”
— Jake Holmquist

Valtech’s AI Concierge transforms commerce by embedding a branded assistant into the buying experience. It understands complex queries, navigates inventory in real-time and even integrates tools like color configurators. All within the conversation.

This is commerce reimagined not around interfaces, but around interaction.

Agentic automation: From monitoring to action

AI is no longer just answering questions, it’s executing decisions. The rise of agentic architecture — where multiple AI agents coordinate across workflows — is reshaping operations. 

“The most impactful AI doesn’t just think. It acts.”
— Lars Ahlfors, Sr. Customer Engineer, ML & GenAI, Google

Google’s Agentspace automates IT support. It analyzes logs, flags issues and proposes or executes solutions — cutting down on resolution times and freeing teams from manual triage. While built for IT, the model applies across retail ops, from pricing adjustments to content updates and inventory actions.

“Think of this as a ‘listen > decide > act’ loop embedded into your operational stack.”
— Lars Ahlfors

Merchandising meets intelligence

In digital retail, guesswork is expensive. Yet many merchandising decisions still hinge on intuition. By aligning customer behavior, product data and experimentation tools, brands can now deliver self-optimizing digital shelves.

“Have you ever made a major digital shelf decision… based on a hunch rather than data?”
— Gabriel Laliberté, Head of Strategy, Retail/CPG, Valtech Americas

With unified pipelines through BigQuery, Looker and Recommendations AI, teams can deploy intelligent PDPs, track variant performance and guide discovery in real time. 

“What builds long-term loyalty: points, personalization, or purpose?” 
— JGabriel Laliberté, Head of Strategy, Retail/CPG, Valtech Americas

The retail AI playbook

The modern retail stack isn’t defined by technology alone, but by how intelligently it’s applied. Here’s how smart brands are connecting strategy to systems: 

From insight to impact

AI in retail is no longer about experimentation. It’s about integration. The winners are those who can deploy intelligence at every touchpoint. Not as a layer, but as the logic that powers everything from strategy to execution.  

“If I had to give one directive to a CMO or CTO tomorrow? Start operationalizing. Scale responsibly, but don’t wait.”
— Jake Holmquist, Field CTO, Google Cloud Solutions

Because when AI moves from theoretical to tactical, from dashboard to decision, it stops being a trend and becomes the foundation of smarter commerce. 

Want to discuss how these solutions can address your specific business needs? Our experts are ready to talk. 

Want to discuss how these solutions can address your specific business needs? Our experts are ready to talk.

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