Retailers embed AI to boost competitiveness

AI with intent drives lifecycle decisions.

Retailers are entering a new phase of artificial intelligence adoption, shifting from experimental pilots to embedded systems designed to drive measurable growth and competitiveness. The model, described as “AI with intent”, centres on integrating decision-grade intelligence directly into core business processes rather than relying on standalone tools.

“We identify that AI has now become compulsory for all businesses,” said Alex Luu. “So for us, we came up with what we call ‘AI with intent' where it reflects a shift from experimental or generic AI towards something that we call decision, great, intelligent, and embedded into the core business process.”

Luu argued that many existing retail AI applications function in isolation. “Many AIs today function as a standalone engine, which means it's considered as a demand forecast tool, generative assistant, or analytic layer that produces the output without understanding the business constraint,” he said. “So this often leads to low trust and high reward.”

By contrast, the “AI with intent” approach is built on three pillars. “First, we’re domain aware. We build on the data of retail, apparel, and consumer good data models. Second, it's contextual, where we understand where the decision sits on the product life circle. And lastly, actionable. This means it’s designed to write specific decisions, not just inside,” Luu said.

Embedding AI across the product lifecycle is central to the strategy. “Centric takes a fundamentally different approach by embedding intelligence directly into a workflow across the entire product life circle,” Luu said, referring to stages from planning and design to sourcing, pricing and inventory. 

“Intelligence is supported by the real time data across the team… reflecting the market signal, consumer feedback and sales through performance. And it can apply at the moment the decision is made, not after the fact.”

The model operates as a closed loop, where “the market is directly influenced by the future product decision.” According to Luu, this integration delivers tangible commercial benefits. “By using the closed loop system combined with AI, the customer typically sees the faster time to market and improves the heat rate, and it reduces the hand off and the manual transaction between teams.”

Beyond efficiency, the approach aims to strengthen organisational alignment. “It improves the alignment, the collaboration between the team… So in practice, this turns AI into the multiplier of human expertise, not a replacement,” he said.

A cloud-native SaaS architecture underpins the framework. “Our system is built based on the configuration rather than the hard coding… so now, the retailer can evolve their AI capability… without doing the large transformation project,” Luu said. 

Ultimately, he summarised: “AI is not treated as a feature, but as an operation principle, embedded, contextual, and continuously evolving with the business.”