Redefining retail strategy with AI with intent

Centric Software’s AI with intent integrates decision-ready intelligence across planning, design, sourcing, pricing, and inventory operations.

Artificial intelligence has rapidly become a staple in the retail and consumer goods industries, with tools that promise speed, efficiency, and deeper insights.

But for many retailers, the reality is less transformative than expected, as many AI solutions remain experimental and disconnected from core workflows. Some are even limited to generating recommendations without a clear path to action.

AI with intent
For Centric Software, the challenge is to deploy AI with purpose. Its philosophy, “AI with intent,” does away with the approach of just layering intelligence on top of existing systems, as it embeds AI directly into retail operations.

“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 decisive, great, intelligent, and embedded into the core business process,” Alex Luu, Regional Director for the Philippines and Vietnam at Centric Software, told Retail Asia.

AI tools are often deployed as separate engines that sit on top of fragmented systems. Whilst these platforms may generate insights or predictions, they rarely understand the broader business context in which decisions are made. This disconnect, Luu noted, frequently leads to low adoption and limited business value.

To address this gap, Centric Software’s AI with intent model aligns AI with the realities of retail operations. It goes beyond simply producing analytics, with the system focused on enabling decisions at the exact moment they are needed.

The framework possesses domain-aware intelligence, as its AI models are trained on retail, apparel, and consumer goods data. It also has contextual understanding, with systems that recognise where decisions sit within the product lifecycle. Moreover, it provides actionable insights, as it is designed to support specific business decisions rather than simply generating information.

Embedding intelligence across the product lifecycle
Retail operations involve complex and interconnected processes which include planning, product design, pricing, merchandising, and inventory management.

To avoid insights arriving too late because of functions operating in isolation, Centric’s approach embeds AI directly into these processes. This creates what Luu describes as a closed-loop decision system.

Instead of analysing data after the fact, the platform integrates real-time information across teams. Market signals, consumer feedback, and sell-through performance feed directly into planning and product development workflows, which allows companies to make faster decisions across the product lifecycle.

In practice, this approach can deliver faster time-to-market for new products, higher product hit rates by aligning designs with real market signals, and reduced manual handoffs between teams.

“It improves the alignment and the collaboration between the team, the same from the creativity team, merchandising team, and supply chain team. This turns AI into the multiplier of human expertise, not a replacement,” Luu stated.

In this approach, designers, planners, and merchandisers remain central to decision-making.

Cloud-native architecture
Technology architecture also plays a critical role in making AI sustainable for retail organisations. Traditional enterprise systems often require long, complex upgrade cycles that can slow innovation.

In response to this, Centric Software built its platform on a cloud-native SaaS architecture that allows retailers to adapt quickly as market conditions evolve. Because the system is designed around configuration, businesses can refine models, incorporate new data, and experiment with workflows without undertaking major transformation projects.

This flexibility is particularly important as today’s consumer behaviour, supply chains, and digital ecosystems change rapidly. It also makes room for retailers to expand their AI capabilities and reduce the risk associated with large-scale technology initiatives.

“Our architecture ensures that AI remains relevant and scalable over time, rather than becoming obsolete as business conditions change,” Luu said.

As AI adoption accelerates, the real differentiator may not be who uses AI but how it is used. Instead of treating AI as a feature or add-on, Centric Software, with its AI with intent, positions it as a foundational element within the retail value chain.

By integrating AI into the very fabric of product development and retail operations, Centric Software aims to move the conversation beyond experimentation.

For retailers navigating constant shifts and seeking a more practical path toward intelligent decision-making, begin your journey with Centric Software. Visit them here.