Hardware and building supply retailers operate in a demanding environment. Product ranges have widened, customer expectations have shifted, and many retailers can find it difficult to understand exactly what is happening in their business because their data sits across systems such as EPOS, accounts, supplier files, loyalty programmes, and online channels. This can result in decisions being driven by historical or incomplete information, rather than the connected, forward looking data that supports quicker, more confident action.
Where AI Is Starting to Make a Difference for Retailers
Across the sector, many hardware and building supply retailers are exploring how connected and predictive data can support clearer, quicker decision-making. For many, this shift begins with recognising the limits of traditional reporting. Historical analysis can be difficult and time-consuming to produce, and delays in gathering reports often hold up decisions. Moving beyond this reactive approach to understand what is likely to happen in the future allows retailers to focus earlier on the areas that matter most.
By unifying data from internal business systems, such as EPOS, accounts, online, ERP and supplier files, AI can reduce strategic and operational blind spots, giving the team a stronger foundation for planning, buying, and trading decisions. AI also allows for earlier detection of things like shifts in demand, margin pressure, or stock issues, so managers can act quickly rather than wait for monthly reports.
Here are some examples of how AI is changing how retailers work:
1. Business performance: Retailers are beginning to rely on connected and predictive information to help them better understand business indicators such as:
– trends in sales, margin, stock value, and category performance
– early signals that trading patterns may be starting to change
– where attention may be needed based on unusual movement or emerging patterns
2. Inventory: Predictive information is helping teams make more confident decisions in areas such as:
– early signals that availability may come under pressure
– indications that certain products are becoming slow movers and may impact cash flow
– forward-looking prompts that show where replenishment levels may need adjustment
3. Customers: Retailers are increasingly exploring connected and predictive information to help them understand things like:
– changes in visit frequency or spend
– variations in basket composition and category interest
– differences in behaviour across trade and consumer buyers
A little prediction goes a long way
These forward-looking signals do not replace local knowledge, but they often give retailers more time to act, reduce surprises, and provide a clearer sense of where attention is needed day to day. That small shift, from relying on historical or incomplete data to using connected, predictive modelling and prompts, can create a significant impact on business growth. It helps move the business from a purely retrospective view to a more future facing approach, where decisions are shaped by what is likely to happen rather than what has already occurred, and where teams can operate with greater clarity and confidence.
A Practical Way Forward
AI does not have to be disruptive. The Galvia Platform connects directly into the you already use, fitting naturally into existing operations. We start with the problem or opportunity already visible in your data and work back from there. This usually begins with one focused use case, such as sales or inventory forecasting, increasing revenue from existing customers or understanding how best to grow the business… The goal is always the same: to prove value quickly without disrupting day-to-day operations. From this foundation, the platform delivers predictions and prompts in practical, commercial terms to support faster, more confident decisions.
The HAI – Galvia Pilot Programme
We are very proud to support Hardware Association Ireland members on their AI journey. As part of this, we are launching a small Pilot Programme for members who want to uncover the opportunities already within their data. Through a short, collaborative process, Galvia will work with you to shape an AI use case for your business and carry out a focused data discovery and data review to identify where AI can deliver meaningful impact.
To learn more about this Pilot Programme or to understand how AI could support your 2026 business objectives, contact Karina Kelly, karina@galvia.ai or go to www.galvia.ai/retail.
KARINA KELLY
Enterprise Development Lead
