AI as the new competitive advantage for Singapore’s small retailers

Before small retailers make AI to work, it helps to clear what ‘relevance’ means to shoppers. 

For years, personalised shopping — understanding what a shopper wants and serving it to them at the right moment — was a privilege reserved for businesses with deep pockets. It took large data teams and heavy infrastructure to pull off, so smaller retailers were left competing mainly on price in a crowded market.

That is changing. Artificial intelligence (AI) can increasingly use high-quality commerce and behavioural signals to understand what shoppers are doing, rather than guessing from a demographic bucket. Most importantly, it is making more relevant, personalised commerce accessible to retailers of all sizes by helping them use structured commerce and behavioural data — without requiring every brand to build the necessary technology in-house.

Yet in Singapore, small-and-medium enterprise (SME) AI adoption is lagging. The Infocomm Media Development Authority (IMDA)’s Digital Economy Report found that only 14.5% of Singaporean SMEs have adopted AI, compared to 62.5% of large enterprises.

Singapore’s refreshed Retail Industry Digital Plan (IDP), launched by Enterprise Singapore and IMDA, aims to close this gap for more than 2,000 SME retailers. In a market where SMEs constitute 99% of local businesses, even a partial narrowing of this gap will have a great impact, not just for individual retailers, but at the economy level.

How SMEs can prioritise relevance with AI
Before small retailers can put AI to work, it helps to be clear what ‘relevance’ means to shoppers today. It isn’t just a nice-to-have. KPMG’s latest Customer Experience study found that ‘personalisation’ remains the single biggest driver of brand loyalty amongst Singapore consumers, ranking above ‘integrity’ and ‘time and effort’, the next two most important factors in its framework.  What they don’t enjoy is irrelevance.

Local brands know this, but struggle to convert strategy to results. Research by Boston Consulting Group found that most companies pursue personalisation only superficially, leaving them with frustrated customers, and little to show for the investment. The minority who got it right, in contrast, grow revenue roughly 10% faster than the rest. This disconnect can be addressed by developing product discovery strategies that match products to shoppers using real-time data, not just product descriptions or guesswork.

Encouragingly, Singapore consumers understand this value exchange. Data from Qualtrics shows that 79% of Singapore shoppers prefer to buy from brands that offer tailored experiences, and 54% say the benefits of personalisation are worth the privacy trade-offs from data sharing. That is the opportunity for SMEs — where relevance once required a big budget, AI now allows smaller retailers to do more with the data they already have, provided it is well-structured and accessible.

Preparing for the era of AI shopping assistants
Across Asia-Pacific, shoppers are moving from typing keywords into a search bar toward using AI assistants to discover, research, compare and shortlist products, alongside existing search and retailer channels. In simple terms, shoppers now describe what they want once, and let AI handle the searching, comparing, and increasingly, the shortlisting. In this environment, SMEs’ agility becomes a competitive advantage, as they can move faster to get their existing data AI-ready, without the legacy systems and internal bureaucracy that slow bigger players down.

But there’s a catch. An AI assistant can only recommend what it can properly ‘see’. Most systems easily read a listing’s title, descriptions, images, and reviews, but not the deeper commerce data that determines whether a product deserves to be recommended, like real-time stock levels, current pricing, sales performance, and complementary purchases — unless the retailer provides access.

This is called the commerce knowledge gap — the space between what AI can read and what it needs to make calls. Retailers, not AI platforms, hold that data.

The upside is real. Singapore is already one of the region’s clearest leaders on AI adoption. Research by McKinsey and the Singapore Economic Development Board found that 56% of Singapore enterprises have moved beyond piloting into scaled AI use, amongst the highest rates in Southeast Asia. Retailers who close the commerce knowledge gap stand to capture a similar upside. Many SMEs already hold valuable customer and product data; the opportunity is to improve its quality, structure, permissions, and accessibility so AI can use it to deliver more relevant recommendations.

How SMEs can operationalise success with AI
Turning this potential into value doesn’t require a ground-up digital overhaul; SME leaders can instead focus on a few concrete steps to ensure their businesses are best positioned in this environment.

The starting point is a structured backend inventory, with titles, descriptions, and metadata optimised so AI agents can crawl, read, and trust the data. From there, it's worth checking how products actually appear today – searching for your own bestsellers on a mainstream AI platform will quickly reveal whether listings are missing or outdated, and where the data needs work. Additionally, rather than building infrastructure from scratch, SMEs can plug into existing commerce networks, partnering with platforms that already feed structured, real-time data directly to where shoppers are searching.

Getting the technology right is only half the equation – data also needs to be treated as a two-way exchange. Being transparent about how and why data is collected and following through with genuinely useful recommendations is what builds lasting consumer trust. And because none of this works without the right people behind it, SMEs should prioritise workforce reskilling and redesign roles to support the sustainable integration of AI into daily operations, starting with customer-facing teams – where the leverage is greatest and where the effort aligns directly with the refreshed Retail IDP.

At the end of the day, an SME’s success still rests on the quality of its product or service. AI doesn’t change that, but what it offers is relevance at scale – the ability to compete on personalisation, not just price, without needing a big-brand budget. For Singapore’s small retailers, that is no longer a trend to prepare for but a competitive advantage available today.