For years, online retail has been organised around a simple assumption: the customer journey begins on a search engine, marketplace, brand website, or app. That assumption is starting to look dated.
A new Salesforce report suggests that more shoppers are now beginning with a question to an AI system, whether through ChatGPT-style assistants built on large language models, an AI tool embedded on a retailer’s website, or a conversational interface inside another platform.
According to the fourth edition of Salesforce’s State of Commerce report, the use of agentic search as the first step in the shopping journey grew 200 per cent year on year.
The findings are based on a survey of 3,450 commerce professionals across 20 countries and 13 industries, including 100 respondents from Singapore. Salesforce also drew on a consumer survey of 4,689 shoppers and behavioural data from more than 1.5 billion shoppers across 37 countries.
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For Southeast Asian retailers, the shift is not just another channel to add to the marketing mix. It raises a more fundamental question: if customers no longer start on a brand’s own website, how does a business make sure its products, prices, inventory and brand information are accurately represented wherever discovery happens?
Discovery is moving away from owned channels
Salesforce’s behavioural data points to a sharp change in how shoppers find products. Traffic referred from AI chats grew between 150 per cent and 428 per cent year on year in every quarter measured, while overall traffic grew only in the single to low double digits.
Consumer behaviour appears to be moving in the same direction. Between August 2025 and May 2026, the rate of shoppers discovering products through brand-owned properties fell 7 per cent, while traditional search fell 15 per cent. Over the same period, the rate of consumers choosing newer discovery channels, including AI assistants, social media AI and delivery apps, grew 38 per cent.
This matters in Southeast Asia because commerce is already highly fragmented. A shopper in Singapore, Jakarta, Manila or Bangkok may move between a marketplace, TikTok, WhatsApp, a delivery app, a physical store and a brand’s website before buying. AI adds another layer to that path. It can compress the discovery process into a single conversation, but it also means the first recommendation may happen outside the retailer’s direct control.
Singapore commerce leaders appear to understand the direction of travel. Eighty-two per cent of respondents in the city-state said large language models will be essential to product discovery within the next year. Many are already adjusting their playbooks: 42 per cent are improving product content quality, 40 per cent are optimising content for conversational queries, 39 per cent are submitting data feeds to AI search platforms, and 38 per cent are rewriting product descriptions for natural language.
In plain terms, retailers are trying to make their catalogues more understandable to machines. A conventional search page may match keywords. An AI assistant tries to interpret intent: “What should I buy for a humid climate?”, “Which running shoes work for flat feet?” or “What is a good gift under S$100?” If product data is incomplete, inconsistent or badly structured, the brand may be invisible in these conversations.
Adoption is still early, but the pressure is rising
Despite the momentum, business adoption remains uneven. Only 28 per cent of Singapore organisations surveyed said they currently use agentic AI. Of those that do not, 52 per cent plan to deploy it within the next six months.
That gap between consumer behaviour and corporate readiness is where the pressure is building. Eighty-six per cent of commerce leaders said AI is raising customer expectations, while 41 per cent said meeting those expectations is harder than ever. Implementing or expanding AI has become both their top priority for the year ahead and their top anticipated challenge.
The term “agentic AI” refers to AI systems that can take actions toward a goal, rather than simply generate text or answer questions. In commerce, that could mean helping a shopper compare products, checking availability, recommending bundles, handling returns or routing a service request. Fully autonomous purchasing remains early, but the influence of AI at the discovery and decision stage is growing quickly.
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In Asia Pacific, companies that have already adopted agentic AI appear to be moving beyond pilots. Only 5 per cent of APAC adopters said they are still primarily testing use cases, while 35 per cent, the largest share, said they are scaling AI across functions and teams, from service and IT to merchandising.
Adopters reported gains in customer satisfaction, personalisation, operational efficiency and employee productivity. Those benefits are attractive in a region where retail margins can be thin and customer acquisition costs have risen across marketplaces and social platforms.
The data problem behind the AI promise
The harder part is that AI does not fix messy systems by magic. In many cases, it exposes them.
Salesforce’s Singapore findings show a commerce stack under strain. Eighty-one per cent of commerce leaders said their vendor count had grown over the past two years. Only 25 per cent said their customer data is fully unified across sales, service, marketing and commerce.
The consequences are practical. Among organisations with fragmented data, 36 per cent reported slow or ineffective responses to customer issues, 32 per cent struggled to measure the impact of commerce investments, and 40 per cent said they faced high costs maintaining disconnected systems.
Omnichannel operations remain a weak point. Just 2 per cent of Singapore multichannel organisations reported no significant failure points. The most common problems were inventory not being synchronised in real time, cited by 46 per cent, and inconsistent pricing and promotions, cited by 36 per cent.
These issues are not new, but AI makes them more visible. If an AI assistant recommends a product that is out of stock, quotes the wrong price, or gives a customer a different answer from a store associate, the experience breaks. In markets such as Southeast Asia, where consumers often compare across channels before buying, these inconsistencies can quickly lead to abandoned carts or lost trust.
Physical retail is also being pulled into the same digital loop. Salesforce found that stores remain the top holiday shopping destination for 77 per cent of consumers, but the in-store journey is increasingly online. Seventy-nine per cent of shoppers use their phones while shopping in store, and 12 per cent ask an AI assistant for purchasing advice in the aisle. Meanwhile, 86 per cent of B2C respondents said customers expect the same personalisation in store as online.
Why unified data becomes the battleground
The report suggests that companies that have made progress on data unification are already seeing returns. The most commonly cited benefits include better alignment between sales, marketing and commerce teams at 44 per cent, improved customer retention and loyalty at 42 per cent, and better AI and automation outcomes at 31 per cent.
That makes data infrastructure less of a back-office concern and more of a competitive issue. As AI becomes a new gateway to shopping, retailers will need to ensure that product information, customer context, promotions, inventory and service histories can travel across channels.
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“Customers are no longer starting their search on a brand’s website or a search bar, they’re starting it in an AI chat, a social feed, or a delivery app,” said Swatantra Kumar, Regional Vice President at Salesforce. “Companies selling online and offline need to show up wherever discovery is happening — and that only works if their data is unified enough for AI to represent their products and brand accurately.”
For Southeast Asia’s commerce players, the near-term question is not whether AI will matter. It already does. The harder question is whether their systems are ready for a world where the first shopfront a customer sees may not be a shopfront at all, but an answer generated by an AI assistant.
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