How Singapore’s Shops and Restaurants Are Getting Practical Results From AI

For Singapore’s retailers and food-and-beverage (F&B) businesses, AI’s immediate value is in everyday decisions: filling tables without excessive waits, handling enquiries and reducing administrative work. The strongest reported restaurant result is promising but narrow, while disconnected systems remain a substantial barrier to repeating it across the sector.218

What a measurable AI gain looks like

At Fico, The Lo & Behold Group used AI in its approach to reservation management and table turnover. The restaurant reported a 2% increase in weekend revenue in the first month after a June 2026 rollout.2 That is a useful business outcome, but it is one restaurant’s early result—not a measure of profit, a sustained improvement or a sector-wide productivity rate.

The broader set of practical applications is less theatrical than robotic service. Reporting on Singapore’s shops and restaurants identifies automated staff rostering, reservation management, customer helpdesks, marketing content and administrative paperwork as common AI projects.2 Each needs its own measure of success: more usable capacity for reservations, fewer staff hours spent on repetitive tasks, or faster responses that still resolve customers’ problems. Faster output alone does not establish a financial return.

Retail offers a different kind of use case. Enterprise Singapore describes a Castlery app feature that uses image recognition to find a close match in the furniture retailer’s catalogue from a customer’s photo.11 That demonstrates a way to help shoppers discover products, but the cited account does not establish a sales or productivity gain from the feature.

Why scaling is harder than running a pilot

These are labour-intensive, customer-facing operations with competing demands on staff time. For a restaurant, the potential value of a better booking decision depends on whether it can be carried through to service. For a retailer, a useful recommendation must ultimately match available products and fulfilment. Manpower constraints and supply-chain pressures make those connections more important; an AI tool cannot resolve them simply by generating an answer.

Disconnected data is a concrete obstacle. A UOB survey cited in local reporting found that six in 10 Singapore F&B operators used mostly standalone digital systems.18 If reservations, point-of-sale records, staffing and inventory sit in separate tools, a business has more work to do before it can use them together reliably. The Enterprise Singapore–UOB programme is explicitly designed to support both AI-enabled solutions and digital-system integration.1725

Skills and training matter too. Staff need to know when to trust a system’s suggestion, when to correct it and when a customer issue requires a person. A pilot should therefore test the workflow around the tool, not just the tool’s ability to produce a plausible response.

A practical route from pilot to wider use

1. Pick one operational problem. Start with an identifiable loss of time or capacity, such as unanswered enquiries or underused tables.
2. Connect only the data the task needs. Check whether relevant booking, sales, staffing or stock records are complete and usable before adding automation.
3. Measure against a baseline. Compare revenue or capacity, staff time, errors and customer outcomes before and after the pilot. Include subscription, integration and training costs when assessing net benefit.
4. Keep exceptions with people. Define who handles complaints, disputed refunds and decisions where a system’s suggestion could harm the customer experience.
5. Expand when results repeat. An initial improvement at one outlet or during one month is a reason to test further, not to assume the same return everywhere.

Businesses looking for support can consult the sector-specific digital guidance under IMDA’s SMEs Go Digital programme, which is identified in reporting on these AI projects.2 The Enterprise Singapore–UOB F&B AI and Digital Integration Programme aims to support at least 200 F&B businesses over two years.25 UOB lists funding of up to 50% for eligible SMEs and up to 30% for eligible non-SMEs on qualifying AI-adoption and integration costs; those rates are not a blanket subsidy for any AI purchase.17 The Enterprise Development Grant is another transformation route, but its eligibility and project terms should be checked separately rather than assumed to match this programme.42

The likely payoff is a better-run business, not necessarily a less human one. Fico’s early revenue result shows why targeted AI is worth testing; the prevalence of standalone systems shows why the ability to connect data, train staff and verify net gains will determine whether such wins can scale.218