Original research | Baseline 2026-07-27

What the first singapore AI evidence baseline shows.

A transparent snapshot of the comparison dataset, built to show where public evidence is strong and where a buyer should slow down.

Why read

Use this baseline to see evidence gaps before you trust a shortlist.

The short answer: the dataset is useful for deciding what to investigate next, not for declaring a safe, effective, or universally best product.

For: enterprise singapore buyers who need to explain why a product is on, or missing from, a shortlist.

What to do with the numbers

Start with a category, market, workflow, and measurable outcome. Then open the product profiles and ask whether the source supports the exact intended use. A missing independent source is a reason to verify more, not proof that a product fails.

Evidence boundary: the counts below are calculated from the public comparison records at the review date. Read the comparison method before interpreting them.

Country research purpose

What the local research is trying to find out.

Singapore is a concentrated enterprise market where AI decisions often touch financial services, ports and logistics, health, public services, and advanced manufacturing. Buyers need evidence that connects innovation with AI Verify, assurance, PDPA, resilience, and accountable human action.

The research connects search demand, official policy, sector evidence, product scope, verified review signals where available, and buyer questions. It is used to decide what deserves a page, what needs more evidence, and what should remain a watchlist item.

Read the country buyer guides · See the monthly market watch

Evidence baseline

The dataset is useful because its gaps are visible.

This is a descriptive baseline, not a claim about which vendor is best. Source type, scope, independence, market, and workflow boundaries still need buyer verification.

Profiles

30

Six products in each of five enterprise buying categories.

Independent or regulatory

12

Profiles with at least one independent-evidence or regulator source in the current dataset.

Vendor-only

0

Profiles where current public evidence is vendor-provided; these are not upgraded to evidence-backed by default.

Markets

1

The country pack keeps local policy, sector, procurement, and availability questions in scope.

Category view

Averages are context, not recommendations.

Average displayed scores include only fully assessed profiles and are rounded for readability. The category pages retain the underlying rationales and evidence gaps.

Baseline counts and average assessed evidence scores as at 2026-07-27
Category	Profiles	Average assessed score	Buyer lens
Public services and Smart Nation operations	6	3.9 / 5	Public-sector executives, service owners, policy teams, GovTech leaders, and enterprise risk owners.
Finance, risk, and compliance	6	4.0 / 5	Chief risk officers, compliance leaders, financial-crime teams, model-risk owners, and banking operations.
Trade, logistics, and manufacturing	6	4.0 / 5	COOs, port and logistics leaders, manufacturing executives, supply-chain teams, and operational-risk owners.
Health and biomedical AI	6	3.9 / 5	Health-system executives, clinical informatics, biomedical leaders, digital-health teams, and safety owners.
Customer service and workforce productivity	6	3.7 / 5	Customer executives, contact-centre leaders, HR, CIOs, service operations, and privacy teams.

What this does not show: no score establishes operational impact, safety, legal compliance, current local availability, ROI, or procurement fit. Future snapshots should add dated independent evidence, buyer interview findings, and anonymised pilot learnings when those assets are genuinely available.

Sources and further reading

IMDA AI Verify standards guidance
Model AI Governance Framework standards guidance
Singapore PDPC AI governance guidance standards guidance
Singapore National AI Strategy standards guidance
MAS Veritas and responsible AI standards guidance
Singapore Cyber Security Agency standards guidance
Singapore Ministry of Health AI guidance standards guidance
Enterprise Singapore digitalisation support standards guidance

A practical next step

Turn an evidence gap into a measurable workflow question.

Enterprise AI Group describes a 6–8 week path for a defined business process, with governance, policy management, enterprise security, and Microsoft-tenant deployment considered from the start.

Enterprise AI Group describes a 6-8 week path for a defined workflow. Timing and cost depend on scope, users, integrations, security, governance, and support. These research pages are published by Enterprise AI Group. The implementation links describe optional services; they are not product endorsements or a replacement for local Singapore diligence.

See the governed platform approach

Do not include personal, confidential, regulated, or other sensitive information in an enquiry.

Keep the useful part

Tell us what you are deciding in Singapore.

Send the Singapore workflow, market, or category you are researching. We will use it to shape the next clear buyer brief.

Useful detail: include the market, workflow, or category behind a singapore AI evidence gap.

Request a buyer brief Browse the categories

Please do not send personal, confidential, regulated, or other sensitive information.