AI ROI Calculator Singapore

It multiplies your workflow volume by the time saved per case and the loaded hourly cost, then subtracts build and running costs.

An AI ROI calculator turns four numbers into an annual estimate: annual cases, hours per case, loaded hourly cost and expected time saved per case. Multiply cases by hours saved, multiply that by the loaded rate, and you have a gross annual saving.

Subtract build, data, training, monitoring and internal review costs to reach net ROI.

• Use workflow records, not estimates, for volume.
• Get the loaded rate from finance - it includes CPF, benefits and overheads, not just salary.
• Validate time saved with a sample log before committing it to the business case.

The output is a planning aid, not a forecast. Paloren recommends documenting every assumption so the finance reviewer can trace each figure to evidence.

Run the calculator with your own figures. It is embedded below, and every input is editable.

AI ROI calculator (opens the full tool)

Model three scenarios on the same four inputs: annual cases, hours per case, loaded hourly cost in SGD and expected time saved. Each row is illustrative until your own data replaces it.

Beneath the table, the calculator shows a payback view: months to break even in year one, plus a simple three-year cumulative line, labeled illustrative.

Include build, data preparation, integration, training, monitoring, support and the internal time needed for review and change management.

Many Singapore business cases fail because they count only the vendor quote. A complete ROI calculation should include:

• Build and data work - scoped proposal, data preparation, integration into systems of record.
• Training and monitoring - staff enablement, quality checks, model monitoring, support terms.
• Internal review time - the hours your own team spends reviewing exceptions, approving outputs and managing change.

Paloren does not insert invented industry prices into the calculator. Use scoped written quotes and internal estimates for each line, and record the owner and evidence for every figure.

Ongoing ownership costs - retraining staff, updating prompts, maintaining integrations - belong in the model too, because they recur every year after launch.

AI strategy: S$15,400 to S$32,100 over 3 to 4 weeks.

Costs vary widely by scope. As illustrative planning ranges for Singapore engagements:

• Readiness assessment: from S$10,300 over 2 to 3 weeks.
• AI strategy: S$15,400 to S$32,100 over 3 to 4 weeks.

Big Four and global firms typically price above these bands; boutiques below. These figures are illustrative - always compare scoped written proposals that name the workflow, systems, assumptions and exclusions.

Paloren provides scoped proposals so buyers can compare on evidence rather than pitch quality.

Published Paloren prices, shown in SGD for Singapore planning. The written proposal confirms scope, billing currency, taxes and any third-party costs.

Start with one named process, measure its baseline, model scenarios with your own data and verify savings after launch.

A practical workflow looks like this:

1. Name the process - for example, invoice processing, customer enquiry triage or report drafting.
2. Record the baseline - cases per year, hours per case, loaded hourly cost, from workflow records and finance.
3. Model scenarios - conservative, expected and optimistic time-saved figures, each with its assumptions written down.
4. Scope the build - systems, fields, exceptions, exclusions, in a written proposal.
5. Verify after launch - compare actual time saved against the model and update it.

If you cannot name an owner who can approve access and review exceptions, the first step is preparation, not build. Paloren's S4 Method structures this sequence.

Any personal data used to measure or automate the workflow must be collected, used and protected in line with the PDPA.

ROI modelling often needs payroll data, customer records or staff activity logs - all likely to contain personal data governed by the Personal Data Protection Act. Practical implications:

• Confirm the purpose limitation covers AI modelling and automation.
• Minimise the fields accessed; prefer read-only retrieval where possible.
• Apply role-based access so users see only data their permissions allow.
• Document retention and correction routes for inaccurate data.

Paloren maps these obligations during discovery so the business case and the compliance position are agreed before build starts, not after.

Yes - schemes such as the Enterprise Development Grant and SkillsFuture funding for training can offset eligible AI implementation and upskilling costs.

Singapore companies can reduce net ROI costs through national support:

• Enterprise Development Grant (EDG) - supports projects that upgrade businesses, including technology adoption, subject to eligibility and scope.
• SkillsFuture - course and training support for upskilling employees, including AI literacy programmes.
• AI Singapore programmes - adoption initiatives for SMEs exploring AI use cases.

Check current eligibility criteria with Enterprise Singapore or the relevant agency, as schemes and funding levels change. Include any expected support in the ROI model as a reduction to build or training costs, but keep it clearly labelled as an assumption until approval is confirmed.

A named business owner - usually the workflow or process owner - with finance validating costs and the sponsor approving the business case.

Ownership determines whether the model survives contact with reality. Paloren recommends three named roles:

• Workflow owner - owns volume data, process records and exception review.
• Finance reviewer - owns the loaded hourly cost and validates every cost line.
• Sponsor - signs off the business case, acceptance tests and the go/no-go decision.

Each row in the model should carry an owner, an evidence source and a review date. When the person who can grant system access, approve exceptions and explain the result to others is named from day one, the estimate becomes a managed forecast rather than a spreadsheet nobody defends.