Raffles Consulting Services
Use a 60-day AI solution trial to test one workflow, data controls, adoption and measurable value before a paid deployment decision.
A 60-day AI solution trial is long enough to test a focused workflow, but too short for unfocused experimentation. Decide the business problem, data boundary, owner, success threshold and exit route before access begins. Otherwise the trial can produce enthusiastic demonstrations without a reliable deployment decision.
The useful output is a scored recommendation: stop, extend under defined conditions or proceed to a controlled implementation.
Understand the current support context
The [SMEs Go Digital Day 2026 keynote](https://www.mddi.gov.sg/newsroom/keynote-address-by-minister-josephine-teo-at-smes-go-digital-day-2026/) says IMDA has assembled a list of 100 AI solutions across business functions. It also announces a Tech Bridge Programme offering structured support and complimentary 60-day access to market-proven tools in sales management, business analytics and market intelligence.
The same keynote describes a Slack AI Launchpad for 1,000 SMEs, with up to 60 days of complimentary use and onboarding to design at least one AI-enabled workflow. These initiatives are not evidence that every listed tool fits every company.
Check the live programme terms, provider conditions, eligibility and data arrangements before participating. Complimentary access can reduce trial cost, but it does not remove implementation, integration, training or later subscription cost.
Select one decision-worthy workflow
Choose a process with a clear user, repeatable input and measurable output. Examples might include sales-call summarisation, product-query drafting, management-report preparation or market-intelligence classification. Avoid starting with the broad goal of using AI across the company.
Map the current process. Record volume, time, error, delay, rework and control points. Identify decisions that must remain with a person. The baseline lets management judge whether the trial improves work rather than merely changing the interface.
Exclude high-risk data or decisions unless the company has suitable governance, security and professional review. A trial is not permission to upload client documents, employee data, trade secrets or regulated information into an unassessed service.
Complete a data and vendor check
Ask what data the tool receives, where it is processed, how long it is retained, whether it trains provider models, which subprocessors are involved and how access is controlled. Review contractual terms, export options, deletion, incident response and service continuity.
Test identity and role design. Use named accounts, least privilege and an approved workspace. Do not share one login across the team. Record integrations and API permissions so they can be removed if the trial stops.
The IMDA artificial-intelligence resource page includes the GenAI Playbook and governance materials for enterprises. Use them as starting points and obtain appropriate legal, security or regulatory advice for the company’s actual risk.
Define the scorecard before launch
Use a small set of weighted measures. A practical scorecard can cover task quality, time saved, rework, user adoption, control effectiveness, data risk and lifetime cost. Define how each measure is collected and who validates it.
For example, management might require acceptable output in 90% of a representative test set, at least 25% less handling time after review, no material data-control exception and a two-year cost below an approved ceiling. Those figures are an illustration, not a recommended universal threshold.
Include a comparison group or before-and-after sample where practical. A trial based only on the most successful prompts will overstate value. Keep failed cases and human corrections because they show where the workflow needs redesign.
Run the trial in short cycles
Divide the 60 days into setup, baseline, controlled use, improvement and decision. Train users on the chosen workflow, data rules and escalation. Hold weekly reviews with the process owner, security lead and affected employees.
Record prompts or configurations that materially change the result. Track provider incidents, model changes and unsupported edge cases. If the tool creates customer-facing or financial content, require the agreed human review before use.
Do not let a free trial become an unapproved production dependency. Mark outputs and integrations as temporary until the deployment decision is made.
Decide the exit before the last day
Prepare the recommendation during the final two weeks. Compare the scorecard with baseline, total cost, integration effort, workforce effects and alternatives. State limitations and the conditions needed for scale.
If the company stops, export permitted records, remove integrations, revoke accounts and request deletion under the contract. If it extends, define the unanswered question and a new end date. If it proceeds, approve ownership, budget, monitoring, incident response and staff training.
Our enterprise AI transformation guide addresses larger-scale readiness. The business support decision guide places AI support beside other investment routes.
A 60-day AI solution trial succeeds when it produces a trustworthy decision, not when every participant keeps the tool. The scorecard should show whether one real workflow became better, safer and economically sensible enough to justify the next commitment.
Include workforce evidence
Ask users which tasks improved, which controls became harder and where the tool changed judgment or workload. Record training time, workarounds and the skills needed for safe use. A time-saving result can be misleading if supervisors spend more time correcting outputs or employees create shadow processes.
Share the final decision with affected teams. Explain what will stop, continue or change and who owns support. This closes the trial as an organisational decision, rather than leaving individual users to keep or abandon the tool without a common operating standard.
Retain a short limitations register for failure cases, data exclusions and provider dependencies. If the tool proceeds, convert unresolved high-risk items into implementation actions with owners and dates. If it stops, keep the lessons without retaining unnecessary trial data or access. Review that register before any wider rollout.