Raffles Consulting Services
Choose one Slack AI Launchpad workflow with a clear business need, data boundary, human owner and sixty-day success test.
The Slack AI Launchpad is most useful when a company chooses one bounded workflow that staff understand. MDDI says participating SMEs will receive up to sixty days of complimentary Slack Business use and onboarding support to design and implement at least one AI-enabled workflow. The trial should test business value, not chase the largest possible automation.
Find a repeated task with a real owner
Start with work that occurs often, consumes visible time and has a named process owner. Examples may include routing internal requests, drafting a meeting summary, finding an approved policy or preparing a structured follow-up list. Avoid a vague objective such as improving productivity across the company.
Observe the current process for one week. Count volume, waiting time, rework, missed handoffs and exceptions. Ask staff where judgment is required. The baseline lets the team decide whether the trial helped and prevents a polished demonstration from replacing evidence.
Define the workflow boundary
Write the trigger, inputs, actions, outputs and stopping conditions. State what the system may read, draft, classify or recommend. State what it must not send, approve, delete or change without a person. Keep the first version narrow enough to inspect every important result.
The SMEs Go Digital Day 2026 keynote presents the programme as help to implement one workflow that addresses a real business need. That language supports a focused trial, not a claim that every Slack process should become agentic.
Set the data boundary
List the channels, files, messages and connected systems the workflow may access. Exclude client, employee, financial or legal records unless the use is necessary, approved and properly protected. Test with representative but minimised data. Record retention, permissions and how access will be removed after the trial.
Check whether prompts or outputs may contain confidential information. Staff should know where the tool is operating and when they are interacting with an AI-enabled feature. Use existing security and privacy processes rather than creating an informal exception for a short pilot.
Keep human responsibility visible
The IMDA agentic AI framework material emphasises meaningful human accountability and clear user information. Name the person who reviews outputs, resolves exceptions and can pause the workflow. The owner needs enough context to challenge a result.
Set approval points based on consequence. A draft summary may need a quick factual review. A message to a customer, payment instruction, personnel decision or legal statement needs stronger control and may be unsuitable for the first trial. Do not confuse a person clicking approve with a meaningful review.
Choose success measures
Use a small set of measures: completion time, handoff delay, correction rate, missed items, user effort and serious exceptions. Add a quality sample reviewed against a fixed standard. Record the number of cases, because a percentage based on a few easy examples can mislead.
Set minimum and stop thresholds before launch. For example, the workflow may need to reduce waiting time without increasing factual corrections, and any unauthorised external action may stop the trial. Keep financial savings as an estimate unless the company can trace them to actual work.
Run the trial in stages
Begin with observation or draft-only use. Compare outputs with normal work, then allow limited actions after the owner is satisfied. Include difficult examples, missing information and conflicting instructions. A workflow that succeeds only with perfect inputs is not ready for routine use.
Use the sixty-day AI trial scorecard for a broader trial record and the agentic AI approval guide for approval design. Those guides remain useful after the complimentary period because production decisions need their own cost, security and operating review.
Decide what happens after sixty days
Choose among stop, redesign, continue as a controlled pilot or move to production. Record licence cost, support needs, integration work, staff ownership and remaining risks. Remove access and exports if the company stops. Do not let a free period become an unmanaged subscription or permanent shadow process.
If continuing, update procedures and staff training. Retain a change log and review the workflow after data, channels, roles or model behaviour changes. Business ownership should remain clear even when a vendor or consultant helps with configuration.
One useful workflow is enough for the first Launchpad test. A narrow boundary, honest baseline and named human owner will teach the company more than a broad automation that nobody can properly review.
Score candidate workflows before onboarding
Use five factors: frequency, time lost, error cost, data sensitivity and ease of verification. Score each from one to five and write one sentence of evidence. A high-frequency, low-risk workflow with an obvious correct output is usually a better first experiment than a rare executive task. Examples can include turning an approved meeting note into assigned actions, summarising a permitted project channel or drafting a status update from confirmed records.
Exclude workflows that require unrestricted access to identity data, health information, privileged advice, bank details or unverified customer records. Also exclude decisions where staff may accept a fluent answer without checking it. The first use case should have a human owner, a clear source boundary and a simple way to compare the output with the original record.
Run a controlled sixty-day learning cycle
Write the baseline before enabling the workflow: number of cases, minutes per case, common errors and current reviewer. During the trial, record who used the workflow, what source material was allowed, how outputs were checked and why exceptions occurred. Measure useful adoption rather than message volume. Stop or narrow the experiment if confidential data is exposed, accuracy falls or review time cancels the saving.
At the end, decide to adopt, redesign or stop. An adoption decision should name the process owner, approved data sources, access controls, review step, training requirement and monthly metric. A stop decision is still useful if the evidence shows that the workflow is too risky or too small. The objective is a governed operational improvement, not a demonstration that every team must use AI.