Practical engineering guide · 14 September 2026
AI deployment readiness checklist for Irish teams
An AI demo becomes a business system when it works with your data, fits the workflow and has people responsible for its operation. Use this checklist before scoping an implementation or approving a production launch.
How to use the checklist
Choose one workflow and review each row with its owner. Mark it ready, needs work or not applicable; attach the evidence and a due date. A total score can hide a critical missing dependency, so assess each launch requirement individually. This is a planning aid, not a certification or substitute for project-specific security and legal review.
| Check | Suggested owner | Evidence to collect |
|---|---|---|
| Workflow and value | Business owner | Name the users, current process and one outcome to improve. Record a baseline such as completion time or exception rate, with a measurement period. |
| Scope and ownership | Product and delivery leads | Define the first release, what is excluded, acceptance criteria and who can approve launch. Assign an owner for each dependency. |
| Data and access | Data owner and security lead | List the sources, permissions, retention needs and approved environments. Use only the access needed for the workflow and document how it is revoked. |
| Supplier and hosting decisions | Technical and procurement owners | Record model and hosting providers, regions, subprocessors, usage limits and exit options. Identify requirements that need specialist review before delivery. |
| Integration behaviour | Engineering lead | Test authentication, rate limits, retries, duplicate events and partial failures. Specify what happens when an upstream system is unavailable. |
| Evaluation | Engineering and workflow users | Create representative normal, edge and failure cases. Agree accuracy and task-completion criteria with the people who will use the result. |
| Human review | Operational owner | Identify decisions that require approval. Define escalation, override and correction procedures, including a route for users to report a wrong result. |
| Monitoring and costs | Operations and finance owners | Track errors, latency, usage and cost per completed task. Agree alert thresholds and identify who responds outside normal operating hours. |
| Rollout and rollback | Release owner | Start with an agreed user group. Document how to pause the workflow, restore the previous process and recover from failed updates. |
| Handover | Service owner | Confirm repository ownership, runbooks, training, support responsibilities and a review date. Test that the receiving team can operate the system. |
Example: handling an incoming order
Suppose a team wants AI to extract order details from an email and prepare a record in its existing system. Test incomplete emails, conflicting product names, duplicate messages and an unavailable order API. Agree which fields a person must check before submission. Measure the whole process, including corrections, against the current workflow. A faster extraction step alone does not establish a better operational result.
What to bring to a scoping call
Bring a workflow description, the systems involved, an example using approved or anonymised data, and a list of people who can resolve access and policy decisions. Identify any hosting, procurement or data-handling constraints at the start. Your team should agree the success criteria before choosing a model or committing to a delivery date.
Need help taking a workflow into production?
Explore forward deployed engineering in Ireland for embedded delivery, or AI automation services for a defined chatbot or workflow build.
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