Incoming enquiry routing
Extract the relevant details from an enquiry, prepare a short summary and route it to the appropriate person for follow-up.
AI automation should move a defined task forward. GenRev helps businesses across Ontario and beyond connect recurring work, from incoming information to a useful next action. First, identify the systems, inputs and decisions involved. Then use AI where interpreting or drafting information helps, and clear rules where the next step is predictable. Human review remains part of the workflow when an uncertain output or sensitive decision needs a person.
Explore the approachWhen AI automation is a good fit
Start when you can name the workflow, its owner and the result it should produce. For example, a new enquiry might need a summary, an assigned owner and an internal task. AI automation can connect those steps, but inconsistent inputs or unclear ownership need attention first. If the process varies from person to person, an audit or SOP review can define it before a build begins.
01
Workflow definition
Map the trigger, required inputs, steps, outputs and ownership for one agreed process.
02
System connections
Assess how information can move between the tools already involved, including access requirements and any integration limits.
03
AI automation rules and review points
Define where the workflow can classify, summarize or draft information, and where fixed rules or human decisions are needed.
04
Review and exception handling
Specify what happens when information is missing, an output is uncertain or a step fails.
05
Testing the workflow and handover
Check representative inputs, confirm the intended outputs and document how the workflow is used and maintained.
What AI automation can include
The AI automation scope follows the agreed process, systems and review requirements. It can include:
- An agreed workflow map and implementation scope.
- The configured automation and any agreed system connections.
- Documented review points, exception paths and operating responsibilities.
- Test scenarios, handover notes and a plan for evaluating the workflow after rollout.
Picture the
possibilities.
These AI automation scenarios illustrate how a workflow can combine rules, AI assistance and a person’s judgment. The final scope depends on your systems.
Client onboarding
Use an approved client record to create a task checklist, flag missing information and prepare an internal handoff.
Recurring reporting
Bring together agreed data sources and prepare a draft status summary for a team member to check before sharing.
Plan an AI automation project
Bring representative inputs and the result each should produce. This makes AI automation testing more useful than a demonstration using only ideal examples.
What shapes the project and cost
The implementation scope depends on the number of systems involved, the condition of the source information and the decisions the workflow must handle. Existing integrations may support a straightforward connection; restricted access or inconsistent records can require additional work. Testing effort grows with the range of exceptions and review requirements. The proposal should distinguish the initial build from software charges, ongoing monitoring and later changes, with responsibilities agreed before work begins.
What we’ll need from you
- A walkthrough of one recurring workflow, including its trigger, owner, desired output and current manual steps.
- Representative inputs and expected outputs that you are permitted to share, including incomplete or unusual cases.
- The systems involved, their available integration options and the decisions that must remain with a person.
How the delivery is checked
- Run the agreed test inputs through the workflow and record whether each produces its expected output or review request.
- Demonstrate how missing information, failed connections and uncertain outputs reach the designated person instead of silently proceeding.
- Confirm that the workflow owner receives operating instructions, access responsibilities and a documented way to pause the automation.
A useful reference
NIST’s framework offers a useful reference for considering trustworthiness when designing, using and evaluating an AI system.
NIST AI Risk Management FrameworkAI & workflow automation questions.
Do we need to replace the software we already use?
Not necessarily. The starting point is to review your current tools, available integrations and access requirements. The scope should make any limitations or proposed software changes clear before implementation.
Does every automated step need AI?
No. Predictable steps are often better handled with explicit rules. AI can help when a step involves interpreting text, classifying information or preparing a draft. The workflow should make that distinction clear.
How will we know whether the automation is working?
Agree on a baseline and a small set of measures before rollout. Depending on the workflow, those might include completion time, manual touches, exception frequency and output accuracy. Review the results against the original scope.
What to Automate First: A Practical Workflow Prioritization Guide
Choose what to automate first by comparing recurring effort, process clarity, data readiness and error costs. Define a focused pilot before you build.
AI Automation Costs and ROI: How to Build a Useful Business Case
Understand AI automation costs and ROI: compare setup, subscriptions, review time and recovered capacity to build a practical business case for your team.
How to Document a Process Before Automating It
Learn how to document a process before automation. Define inputs, decisions, exceptions and ownership, then test your SOP with a worked lead-assignment example.