1. Repeated data entry
Look for information typed into two or more systems. Record how often it happens, who owns the information and what errors occur. Sometimes an integration or a better form is enough; AI may not be needed.
2. Quote and proposal preparation
Review where staff gather inputs, check prices, reuse descriptions and request approvals. Standard templates and clear handoffs can improve consistency before any AI-assisted drafting is introduced.
3. Customer inquiries and follow-up
Map common questions, response delays and escalation paths. AI-assisted drafts may help, but customer-facing answers should be checked for accuracy and sensitive information.
4. Document review and routing
Observe how invoices, forms, requests and supporting documents arrive, are categorized and reach the right person. Define exceptions and approvals before considering extraction tools.
5. Reporting and status updates
Identify reports rebuilt manually from spreadsheets or multiple applications. Agree on reliable data definitions and ownership before automating a dashboard or narrative summary.
Start by measuring one workflow: volume, time spent, error rate and business impact. Compare simple process changes with automation and AI options. A short online Process Scan can help start the conversation; a paid Process Review examines operations in more depth.
Related: AI consulting in Ontario · AI governance · Process Review