Short answer
Do not use AI simply because a workflow is annoying. Use AI only when it improves a real decision, saves meaningful time, improves access to knowledge or reduces process friction without adding unacceptable risk.
Use rules-based automation instead
If the inputs, rules and outputs are stable, a conventional automation is usually easier to test, explain and maintain than an AI agent.
- Invoice routing with clear approval thresholds.
- Standard CRM field updates from known form data.
- Scheduled reports with fixed calculations.
- Notifications triggered by a clear status change.
Fix the process first
AI will not rescue a workflow that has no owner, unclear data definitions or contradictory approval rules. Clean process design often creates value before any model is introduced.
Be careful with poor data
If documents are outdated, systems disagree or ownership is unclear, AI can make unreliable answers look confident. Data quality should be checked before production use.
Keep humans accountable
AI should not make sensitive, irreversible or high-impact business decisions without human review. Approval points, logs and escalation paths matter more than impressive demos.
Sources and further reading
For higher-risk AI work, review guidance from the ICO, NCSC, NIST AI Risk Management Framework and relevant vendor documentation before implementation.