AI & Automation
Automating agency workflows with integration and AI
Where automation removes manual steps between systems, and where AI extends it to tasks that used to need a person to read.
Much agency work is moving information between systems and people: a form arrives, someone reads it, enters it, routes it, and notifies someone else. Integration automates the structured steps. Language models now extend automation to steps that required reading and judgment, provided a person remains responsible.
The automation ladder
- Integration. Data flows between systems through APIs without re-keying.
- Workflow. Rules route items, assign tasks, and send notifications.
- Document understanding. AI extracts data from unstructured inputs such as PDFs and emails.
- Classification and triage. AI sorts and prioritizes items by content, with confidence scores.
- Drafting. AI prepares responses, summaries, or records for a person to review.
- Assisted decisions. AI recommends, a person decides, and the decision is logged.
Each rung adds value and risk. Most agencies gain the most from the first three.
Examples
- Service requests classified, routed to the right department, and acknowledged automatically
- Invoices captured, matched to purchase orders, and queued for approval
- Public comments summarized by topic for a staff report, with links to the originals
- Permit applications checked for completeness before a planner sees them
- Records requests triaged by the systems likely to hold responsive records
Guardrails
- A person accountable for every consequential outcome
- Confidence thresholds that route uncertain items to review
- Full logging for audit and public records
- Data handled within approved boundaries
- Measurement of accuracy and of time saved
What to avoid
Automating a broken process. Map the process first, remove unnecessary steps, then automate what remains.
Procurement
Workflow and integration platforms, document AI, and language model services can be bought separately or together. Require APIs, logging, and data terms regardless.
Where HQT fits
Process mapping, integration, workflow implementation, AI components with review workflows, and the measurement that shows what changed.