How to Design Agentic AI Workflows for Government and Public Services in Dubai
A practical design for permit, licence and citizen-service case preparation using bounded AI agents, explicit controls, reliable evidence and staged deployment for Dubai government and public services.
Where agentic workflows fit in Dubai government and public services
A public-service case can require identity, property, eligibility, payment and specialist evidence from several authorities. Difficult cases contain conflicts or exceptions that a standard form cannot resolve. An agentic workflow is useful where the next step depends on evidence that cannot be handled economically through one fixed route. Stable rules, approval limits and mandatory controls should remain deterministic.
A strong starting workflow: permit, licence and citizen-service case preparation
The workflow should receive and classify the request, verify identity and jurisdiction, collect required evidence, retrieve the applicable rule, identify conflicts or missing information, prepare the case, obtain the authorised decision and communicate the outcome. This is an application design, not a claim about a completed client engagement. The business should narrow the first pilot to one population, route and accountable owner.
Choose the architecture deliberately
A case agent can retain the citizen request and deadlines. Registry and policy agents can retrieve approved evidence. A workflow engine should control statutory steps, while the responsible officer retains formal judgement and discretion.
Prepare the evidence and knowledge
The workflow needs applications, identity and registry records, policy versions, payments, specialist reviews, prior decisions, appeals and citizen feedback. Each source should have an owner, definition, effective date and access rule. The workflow must distinguish retrieved evidence, deterministic calculation, model inference and human judgement.
Keep authority and controls visible
The workflow must not make a statutory judgement, change eligibility or conceal the source supporting a recommendation. The public authority remains accountable for the decision.
Test the complete trajectory
Use historical and constructed cases covering normal work, missing information, conflicting evidence, unusual combinations, tool failure and attempts to bypass policy. Test retrieval, routing, tool calls, approvals and downstream effects. Compare the agentic design with the present process and with a simpler controlled workflow.
Deploy in stages
Begin with historical replay and shadow operation. Move to restricted production with limited cases and actions, then expand only when evidence supports the current boundary. Log source versions, handoffs, tools, approvals and final outcomes. Maintain a manual route and tested rollback.
Measure operating value
Useful measures include complete cases at first review, time to accountable ownership, overdue work, officer correction, appeal, service accessibility and citizen effort. Report performance by route and material subgroup rather than relying on one average. Include model use, integration, human review, monitoring and incident costs in the value case.
How Marketways approaches the design
Marketways maps the current work, selects the least complex suitable architecture, defines data and tool contracts, designs human authority and evaluates the complete workflow. The work connects Agentic AI Design and Deployment with Process and Workflow Analysis and Redesign and AI and Model Risk.