Government & Public Sector

Frequently asked questions

What are the main barriers to AI adoption in the public sector?

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AI for government faces three structural barriers that private-sector deployments do not: procurement rules that require competitive RFPs for software above threshold (typically $25K–$100K federally), legacy infrastructure that lacks API access, and public accountability requirements that make 'move fast and break things' politically untenable. None of these barriers is insurmountable — but they require different project structures than commercial deployments, starting with a contained pilot that can proceed under existing departmental authority before triggering a full RFP.

How do you ensure AI decisions in government are explainable and accountable?

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Accountability in AI public-sector decisions requires that every AI-assisted recommendation has a documented reasoning chain, a human decision-maker of record who signs off, and an audit trail that can be disclosed under ATIP or FOIA. We design government AI systems with explainability-first architecture: structured outputs with citation of source data, mandatory confidence scores, and a clear escalation path that keeps the human in the loop for any decision affecting individual rights or entitlements. The Directive on Automated Decision-Making (Canada) and equivalent US guidance set the floor; we design above it.

Can AI automate ATIP or FOIA processing?

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AI can automate the most time-consuming parts of ATIP/FOIA processing — document ingestion, relevance classification, redaction recommendation, and consultation routing — while keeping a human coordinator as the decision-maker of record. Departments handling 500+ requests per year typically see 40–60% reduction in analyst hours per request after full deployment. The redaction step uses AI as a proposal engine, not a final arbiter; the coordinator reviews and approves each package before release.

How does AI fit with the GC Digital Standards and Treasury Board directives?

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Canada's GC Digital Standards (design with users, iterate, use open standards, build in accessibility and security) map cleanly onto responsible AI deployment. Remolda's government engagements are structured to comply with the Directive on Automated Decision-Making, the Directive on Service and Digital, and the draft AI and Data Act (AIDA). We produce the algorithmic impact assessments, privacy impact assessments, and GBA+ reviews that federal procurement and audit require, so departments are not left to produce these in-house after deployment.

What AI use cases deliver the fastest ROI in government?

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The fastest-ROI government AI use cases are citizen service chatbots for high-volume inquiries (benefits eligibility, permit status, document requirements), document triage and routing for intake operations, and internal knowledge-base assistants for front-line staff. These avoid the complexity of automated decision-making on individual rights and can go live without a full algorithmic impact assessment. A well-scoped citizen chatbot typically goes from kickoff to production in 8–12 weeks and handles 30–50% of inbound inquiries without agent escalation.

How do you pilot AI in government without a full RFP?

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Most federal and provincial authorities allow departments to procure professional services under a standing offer or pre-qualified vendor list without a competitive RFP for work under $100K–$250K. A well-designed AI pilot fits within this envelope: 8–10 weeks, one contained workflow, a defined acceptance test, and a clear go/no-go gate before any larger commitment. We structure every government engagement to deliver a shippable pilot within the departmental authority threshold so procurement does not block innovation — the full RFP comes only after the pilot proves value.