Rhode Island Department of Labor and Training & Iowa Workforce Development: Automating unemployment contact centers with Amazon Connect and generative AI

Use case typeCustomer service automationUpdated Jun 13, 2026

Rhode Island Department of Labor and Training and Iowa Workforce Development are US public sector agencies responsible for unemployment insurance contact centers. The article describes how agencies can use Amazon Connect, Amazon Q in Connect, Contact Lens for Amazon Connect, chat assistants, outbound notifications, IVR self-service, and ML-powered workforce management to reduce call volume and improve service. It cites Rhode Island and Iowa examples to show how these capabilities support multilingual self-service and call deflection during unemployment surges.

Organization
Rhode Island Department of Labor and Training
Industry
Public Sector
Location
United States
Published
December 2024

Reported outcomes

−60%

repeat calls reducedOther quantified impact

+30%calls shifted to self-service11,000 hoursstaff hours saved+2,100%call volume increase−20%call volume deflected

Strategic outcomes

New product / capabilityEnabled 24/7 self-service supportCustomer experience & trustImproved access for vulnerable constituentsSpeed & agilityAutomated claim-status and FAQ handlingBetter decisions & insightImproved quality monitoring and documentation

Primary read

Use case focus

Showing 3 of 5

  • 1Contact Center Automation
  • 2Public Sector Service Delivery
  • 3Self-Service Automation
  • High, time-sensitive call volumes and complex claim eligibility workflows during economic downturns.
  • Limited access for constituents with language, health, or literacy barriers.
  • Excessive staff time devoted to routine inquiries and after-contact work.
  • Implemented chat assistants and a mobile-friendly claim status portal to enable 24/7 self-service.
  • Sent event-based outbound notifications via text or email triggered by claim status changes.
  • Deployed voice chat assistants to answer FAQs and automate claim-status inquiries via IVR modules.
  • Used Contact Lens analytics and generative AI post-contact summaries to reduce manual note-taking and improve quality monitoring.
  • Used ML-powered forecasting, capacity planning, and scheduling to improve staffing.
Technologies
Amazon ConnectAmazon Q in ConnectAmazon Connect Contact LensAmazon Connect Voice IDAmazon PollyAmazon Lex
  • Rhode Island deflected call volume and improved timeliness/compliance with chat assistants and outbound updates.
  • Iowa Workforce Development shifted about 30% of calls to self-service while call volume increased by more than 2,100%.
  • Iowa saved close to 11,000 staff hours in a 3-month period.
  • Connecticut Department of Labor achieved a 60% reduction in repeat calls after scheduled callbacks.
  • North Carolina's IVR claim-status module deflected 20% of call volume when the agency was receiving around 200,000 calls per day.
Sources & evidence1
Groundedness: 5/5Type: Blog PostPublished: Dec 17, 2024Publisher: AWS Public Sector BlogEvidence: VendorConfidence: Medium
Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

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