What challenges did Blackboard face before AI implementation?

Blackboard’s legacy on-premises contact center had to scale to more than eight million inbound and outbound interactions annually. Agents were overloaded with repetitive questions about logins and financial aid status. The company wanted to improve consistency, speed, retention support, and proactive student outreach.

What was the impact of the AI solution?

The article says the new approach will help students get answers faster. It is expected to reduce burden on staff by offloading repeatable questions. Blackboard expects to use sentiment and propensity modeling to improve retention and engagement. The article mentions early positive feedback from clients, but no quantified business outcome is reported.

Source

Evidence: Low25/100

Blackboard launches omnichannel student services transformation with Amazon Connect (Amazon Q in Connect)

Use case typeCustomer support automationUpdated Jun 13, 2026

Blackboard, a higher education technology company, is modernizing its Student Success services with an omnichannel cloud contact center. The solution uses Amazon Connect for voice, text, chat, and IVR, Amazon Q in Connect for real-time agent guidance, and Amazon Connect Contact Lens for analytics and sentiment analysis. Blackboard supports student services such as enrollment, financial aid, course registration, technical support, and other college support workflows across more than 2,000 institutions.

Organization: Blackboard
Industry: Education
Location: United States
Published: February 2025

Reported outcomes

Strategic outcomes

Speed & agilityHelped students get answers fasterCost efficiencyReduced burden on staffCustomer experience & trustImproved retention and engagement supportNew product / capabilityEnabled omnichannel student support

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Blackboard
Provider: AWS
Maturity: Unknown
Linked source: AWS Public Sector Blog

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 5

1Customer Service Automation
2Contact Center Transformation
3Agent Assist

Blackboard’s legacy on-premises contact center had to scale to more than eight million inbound and outbound interactions annually.
Agents were overloaded with repetitive questions about logins and financial aid status.
The company wanted to improve consistency, speed, retention support, and proactive student outreach.

Modernize the student support function with Amazon Connect as an omnichannel cloud contact center.
Let students use chatbot, SMS/text messaging, and IVR for routine questions, with escalation to agents for complex issues.
Use Amazon Q in Connect to give agents real-time guidance and recommended actions from knowledge bases.
Use Amazon Connect Contact Lens to analyze conversations, surface sentiment trends, and help identify at-risk students for proactive support.

Technologies

Amazon Connect Amazon Q in Connect Amazon Connect Contact Lens

The article says the new approach will help students get answers faster.
It is expected to reduce burden on staff by offloading repeatable questions.
Blackboard expects to use sentiment and propensity modeling to improve retention and engagement.
The article mentions early positive feedback from clients, but no quantified business outcome is reported.

Sources & evidence1

Evidence: Low25/100Evidence strength