AWS re:Invent 2025 - Anthology boosts contact center efficiency with AI (BIZ212)

Anthology Boosts Contact Center Efficiency with AI

Anthology's Mission and Contact Center Transformation

• Anthology is an education technology company that supports students outside the classroom, primarily in higher education
• Their mission is to increase enrollment and student retention by providing comprehensive support services
• Anthology's contact center has evolved from a traditional model to handling a wide range of student inquiries, including financial aid, admissions, and more
• Over the past 5 years, Anthology has been on a journey to move their contact center infrastructure to the cloud and leverage AI and automation to transform their business model

Key Drivers for Transformation

• Improve reliability and uptime of contact center technology
• Reduce reliance on seasonal hiring spikes to handle high-volume periods
• Leverage automation and AI to handle repeatable, high-volume inquiries more efficiently
• Provide a more consistent, frictionless experience for students

Evaluating Solutions and Choosing Amazon Connect

• Anthology initially looked at traditional contact center solutions and models, but found they were still limited in their ability to drive the desired transformation
• The team considered building their own chatbot and automation solutions, but lacked the development velocity to go beyond basic, static capabilities
• When Anthology's CEO recommended exploring AWS and Amazon Connect, it shifted their mindset from a "lift and shift" approach to a true transformation
• Collaborating with AWS, Anthology was able to align Amazon Connect's capabilities with their student-centric vision and long-term goals

Implementing the Amazon Connect Solution

• Anthology took a phased, iterative approach to implementation, focusing on:
  • Minimizing risk
  • Maximizing impact
  • Ensuring adoption
• They started with the core Amazon Connect capabilities, then progressively introduced AI features like Contact Lens and agent assist
• AWS brought in a team of specialists, including professional services and a partner, to deliver an agile framework and ensure a successful deployment

Key Results and Outcomes

• Reduced wait times by 50% during their busiest season, with no escalations on wait times
• Increased accuracy of responses by 14 percentage points compared to human agents
• Reduced agent attrition by 10%, improving consistency and reducing training overhead
• Dramatically improved reliability, with only 2 unplanned outages during their peak season, compared to 12 previously
• Enabled 100% automated agent evaluations, allowing supervisors to review and optimize performance at scale

Looking Ahead: Proactive Student Engagement

• Anthology's next focus is leveraging the data and insights from Amazon Connect to proactively reach out to students before they have issues, such as with financial aid applications or password resets
• This will allow them to further enhance the student experience and reduce the burden on both students and agents

Key Takeaways

• Anthology's journey demonstrates the power of transforming a contact center with cloud-based AI and automation, rather than just lifting and shifting legacy systems
• By aligning technology decisions with their student-centric mission and business goals, Anthology was able to achieve significant operational improvements and enhance the overall student experience
• The collaborative approach with AWS, leveraging a team of specialists and an agile delivery framework, was critical to the successful implementation and ongoing optimization
• Anthology's focus on proactive student engagement, enabled by the data and insights from Amazon Connect, represents the next frontier in delivering exceptional student support