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Case Study: AI-Powered Skills-Based Hiring Transforms Customer Care Recruitment

joseph cole

Updated on September 11, 2025

Case Study: AI-Powered Skills-Based Hiring Transforms Customer Care Recruitment

joseph cole

Updated on September 11, 2025

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TL;DR

One of the world’s largest banks partnered with Pontoon and Glider AI to modernize hiring for its high-volume customer care program. Initially, AI-powered skill assessments improved candidate alignment with role requirements. Later, persistent in-person interview no-shows slowed the process. By adopting a full AI-powered, skills-based hiring strategy—combining targeted assessments, supplier alignment, and on-demand video interviews—the bank reduced time-to-offer by two business days, saved hundreds of recruiter hours, and successfully scaled the model across business units.

The Challenge: Skills Gap and Interview Inefficiencies


The client needed to fill hundreds of customer care roles each year, but the process was struggling:

  • Skills mismatch: Too many applicants lacked the customer service and problem-solving skills the roles required.
  • In-person interview no-shows: Managers wasted time on interviews that were often rescheduled or abandoned.

The inefficiencies slowed hiring and negatively impacted the candidate experience.

The Solution: AI-Powered Skills-Based Hiring


With Pontoon and Glider AI, the program evolved into a streamlined, skills-first hiring model:

  • Targeted skill assessments: AI-powered assessments measured real-world customer care abilities, ensuring stronger candidate-role alignment.
  • Supplier consistency: All suppliers were required to adopt Glider AI, while an additional supplier was onboarded to expand candidate reach.
  • Ongoing calibration: Bi-weekly meetings kept skill requirements and market dynamics aligned.
  • Video interviews at scale: After passing assessments, candidates completed structured video interviews, giving managers flexible, on-demand access to candidate responses.
  • Personalized candidate experience: A custom welcome video filmed by client managers made the process more engaging and authentic.

By embedding AI-driven assessments and interviews into one connected process, the client created a true skills-based hiring strategy.

The Results: Faster, Fairer, Scalable Hiring


The new approach delivered measurable outcomes:

  • 277 in-person interviews eliminated per year → saving recruiters and managers hundreds of hours.
  • Time-to-offer reduced by 2 business days (from 17 to 15).
  • Improved retention by aligning hires to verified skills.
  • Expansion into new business units: Another division adopted the model, onboarding 162 customer care representatives with release-to-offer averaging 11 days.

Client Feedback

During the past year, we have seen tremendous improvement in the onboarding process by working with Pontoon. The implementation of AI interviewing has resulted in an increase in applicants and a reduction in the time required to review and select candidates. We’ve also coordinated for improved communication with our vendors and revised the referral process, allowing us to focus on quality candidates and improved retention. Overall, our partnership with Pontoon has created a very successful and streamlined process.

— Sr. Supervisor, Customer Care

The Takeaway: A Scalable Model for Enterprise Hiring


For one of the world’s largest financial institutions, shifting from a traditional process to AI-powered, skills-based hiring created faster hiring cycles, stronger candidate alignment, and improved retention. By combining skill assessments, supplier consistency, and video interviews, the organization built a scalable model now expanding across multiple business units.

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