A large financial services organization sought to explore how artificial intelligence could improve efficiency and decision-making across its contact center operations. The initiative focused on two operational workstreams: Quality Management (QM) and Agent Assist (AA).

The challenge was to understand how frontline staff, managers, and technical teams currently interacted with these systems, identify workflow pain points, and design future-state experiences where AI could enhance existing operations.

We began by aligning with stakeholders on the objective: identifying where AI could improve efficiency and decision-making across contact center operations, specifically within Quality Management (QM) and Agent Assist (AA).

After defining the scope, we conducted a research-driven discovery focused on understanding current workflows, operational constraints, and opportunities for AI integration.

Stakeholder Research

• Conducted interviews with frontline agents, operational managers, and technology teams to understand day-to-day workflows and pain points
• Identified key inefficiencies, manual processes, and gaps in existing tools

Current-State Analysis

• Synthesized insights into detailed workflow maps for QM and AA
• Highlighted friction points, process breakdowns, and areas of operational complexity

AI Capability Research

• Analyzed best-in-class AI implementations across the market
• Identified practical opportunities where AI could augment existing workflows

Future-State Design & Validation

• Designed AI-enabled future-state workflows to improve efficiency and user experience
• Facilitated workshops with stakeholders to validate concepts, gather feedback, and refine recommendations

The project resulted in a set of AI-enabled future-state workflows across the Quality Management and Agent Assist workstreams.

Key deliverables included:

• detailed current-state workflow maps identifying operational friction points
• future-state process models showing where AI could augment workflows
• a set of prioritized AI implementation opportunities aligned with business goals

These findings were presented to company leadership and incorporated into the organization’s broader technology initiative roadmap.