How Citi Used AI Workflow Orchestration to Elevate Customer Service & Scale Faster
In today’s banking sector, customers expect even more than quick transactions or user-friendly apps. They want support that is responsive, personal, and seamless. For global institutions like Citi, meeting that standard at scale requires more than people and policies. It demands intelligent systems working in harmony.
Citi’s roots trace back over 200 years and has a presence in nearly every corner of the globe. The company has consistently invested in digital transformation to stay competitive. Yet even giants can hit friction points, especially when legacy systems, siloed teams, and high-stakes processes collide.
One area where that friction became clear was in Citi’s forbearance program, which is a critical support system meant to help customers facing financial difficulties. While the program itself was well-intentioned, its execution was falling short of expectations.
Let’s look at how Citi addressed this challenge and how AI-driven workflow orchestration helped them go from lagging operations to lightning-fast, customer-first service delivery.
Background
The forbearance process is a lifeline for customers going through difficult times, offering temporary relief from payments and financial obligations. During periods of economic uncertainty, demand for this kind of support spikes dramatically. Citi found itself facing an influx of requests and a growing queue of unhappy customers.
Behind the scenes, multiple systems had to be checked for eligibility, and several departments had to coordinate for approval and implementation. Most of the process was manual, which meant delays were common, and inconsistencies were inevitable.
This was not just an operations issue. It was a customer trust issue. The very people who needed help the most were experiencing friction and frustration. For Citi, that reality triggered a turning point.
The Challenge
Citi’s internal teams recognized that they were working harder, not smarter. Customers were waiting up to 24 hours just to receive updates about their eligibility status. Employees were manually checking systems, copying and pasting data between applications, and relying on email to move requests through different departments.
The customer support experience had become slow, disjointed, and painful for everyone involved. The workflows were functional but rigid and were unable to scale with demand or adapt to changes in real time.
The question was clear. How could Citi maintain its reputation for service excellence while improving speed, consistency, and transparency for customers?
The Solution
Instead of adding more people or tweaking a few broken steps, Citi chose to rethink the entire process. They integrated a modern AI-driven workflow orchestration platform that connected the dots between their various systems, removed repetitive tasks, and introduced automation where it mattered most.
This was not about replacing people. It was about removing the friction between them.
Here is how the new AI-enabled system reshaped the experience:
Real-time eligibility checks were now possible by integrating data from multiple systems instantly.
Customer updates were automated and delivered within seconds, creating transparency at every step.
Repetitive manual work was eliminated, allowing support teams to focus on complex cases and human interactions.
Error-prone handoffs between departments were replaced with automated workflows that ensured nothing fell through the cracks.
By orchestrating the entire journey through AI and automation, Citi transformed a fragmented process into a smooth, intelligent system that could respond as quickly as customers needed it to.
“We reduced turnaround times in some of our most sensitive customer support programs by over 70%. That’s not just operational efficiency — that’s real impact on people’s lives.”
Outcomes & Results
The transformation was not just impressive in theory, it delivered real, measurable outcomes:
Speed: From Hours to Seconds
Customer enrollment time went from 24 hours to just three seconds. What used to involve back-and-forth emails, spreadsheet checks, and multiple approvals was now handled in the time it takes to refresh a browser.
Efficiency Gains
Manual tasks were reduced by over 50%. That meant Citi’s teams were no longer bogged down by redundant work and could instead focus on areas where their judgment and empathy made a difference.
Improved Customer Experience
Customers received timely updates, real-time clarity, and fewer surprises. This built trust, reduced call volume, and gave customers confidence that they were being heard and helped without delay.
Scalability
As demand grew, the system adapted effortlessly. The orchestration engine did not require new training or onboarding. It simply ran the workflows faster, with zero drop in quality.
Aspect
Customer Enrollment Time
Process Type
System Integration
Manual Workload
Customer Updates
Error Rate
Scalability
Employee Focus
Customer Experience
Before AI Workflow Orchestration
Up to 24 hours
Manual, fragmented
Siloed systems with limited communication
High, teams manually processing tasks
Delayed, inconsistent
Higher, manual handoffs & data entry mistakes
Difficult to scale during demand spikes
Manual repetitive tasks
Frustration, long wait times, trust issues
After AI Workflow Orchestration
Just 3 seconds
Automated, seamless
Fully integrated systems enabling real-time data sharing
Reduced by over 50% through automation
Instant, transparent, real-time
Minimal, due to automated workflows and validations
Effortlessly scales with growing demand
Freed to focus on complex, value-added customer interactions
Enhanced satisfaction, trust, and loyalty
Why Does This Matter?
What Citi achieved wasn’t just a fix for a broken program. It was a model for what modern enterprises can do when they stop patching and start reimagining. Workflow orchestration powered by AI is not just a technical solution. It is a strategic one.
It empowers teams to act faster, customers to feel supported, and leaders to scale with confidence. In industries like banking, where the stakes are high and competition is fierce, having that kind of edge makes all the difference.
Key Takeaways
Here are some key takeaways that others can learn from Citi’s transformation:
Start with the customer journey. Fixing internal processes is only valuable if it improves the experience on the outside.
Think systems, not silos. Orchestration works best when data and actions flow across departments without friction.
Automate with purpose. Not every task needs AI, but the right ones benefit enormously from speed and consistency.
Measure what matters. Look at outcomes like time to resolution, customer satisfaction, and scalability, not just cost savings.
Citi’s use of AI workflow orchestration is part of a broader movement toward what many are calling “invisible operations”; processes that run smoothly in the background, quietly elevating customer experience without drawing attention to themselves.
The future of banking, and business in general, will not be won through flashy tools or one-off automations. It will be shaped by how well companies integrate intelligence into every corner of their workflows, creating a seamless, responsive system that can evolve alongside customer needs. And as Citi has shown, it is not just possible. It is already taking place.
Keyword Profile: Citi Bank, AI Workflow Orchestration, Scalable Automation Solutions, Data Management, No-Code, Workflow Automation, Agentic AI, AutoML, Machine Learning, AI, DataPeak by FactR