At Align Technology, the integration of artificial intelligence into customer service operations has automated more than 60 percent of daily interactions, transforming how healthcare providers receive technical support. Sandeep Kakani, who heads customer service technology initiatives across North America and Europe, the Middle East, and Africa (EMEA) regions, is leading this transformation.
The AI-powered chatbot system, developed under Kakani’s direction, processes over 10,000 customer inquiries daily, reducing response times from hours to minutes. This automation has generated cost savings equivalent to 50 full-time positions while maintaining service quality metrics above 95 percent.
From Research Lab to Enterprise Innovation
Kakani’s path to enterprise innovation began at Eastern Michigan University’s Center for Adaptive Technology in Education (CATE), where he developed solutions for students with disabilities. As a graduate research assistant, he created adaptive computing systems that served over 500 students annually.
This experience shaped his later work at United Health Care’s Optum division, where he led the development of the Arkansas Independent Assessment application. The platform streamlined disability assessments for thousands of residents, reducing processing times by 40 percent.
“My early work with adaptive technology taught me that innovation must serve real human needs,” Kakani says. “This principle guides our current AI implementations at Align Technology.”
Technical Architecture Meets Business Impact
The transition from Cisco to Twilio for contact center operations marked a significant technical achievement, with the new cloud-based infrastructure processing over 100,000 customer interactions monthly across 15 countries. Machine learning algorithms now analyze customer sentiment in real time, automatically routing complex cases to specialized support teams. This system has improved first-call resolution rates by 35 percent and reduced escalations by 45 percent.
Implementation of automated ticket prioritization through Salesforce Service Cloud has transformed case management efficiency. The system processes 250,000 cases annually, using AI to categorize and route tickets based on complexity and urgency.
“By letting AI handle routine queries, our specialists can focus on complex cases requiring human judgment,” Kakani explains. “The data shows this hybrid model delivers better outcomes for healthcare providers and patients.”
These improvements have contributed to measurable business results, with customer satisfaction scores increasing from 85 percent to 92 percent since the system’s implementation in 2023. The CIO 100 Award recognized Kakani’s innovations in 2023, specifically citing the measurable impact of AI implementation on enterprise operations. The project also earned multiple Stevie Awards for customer service innovation.
The success of these implementations has influenced industry standards, with similar AI-driven support systems now being adopted by other medical device manufacturers. According to industry analysts, AI-powered customer service in medical devices is projected to grow by 35 percent annually through 2026.
Educational Access and Innovation
Kakani’s background includes completing his education entirely through scholarships, from early schooling through his master’s in information systems. This experience sparked his interest in developing accessible technology solutions.
“Scholarship support showed me how removing barriers creates opportunities,” Kakani notes. “We apply this same principle when designing customer service systems – making support accessible and efficient for all users.”
His team continues to refine the AI systems, recently introducing multilingual support capabilities that handle queries in 12 languages. The platform maintains 99.9 percent uptime while processing thousands of interactions daily across multiple time zones.
The measurable results of these implementations demonstrate how AI can enhance enterprise customer service while maintaining high standards of support in regulated industries. As similar systems become industry standard, Kakani’s work provides a documented case study in successful enterprise AI implementation.
Photo credit: Sandeep Kakani
