Rapidly evolving customer expectations along with AI advancements have necessitated a transformative shift in contact centers. CTOs & CIOs face the critical task of migrating contact centers to the cloud, unlocking their potential for scalability, agility, enhanced Customer Experience (CX) outcomes, and AI readiness, while maintaining privacy and security compliances.
TechCircle, in collaboration with Ozonetel, hosted an invigorating boardroom discussion on 24th June 2023 in Udaipur, where technology leaders from various industries came together to explore the challenges and best practices associated with seamlessly transitioning contact centers to the cloud within enterprise environments. Atul Sharma, Cofounder & CTO, Ozonetel; Sudhanshu Mishra, Vice President - Business Development, Ozonetel; and Sagar Rane, VP- Sales, Ozonetel chaired the event with Shalil Gupta, CBO, Mosaic Digital & Mint, An HT Media Group company, who kickstarted the session.
During the discussion, leaders shared their experiences and knowledge, creating a collective pool of insights on leveraging the potential of the cloud to optimize contact centers, improve customer experiences, and establish future-proof, AI-powered organizations.
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According to a CIO from a prominent company, integrating artificial intelligence (AI) into digital customer platforms can significantly humanize customer experiences at scale. It can enhance the quality of life for individual customers and employees and unlocks a multitude of opportunities for businesses.
Taking this view forward, Atul Sharma emphasized the importance of identifying relevant use cases that are aligned with business priorities. There are four key domains where contact center AI can be applied effectively:
1. Customer insights: Utilize AI to comprehensively understand your customer and incorporate insights like social traits, behavior patterns, and propensity to purchase — to personalize customer engagement.
2. Augmenting customer engagement: Combine automation, machine learning-based predictions, and real-time customized propositions to support employees and enhance customer engagement during interactions.
3. Conversational interfaces: Leverage natural language processing for contextual, personalized conversations with deep integration, sentiment/emotion detection, and seamless employee engagement, enhancing customer interactions.
4. Immersive experience: Create AI-driven immersive experiences (augmented, virtual, mixed reality) to enhance customer interactions, leveraging vision, voice, and natural language capabilities for a richer product orservice experience.
An IT leader of a top firm highlighted the hurdles associated with migrating contact centers to the cloud and applying AI to customer experience (CX). The key hurdles he identified included: customer data integration, selecting appropriate technologies, proactive compliance management, and talent acquisition for effective AI adoption.
Sudhanshu Mishra addressed the key question of orchestrating AI-enabled CX transformation for business value. He emphasized that during the exploration stage,thorough planning is crucial to identify use cases and review data quality. These use case must then be enriched during the development stage,before successful large-scale deployment.
When discussing the selection of technology partners, Sagar Rane highlighted significant concerns related to AI risks. These risks encompass loss of control, lack of transparency, algorithm traceability, data security, confidential information misuse, liability, biases in machine learning models, and the absence of regulations. To cultivate loyalty, businesses must effectively prioritize honesty, trust, and integrity while addressing these challenges.
In conclusion, customer experience is a crucial competitive advantage that directly impacts business outcomes. The emergence of cloud and AI within contact centers enables businesses to optimize and personalize CX at scale. It helps them tap into higher efficiency and create higher efficacy. Achieving success requires collaboration between business and IT, ensuring that AI implementation aligns with business goals and delivers measurable value on a large-scale.