• The Next Gen Call Center

  • 著者: Tomato.ai Inc
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The Next Gen Call Center

著者: Tomato.ai Inc
  • サマリー

  • The Next Gen Call Center interviews leading subject matter experts to discuss the most important trends, technologies, and best practices shaping the call center landscape.
    © 2024 Tomato.ai, Inc
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あらすじ・解説

The Next Gen Call Center interviews leading subject matter experts to discuss the most important trends, technologies, and best practices shaping the call center landscape.
© 2024 Tomato.ai, Inc
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  • Top Priorities for Call Center Executives
    2024/10/16

    AI is transforming call centers by automating routine tasks, allowing agents to focus on deeper, human connections. The key to success is balancing innovation with the irreplaceable value of human touchpoints.


    In our most recent podcast episode of the Next Gen Call Center, we interview Asli Uysal, VP of Enterprise Transformational Accounts at Avaya. Avaya is a global leader in customer experience solutions, delivering contact center and unified communications platforms trusted by over 90% of Fortune 100 companies, including Apple, AT&T, Dell, and CVS Health. With over 20 years of experience in the contact center industry, Asli leads strategic initiatives that transform enterprise customer engagement through innovative, AI-powered solutions.

    Key Takeaways:

    AI + Human Touch. Asli highlighted that while AI is transforming call centers, it’s not about replacing humans. The human connection is more valuable than ever. AI should enhance—not replace—the experience, especially by automating low-value tasks so agents can focus on what really matters: human-to-human interaction.

    Flexibility is Key. Companies don’t have to fully dive into the cloud or rip and replace everything. Asli shared how Avaya is pushing for hybrid solutions that bring innovation without disrupting existing infrastructures.

    Art Meets Technology. Asli’s unique background in both art and tech allows her to see technology solutions as a composition of building blocks—an approach that fuels creative problem-solving. It’s not just about tech; it’s about how it all fits together.

    The AI Trap. Poorly implemented AI can actually drive customers away. Asli shared how some AI systems end up pushing customers to expensive human channels—unintentionally creating more costs.

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    47 分
  • Call Center AI, Beyond The Hype
    2024/09/04

    Artificial intelligence (AI) is revolutionizing the call center industry—but is it truly driving transformation, or is it just another buzzword? As with most advancements, the reality is more nuanced.

    In this episode of The Next Gen Call Center, we talk with Ram Sundaram, Director of AI Development at Genesys. Leading a team that develops AI solutions for enterprises handling millions of customer interactions, Ram has over a decade of hands-on experience in the world of conversational AI. His journey spans from the early days of Hidden Markov Models and deep learning NLP to today’s cutting-edge LLMs and SLMs. With previous roles at Broadcom and Microsoft’s Core Speech Team, Ram offers a unique insider's perspective on how AI has evolved and what it means for the future of customer service.

    Here are some key takeaways:


    The Evolution of AI in Call Centers:
    Significant advancements in AI have taken place, from early rule-based systems to today's sophisticated language models. Staying updated on the latest developments is crucial to fully leverage AI's potential in call centers.

    The Importance of Practical AI: AI solutions must deliver real-world value, not just remain theoretical concepts. Engineering and building scalable, practical solutions that can be deployed in real environments is essential.


    The Future of AI in Call Centers:
    AI will increasingly automate routine tasks, enhance agent efficiency, and provide supervisors with better insights. There is also potential for AI to personalize customer experiences and optimize customer-agent matching.

    Challenges in Developing AI Solutions: High-quality data, skilled engineers, and a clear understanding of business problems are key to successful AI development. Continuous innovation and iteration are necessary to keep AI solutions relevant.

    Ethical Implications of AI: Ethical considerations such as privacy, job displacement, and potential bias must be addressed. Responsible development of AI solutions that prioritize ethical standards is essential.

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    52 分
  • Pioneering AI Speech Models To Transform The Call Center
    2024/08/01

    Imagine a world where call center agents can effortlessly understand customers with thick accents, and background noise becomes a thing of the past. This future is closer than you think, thanks to advancements in Artificial Intelligence (AI) and specifically, audio-based Large Language Models (LLMs). AI and audio-based LLMs are poised to revolutionize the call center landscape for enterprises and BPOs.


    In a recent interview, we had the privilege of discussing these groundbreaking concepts with James Fan, the Chief Technology Officer of Tomato.ai. Before joining Tomato.ai, James served as a Senior Manager at Google, where he played a pivotal role in developing the CCAI analytics solution and led the Google Cloud Speech Group. Additionally, James founded and successfully exited Hello Vera, a contact center start-up.

    Here are some key takeaways

    AI is not a replacement for human agents. James emphasizes that AI is designed to augment human capabilities, empowering agents to provide a more personalized and efficient service.

    Modern Call Center Challenges: Balancing cost-efficiency and customer experience remains a significant challenge for enterprises.


    Addressing the Accent Challenge.
    Tomato.ai’s technology was born from the need to bridge the communication gap caused by accents. Their solutions directly address a pain point for many call centers.

    Seamless Integration is Key. Tomato.ai integrate seamlessly with existing call center infrastructure, minimizing disruption and maximizing ROI.

    Overcoming Implementation Hurdles. Successful AI implementation requires thorough testing, phased deployment, and addressing concerns about AI’s impact on the workforce.

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    33 分

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