Jun 25, 2024

Leveraging Generative AI in Enhancing Customer Support- Is it worth it?

96% of consumers globally consider Customer Service as a deciding factor for their loyalty to an organization and Generative AI is leading this technological revolution.

Leveraging Generative AI for Enhancing Customer Support.


In the dynamic world of customer service, generative AI is climbing the ranks to become a pivotal element in corporate strategy and is seen as a very strong driving force for moving forward. A staggering 85% of business leaders predict that within the next two years, generative AI will be at the forefront of customer interaction. By the end of 2023, 63% of these leaders expect to have invested in generative AI applications to bolster their customer service teams. If you're navigating the customer service landscape, you might be curious about the role of AI, its implications for your career, and its overall impact on the industry. This guide is crafted to help you understand what generative AI really means and its significance in customer service.

What do we actually mean by Generative AI ?

Generative AI, a branch of artificial intelligence, specializes in creating new content, data, or outputs. It learns from existing data to produce results that mimic human-generated content, including images, text, and even music. While it may seem like a recent phenomenon, the roots of generative AI trace back to the 1950s.

Generative AI vs. Traditional AI

The term AI is often used broadly, but it's crucial to distinguish between AI and generative AI. AI refers to machines designed to perform tasks typically requiring human intelligence, such as speech recognition and problem-solving. Generative AI goes a step further, using data to create entirely new content. As AI continues to evolve, understanding the differences between machine learning, deep learning, neural networks, and large language models (LLMs) like OpenAI's GPT-3 becomes increasingly important. Put simply, the key difference between traditional and generative AI is that generative AI is able to create something new.

The Importance of Generative AI

Generative AI's potential is vast, from fostering creativity and innovation to enhancing productivity across industries. It's projected to boost business productivity by up to 40% by 2023. Its applications range from simulating real-world scenarios for research to suggesting novel molecular structures for scientific advancements. According to a report by McKinsey, Generative AI could enable automation of up to 70 percent of business activities, across almost all occupations, between now and 2030, adding trillions of dollars in value to the global economy and this number itself shows how crucial this tech is.

Generative AI's Role in Customer Service

The influence of generative AI on customer service is undeniable, with the global chatbot market expected to reach $994 million by 2024. Generative AI is reshaping customer service roles, creating opportunities for professionals to transition from traditional positions to roles like Bot Specialist or Conversational AI Specialist. AI will be so crucial for improving customer experience and create more delightful interactions with consumers that few months down the lane, we cannot expect a customer support business that does not tap into this tech

Phases of Implementing Generative AI in Customer Service

The deployment of generative AI in customer service can be broken down into three phases:

  1. Deploy: Launch conversational AI quickly by utilizing generative AI to scrape support documentation and provide answers to customer inquiries.
  2. Learn: Monitor bot analytics and insights to implement deeper integrations and increase automated resolutions.
  3. Improve: Under the guidance of a Director of ACX, delve deeper into AI chatbot strategy and leverage AI to inform business decisions.

The Advantages of Generative AI for Customer Service

Generative AI offers numerous benefits for customer service, including reducing operational costs, providing personalized recommendations, resolving inquiries at scale, and offering multilingual support. It ensures that customer insights are captured and utilized effectively, bridging the gap between CX organizations and customers.

Conclusion

Generative AI is transforming customer service, offering unprecedented opportunities for efficiency and innovation. By understanding and implementing generative AI thoughtfully, customer service leaders can harness its power to enhance the customer experience and drive business growth.


Decision pointsOpen-Source LLMClose-Source LLM
AccessibilityThe code behind the LLM is freely available for anyone to inspect, modify, and use. This fosters collaboration and innovation.The underlying code is proprietary and not accessible to the public. Users rely on the terms and conditions set by the developer.
CustomizationLLMs can be customized and adapted for specific tasks or applications. Developers can fine-tune the models and experiment with new techniques.Customization options are typically limited. Users might have some options to adjust parameters, but are restricted to the functionalities provided by the developer.
Community & DevelopmentBenefit from a thriving community of developers and researchers who contribute to improvements, bug fixes, and feature enhancements.Development is controlled by the owning company, with limited external contributions.
SupportSupport may come from the community, but users may need to rely on in-house expertise for troubleshooting and maintenance.Typically comes with dedicated support from the developer, offering professional assistance and guidance.
CostGenerally free to use, with minimal costs for running the model on your own infrastructure, & may require investment in technical expertise for customization and maintenance.May involve licensing fees, pay-per-use models or require cloud-based access with associated costs.
Transparency & BiasGreater transparency as the training data and methods are open to scrutiny, potentially reducing bias.Limited transparency makes it harder to identify and address potential biases within the model.
IPCode and potentially training data are publicly accessible, can be used as a foundation for building new models.Code and training data are considered trade secrets, no external contributions
SecurityTraining data might be accessible, raising privacy concerns if it contains sensitive information & Security relies on the communityThe codebase is not publicly accessible, control over the training data and stricter privacy measures & Security depends on the vendor's commitment
ScalabilityUsers might need to invest in their own infrastructure to train and run very large models & require leveraging community experts resourcesCompanies often have access to significant resources for training and scaling their models and can be offered as cloud-based services
Deployment & Integration ComplexityOffers greater flexibility for customization and integration into specific workflows but often requires more technical knowledgeTypically designed for ease of deployment and integration with minimal technical setup. Customization options might be limited to functionalities offered by the vendor.
10 ponits you need to evaluate for your Enterprise Usecases

At Fluid AI, we stand at the forefront of this AI revolution, helping organizations kickstart their AI journey in enhanced Customer Support. If you’re seeking a solution for your organization, look no further. We’re committed to making your organization future-ready, just like we’ve done for many others.

Take the first step towards this exciting journey by booking a free demo call with us today. Let’s explore the possibilities together and unlock the full potential of AI for your organization. Remember, the future belongs to those who prepare for it today.

Didn't find specific use-case you're looking for?

Talk to our Gen AI Expert !

Book your free 1-1 strategic call

- Outline your AI strategic roadmap and identify high-impact use cases.
- Craft an optimal data architecture, tailor models, & bring your most ambitious AI projects to life.
- Scope with simple internal pilot journey instantly in just 1-day.
- Easily Scale-to-Production, & achieve seamless integration with your existing financial systems.
- Holistic end-to-end support, insights & performance evaluation for successful journey.