How Amelia Conversational AI outperforms Large Language Model applications in addressing customer service challenges.
Generative AI continues to be one of the hottest topics of 2023. By now, many of us have discussed the impact of this technology with friends and family over dinner, and with colleagues at the office.
While it is fascinating that Large Language Model (LLM) applications can generate song lyrics and ten-page essays from a few simple prompts, the hype around this technology can make it difficult for business leaders to cut through the noise and understand where AI will drive the most value.
In a recent article from Harvard Business Review, CEO and co-founder of filtered.com Marc Zao-Sanders and Chief Learning Officer of Cornerstone Marc Ramos explore a simple yet effective framework for helping business leaders understand where to deploy generative AI. The framework has two variables: Risk and Demand:
“On risk, how likely and how damaging is the possibility of untruths and inaccuracies being generated and disseminated? On demand, what is the real and sustainable need for this kind of output, beyond the current buzz?” (source)
The top left quadrant of their framework includes use cases that are low on risk and high in demand, such as marketing, copyediting, ideation, and rapid design and reviews, and the authors urge business leaders to deploy these use cases first.
While creative use cases for AI are astounding, it is vital that one important AI use case does not get lost amongst the hype: customer service. There is an urgent need for better customer experiences across all industries. As endless call center queues and disconnected systems continue to cause customer satisfaction to plummet and employee burnout to rise, there is a tremendous demand for AI to step in and transform customer experiences.
Customer service use cases are not included in the generative AI framework from Zao-Sanders and Ramos – and understandably so. Considering that many high-profile generative AI tools have been caught providing biased, incorrect and/or aggressive responses, customer-facing AI use cases may appear risky to some business leaders.
However, this “risk” lessens considerably when deploying a Conversational AI solution from a Trusted AI partner like Amelia. Amelia Conversational AI does not act or provide answers to customer questions that are beyond its training. Instead, Amelia learns to replicate companies’ best trained and most successful employees, which drastically reduces risk while simultaneously improving customer satisfaction.
In addition, while Amelia utilizes generative AI technology to deliver immediate responses to customer requests, this capability is coupled with neuro-symbolic training – which combines machine learning with symbolic logic – to ensure that customers receive answers and results they can trust.
Amelia Conversational AI also seamlessly connects with companies’ existing enterprise systems, tools and platforms, enabling Amelia to do more than simply converse. With this capability, Amelia delivers personalized service, fully resolves customer requests and coordinates information across all enterprise systems, helping to increase customer satisfaction and improve operational efficiency.
Amelia Conversational AI outperforms LLM applications in alleviating the strain on organizations’ customer service operations, and many leading brands are already reaping the benefits, including:
- Visionworks: Amelia Conversational AI for Contact Centers (read this story)
- Aveanna: Amelia Conversational AI for Employee Services (tune in to this podcast)
- Resorts World Las Vegas: Amelia Conversational AI as a Digital Concierge (watch this seminar replay)
This is undoubtedly one of the most exciting times for AI innovation, and the use cases and opportunities for this technology are seemingly endless. However, as AI tools and use cases continue to proliferate, organizations will need to be diligent about investing in AI platforms that drive true business value – and our team at Amelia will be right there to help.