Experience Management Update - June 2023
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Experience Management Update
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Key Theme: AI Powered Chatbots
- The new generative AI world has caused a new question to emerge in XM: will powerful large language models (LLMs) like ChatGPT will replace traditional chatbots? Currently, often providing narrow, pre-set responses, chatbots are predicted to resolve 75%-90% of queries in the healthcare and banking industries by 2027. Could LLM powered accelerate chatbots’ evolution to have interactions so human-like that most customer service requests can be handled without human intervention? Traditional chatbots are limited to a defined set of topics and not able to respond to prompts from outside those topics. Answers are also pre-written or pre-approved by humans, which means that they are non-generative.
- LLM-based chatbots, on the other hand, are open-domain and can discuss a wide range of topics. Chatbots infused with AI would be able to generate responses in real-time, rather than from a pre-ordained set of questions. Examples include Open AI’s ChatGPT and Google’s Meena. LLMs have the potential to propel the CX world into another technological tier. They key will be fusing LLMs like ChatGPT command of natural language and expressiveness with the guard rails that CXO seek to have when responding to customer inquiries. According to Gartner, AI powered chatbots are predicted to save $80 billion in labor costs by 2026 and one in 10 agent interactions will be automated by 2026, which is an increase from the 1.6% of interactions today automated by AI.
- “I also think that there's going to be a very interesting convergence between some of the AI agents in messaging and business messaging, where, right now, we see a lot of the places where business messaging is most successful are places where a lot of businesses can afford to basically have people answering a lot of questions for people and engaging with them in chat. And obviously, once you light up the ability for tens of millions of small businesses to have AI agents acting on their behalf, you'll have way more businesses that can afford to have someone engaging in chat with customers. So I think that, that could be a pretty big opportunity, too.” – Mark Zuckerberg (Chairman & CEO at Meta), Q1 202e Earnings Call, 4/26/2023
Key Theme: Proprietary Data Sets
- As a race to create the most effective, AI powered chatbot gets underway between XM players, access to proprietary data sets, upon which to train their LLMs will rapidly become the next battleground.
- “From a strategic perspective, AI has 2 foundational pieces. One is the data models. And that's the stuff we're seeing with OpenAI and large language models. And the other, just as important, is actually the data set that the model uses to generate outcomes. There's been a lot of focus on the model because of what's gone on with ChatGPT. But we can see sometimes it has issues because the underlying data set is using public data. LivePerson has one of the largest and most precise conversational business data sets in the world. And I use the word precision because over 350,000 people on our platform each day, and they're messaging their live agents and they are generating 1 billion conversations a year, and these are high-quality conversations around many different topics, but the conversations are precise. There are answers to questions in the way the brand would want it answered. These agents, they create a long tail of answers.” – Robert LoCascio (Chairman & CEO at LivePerson), Q4 2022 Earnings Call, 3/15/2023
We hope you find this information valuable, and as always, feel free to reach out if you would like to discuss in further detail. To read the full report, download the PDF below. Footnotes and sources are noted in the deck.
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Joe Mathew
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Roderick Moon
Managing Director, KPMG Corporate Finance LLC
Joe Mathew
Vice President | TMT Investment Banking, KPMG Corporate Finance LLC
Jacquie Litwin
Senior Associate | TMT Investment Banking, KPMG Corporate Finance LLC