Roos Knape

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We are all familiar with the traditional definition of network effects, but if you are not, here is a quick reminder. According to Banton (2024), network effects occur when the value of a product or service grows when an increased number of people make use of it. Network effects can play a significant role in the growth of products and services. For example, think of how much value OpenAI created when it reached over 100 million users within two months for its newly developed ChatGPT application (Milmo, 2023). However, Generative AI services, such as ChatGPT, are subjected to a new form of network effects. A distinct network effect that could be even more beneficial to Generative AI.

Generative AI tools grow value by providing accurate answers to the queries they are being asked. As Generative AI tools depend on the inflow of large customer data sets to work effectively, they use customer feedback to enhance their answers. The value of the systems, therefore, depends on the data that is provided by users. The ability to provide enhanced answers and suggestions based on user feedback introduces a new network effect: data network effects. Data network effects similar to traditional network effects, but rather focus on the technological value users provide. Let me explain! Through reinforcement learning, Generative AI tools can use customer feedback on queries to increase their intelligence. Higher intelligence results in more accurate answers and suggestions, making it more attractive for new users. More users lead to more responses, resulting in even higher accuracy and a circular development of the Generative AI tool (Levine, 2023).

By explaining how data network effects work, managers can understand its impact on future applications. However, the discovery and effects of data network effects has just started!

References:

Banton, C. (2024, 22 augustus). What Is the Network Effect? Investopedia. https://www.investopedia.com/terms/n/network-effect.asp

Milmo, D. (2023, 3 februari). ChatGPT reaches 100 million users two months after launch. The Guardian. https://www.theguardian.com/technology/2023/feb/02/chatgpt-100-million-users-open-ai-fastest-growing-app

Levine, S. S. (2023, 16 maart). How network effects make AI Smarter. Harvard Business Review. https://hbr.org/2023/03/how-network-effects-make-ai-smarter

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Picture this: You’ve bought a festival ticket, but something went wrong—maybe you need to report a problem or request a refund. So, naturally, you head to the website, expecting a quick solution. Perhaps a helpful phone number or at least a clear answer to your question. Instead, you’re met with a chatbot. After a few attempts, it’s clear that you’re trapped in a loop of canned responses, none of which solve your issue. Frustration builds as it feels as if you are talking to a wall instead of a person who is willing to help you.

Sound familiar? Well, you’re not alone. This type of experience has become the norm when dealing with chatbots, leaving users feeling more helpless and unsettled than ever and preferring human agents (Elliott, 2018). But what if there was a different solution to this problem? Enter generative AI avatars. Shah (2024) explains how advanced, human-like versions of chatbots offer something chatbots lack, emotional intelligence, engagement, and empathy. Unlike chatbots, which often answer with pre-determined or automated responses, AI avatars are designed to engage in more dynamic and natural conversations. They can interpret the intent behind questions and adjust accordingly. Diminishing the feeling of irritation and helplessness.

I was fortunate enough to develop such a real-life generative AI avatar myself. I have a hate-love relationship with chatbots. Having worked and experimented with chatbots, I can easily distinguish the difference between a so-called cheap or expensive (well-developed) chatbot. However, generative AI avatars are on a whole other level. When asking a question, it feels much more personal and interactive in comparison to an online chatbot. I felt more at ease and wanted to cooperate more than I would have with an online chatbot. As generative AI avatars continue to evolve and improve, their potential applications extend far beyond just customer service. From therapy to healthcare, these avatars could play a significant role in transforming how we interact with technology—or even each other.

References:

Shah, S. (2024, 8 maart). The rise of AI talking avatars: Enhancing customer interactions and engagement. Revenue Marketing Alliance. https://www.revenuemarketingalliance.com/ai-talking-avatars-customer-interactions-and-engagement/

Elliott, C. (2018, 27 augustus). Chatbots are killing customer service. Here’s why. Forbes. https://www.forbes.com/sites/christopherelliott/2018/08/27/chatbots-are-killing-customer-service-heres-why/

The data network effect: The impact of Network effects on the development of AI

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Beyond the script: How Gen AI avatars could redefine customer service

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