TECHNICAL
position themselves as service providers, with solutions underpinned by generative AI integrated into existing portfolios. Specifically, Juniper Research predicts that generative AI will revolutionise the automation of personalised marketing campaigns in a number of ways, including: n Chatbots and Conversational AI: Chatbots that leverage generative AI will engage with users with personalised conversations, recommendations and question answering. n User Segmentation: Generative AI will allow enterprises to identify and segment audiences based on demographics and behaviours to enable more targeted marketing campaigns. Through the support of CPaaS (Communication Platforms-as-a- Service) and CSP (Communications Service Providers), enterprises are able to provide an omnichannel experience through the coordination of marketing materials across various marketing channels to ensure a consistent tailored experience. n Multichannel Marketing: However, Juniper Research warns that educating enterprises is necessary to ensure that the ecosystem is able to understand and utilise the differences in capabilities between generative AI
have the ability to increase the value proposition of their services, specifically via authentication services. For example, if operators are not able to reduce prices, then they must look to promote their API- based authentication solutions, such as Number Verify. Generative AI to Revolutionise Conversational AI by Automating Personalised Marketing Since late 2022, conversational AI has gained an immense new level of popular curiosity with the November 2022 launch of OpenAI’s ChatGPT (Generative Pre-trained Transformer). ChatGPT is a chatbot with a generative LLM. The initial language model on release was called GPT-3.5, but the subsequent GPT-4 was released in March 2023. Since then, generative AI, an emerging technology that automates the generation of new digital content, will be considered a priority in 2024 for conversational AI vendors and will play a key role in LLMs. Specifically, Juniper Research believes that generative AI models will be embedded into LLMs to map entity and sentiment analysis whilst also being able to provide summaries of conversations for enterprises to utilise in future conversations. There are numerous examples of how the technology can benefit enterprises, and conversational AI vendors must look to
Figure 7: Example of Conversational Commerce Chatbot
and conversational AI. With this, whilst conversational AI is trained using large datasets to respond to customer queries as if it were human, generative AI is trained to autonomously create personalised content and resources. Additionally, with all the hype around generative AI, there seems to be a common opinion amongst enterprises that the technology will be able to adapt to specific company processes to solve all business problems, thus replacing the need for specific third-party service providers. For example, many enterprises confuse generative AI with general AI and the efficiency savings that arise. Therefore, Juniper Research anticipates that in 2024, services providers in the telecommunications space will not focus on developing their own generative AI capabilities to automate marketing processes, but these vendors will also place emphasis on educating enterprises on the capabilities of generative AI. This education will ensure that enterprises still value the outsourcing and management of telecommunications services to third- party service providers. With this, Juniper Research predicts that generative AI will create personalised content such as product descriptions, social media messages, and email reach-out that will be used for tailored conversational interactions with customers.
Figure 6: Total Spend on Chatbot Commerce ($m), Split by Market Vertical, 2023-2028
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Volume 46 No.1 March 2024
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