Conversational AI
The Future of Conversational AI for Product Marketers
The buzz around OpenAI’s ChatGPT and the surge in experimentation across various generative AI use cases signify the incredible advancements in conversational artificial intelligence (AI).
This innovation is driven by the fusion of foundation models, knowledge graphs, and human-supported reinforcement learning. Over the next three years, these AI techniques will dramatically transform the intelligent capabilities of software and advanced virtual assistants (VA).
As a product marketing professional, it’s important to stay on top of these trends and understand how they can give you a competitive edge. In this blog post, we’ll explore how generative AI and foundation models are shaping the future of conversational AI.
Foundation Models: A Major AI Advancement
Foundation models are one of the most significant advancements in AI technology. These models are created by training a neural network on vast amounts of data, allowing it to learn patterns and make predictions. They represent a major AI advancement and are transforming the intelligent and conversational capabilities of software and advanced virtual assistants (VA).
However, it’s important to note that foundation models should be explored as a potential technology in combination with other AI-developing techniques, such as knowledge graphs and reinforcement learning. As a product marketer, it’s important to explore custom large language models (LLMs) to prepare for organizations’ accelerated acceptance of intelligent software and VA.
Generative AI: Increasing Perception of Intelligence
On the other hand, generative AI is a technique that uses machine learning to generate new data that resembles the training data. It’s a powerful tool that can be used to create content, personalize customer experiences, and even develop AI avatars that can assist with digital and marketing communications.
The use of generative AI will expand in the next two years, and Gartner predicts that generative AI will create more than 30% of marketing content that’s human-augmented by 2025. By incorporating generative AI and foundation models around specific areas and utilizing a Markov decision process-based approach, product leaders can create successful product strategies and gain a competitive edge in the market.
Applications to Multiple Industries and Domains
The use cases for conversational AI are expanding across multiple business domains and industries, from content marketing to new intelligent search options, AI avatars, and decision intelligence. As a product marketing professional, it’s important to examine NLP-related startups to help identify new opportunities for innovation.
It’s predicted that by 2025, more than 50% of advanced virtual assistants (VAs) will be industry-domain-specific, up from less than 25% in 2022. Industry-domain-specific VAs are designed to assist people within a specific domain, such as healthcare, banking, retail, or legal. They can also incorporate fine-tuned, domain-specific language models, prebuilt integration with relevant enterprise applications, and connection with business processes.
The Next Steps for Product Leaders
As a product marketer, it’s essential to understand the challenges and opportunities associated with these emerging technologies.
Accelerating your solutions toward becoming more generative AI-enabled, complementary to existing search solutions, and enabling real-time neural machine translation is crucial. Additionally, humanizing internal and customer communications with AI avatars based on text-to-video generative AI technology is an area of significant opportunity. To elevate the business value of emerging technologies like conversational AI and advanced VAs, technology providers can uncover a promising future.
