The GPT-3 chatbot has taken the world by storm.
Only a few years ago, terms like “ChatGPT” and “Generative AI” were virtually unheard of in the business space. Now, it seems like GPT technology is all anyone can talk about.
Marking a new era for chatbot creation, GPT technology, and other solutions built with large-language models are significantly impacting the customer experience landscape.
Countless vendors, from Salesforce to Microsoft, are now investing in building their own generative bots for various use cases. At the same time, the hype around GPT-3 and similar tools have accelerated the growth of the chatbot market.
By 2032, the market for chatbot technology is set to be worth around $4.9 billion.
So what is a GPT-3 chatbot, and how does it influence customer service?
What is a GPT-3 Chatbot?
A GPT-3 chatbot is a programmable artificial intelligence application powered by generative AI. Specifically, GPT-3 is the language model produced by OpenAI, used to form the first version of ChatGPT. “GPT-3” stands for “Generative Pretrained Transformer 3”.
GPT-3 chatbots utilize the underlying language model created by OpenAI to interact naturally with human beings. The software that powers these bots includes over 175 billion machine-learning parameters. These parameters help the GPT-3 bot analyze human input in text form.
OpenAI’s GPT-3 chatbot technology can analyze, understand, and respond to customer questions. It can predict intent and needs based on a single word and respond to queries with natural human language.
The hype around ChatGPT has prompted countless companies to implement GPT-3, GPT-3.5, and GPT-4 language learning models into their ecosystems, particularly in the contact center. The rise of this technology has also inspired other brands to create similar large language models.
For instance, Zoom recently partnered with the AI developer Anthropic to create its own competitor to ChatGPT, Claude, ready to be deployed within the Zoom CCaaS platform.
Is a GPT-3 Chatbot ChatGPT?
The GPT-3 chatbot represents a new era for chat technology based on generative AI. However, as a relatively new technology, it has sparked some confusion among companies.
For instance, people frequently use the terms “GPT-3” and “ChatGPT” interchangeably. However, while OpenAI created both solutions, they serve slightly different purposes.
ChatGPT is a specific tool designed for chatbot applications, while GPT-3 is a more general-purpose model used for various use cases. ChatGPT excels at generating responses to questions with conversational context, while GPT-3 is better suited to language translation and content creation.
Notably, GPT-3 is also a more customizable solution. Though OpenAI has created enterprise-grade APIs for companies looking to access ChatGPT in business operations, ChatGPT isn’t an open platform. GPT-3, as well as other large language models, are available to access and customize.
With GPT-3 and similar solutions, companies have more freedom to take full advantage of the generative AI ecosystem. Brands can create GPT-3 chatbots tailored to specific use cases, such as serving customers on a financial app or responding to troubleshooting requests.
How Does a GPT-3 Chatbot Work?
A GPT-3 chatbot and other generative AI bots created with similar large language models use deep neural networks, massive databases, and machine learning to interact with humans. A GPT-3 chatbot, unlike a standard conversational bot, can deeply analyze and understand customer queries.
GPT-3’s large language model adds greater contextual understanding and pattern recognition to the processes of scripted bots. Like other generative language models, GPT-3 chatbots use statistics drawn from vast volumes of data to predict and generate outputs based on specific inputs.
The pre-trained technology offered by OpenAI with the GPT-3 model makes it easier for customer service departments to create and launch their own bots quickly. There’s no need to develop new AI and machine learning tools, meaning virtually any business can use generative AI.
Part of what makes a GPT-3 chatbot unique is its ability to draw context and meaning from structured and unstructured interactions. These bots can process information almost in the same way as a human brain, leading to more natural conversational experiences.
The Evolution of GPT-3 Chatbots: GPT-3.5 and GPT-4
Although business leaders and contact center vendors have only recently begun exploring the benefits of GPT chatbot technology, the underlying model has been around for a while. The GPT-3 technology was released in 2020 and was fine-tuned in 2022 to create GPT-3.5.
In March 2023, OpenAI released the next version of its GPT language model: GPT-4. This updated version of the GPT technology takes the abilities of LLM bots to the next level. GPT-3 is 40% more likely to serve factual responses than GPT-3.5.
Additionally, GPT-3 can process 25,000 words (eight times more than GPT-3), handle image input, and deal with far more nuanced instructions than GPT-3.5. GPT-4 also addresses some major concerns of companies using GPT chatbots for customer service.
The solution is 82% less likely to respond to requests for inappropriate content. It’s also faster and more efficient than its predecessors. GPT-4 chatbots could lead the way to new opportunities in customer service, offering enhanced multi-media information sharing and more secure interactions.
How to Create a GPT-3 Chatbot
The GPT-3 chatbot model and OpenAI’s GPT-3.5 and GPT-4 solutions are now available to access online. However, creating a GPT-3 chatbot from scratch can be complex. It requires deep knowledge of development languages, like Python, and access to an OpenAI API key.
Fortunately, OpenAI and other development companies are making it easier for business owners to access and customize their GPT-3 chatbots. OpenAI’s decision to launch ChatGPT APIs for business leaders has already led to an influx of companies embedding GPT chat technology into their ecosystems, such as Shopify and Snap.
Contact center vendors are also working with OpenAI and other developers to implement GPT-3 chatbot capabilities into their existing tools.
Cyara integrated GPT-3 into its ecosystem to speed up the creation of training and testing data for Cyara Botium, the brand’s conversational AI assurance solution. Five9 also recently launched two new products, leveraging GPT-3 chatbot technologies: AI Insights and AI Summaries.
The AI Insights tool combines GPT-3 with real-time transcription to interpret customer conversations and arrange them into categories. The AI Summaries tool, on the other hand, supplements Five9’s agent-assist solutions by auto-summarizing interaction transcripts and uploading them to CRMs.
However, companies aren’t just investing in OpenAI’s technology for GPT chatbots. The growing hype around GPT-3 bots has prompted many organizations to experiment with their large language models and innovative tools.
The Google AI contact center now uses its own GPT technology to provide companies with a way of building their own generative AI bots for customer service requirements.
Companies Investing in GPT-3 Chatbot Tools
As interest in generative AI technologies continues to grow throughout the customer experience landscape, virtually every major brand is getting involved.
Talkdesk launched a call summarization feature, which uses GPT-3 chatbot services similar to those used by ChatGPT to automate post-call processing for agents.
HORISEN added a direct ChatGPT bot API into its omnichannel business messenger platform, designed to support companies with customer service and messaging campaigns. Elsewhere, Nuance built GPT technologies into its AI platform, Nuance Mix.
The GPT solution Nuance offers includes “Nuance Mix Answers,” a solution built on the Azure OpenAI service powered by Microsoft’s partnership with OpenAI. Even Microsoft is getting involved with the GPT chatbot landscape.
The company created its “Copilot” solution for Office apps and Microsoft Teams. It’s also working on adding generative AI to solutions like Viva Sales and the Microsoft Digital Contact Center platform.
NICE also announced the integration of its contact center solutions with OpenAI’s generative modeling infrastructure. At NICE Interactions 2023, the company introduced its new “Enlighten” solution, powered by generative AI, to deliver personalized self-service experiences and agent support.
The Benefits of a GPT-3 Chatbot for Customer Service
Access to solutions like GPT-3 chatbot models gives contact center vendors and business leaders many new opportunities to explore in customer service. Demand for innovative chatbot solutions in the contact center has been increasing for years.
Already, companies have learned bringing chatbots to the customer service landscape means unlocking opportunities for better team efficiency, 24/7 availability, and personalized customer service. However, many old-fashioned bots have needed help to keep up with customer expectations.
Enhanced GPT-3 chatbot systems and similar tools can overcome these issues.
GPT-3, GPT-3.5, and GPT-4 bots can:
1. Transform communication
GPT-3 chatbots and bots built with generative AI technologies can significantly enhance communications between bots and customers. Companies can tailor their generative bots using streamlined APIs and train them to respond to many customer questions.
Brands can use predictive technology in GPT toolkits to help bots anticipate client needs and provide context-based answers. Plus, because GPT bots can be customized to each company’s needs, they can provide every customer with a consistent, branded experience.
Thanks to APIs, companies can embed these bots into various channels, from web-based chat systems to social media messaging platforms and more.
2. Enhance agent performance
Most chatbots are excellent at improving efficiency and productivity in the contact center. They can handle multiple queries simultaneously, drastically reducing waiting times and minimizing the number of interactions each agent needs to take.
However, GPT-3 chatbot tools and similar solutions can take agent performance to the next level. They can automatically gather pertinent information and use context to determine how to escalate concerns to live agents. They can also automatically guide agents through a conversation, generating intelligent responses to customer questions.
3. Improve agent support
Programmable GPT-3 chatbot tools can help answer customer queries and drive self-service experiences. However, they can also be beneficial to agents in the contact center. They can clarify customer requests with a contact before passing them to an agent, streamlining conversations.
They can also collect information from CRM libraries and product listing databases, giving agents access to all the resources needed to resolve a query in one place. Some solutions, like NICE’s Enlighten Actions, can even provide CX leaders with actionable insights on enhancing productivity and streamlining operations.
4. Increase customer satisfaction
Chatbots have long promised companies the opportunity to improve customer experiences with personalized, 24/7 service for clients. However, many old-fashioned bots were frustrating, complex, and challenging. A GPT-3 chatbot, or even one powered by GPT-4, could address this problem.
The right GPT bot can personalize interactions based on the given data, leading to more relevant customer experiences. It can also better understand various kinds of input, meaning the system is more likely to deliver accurate, helpful responses without human support.
5. Reduce operational costs
Although companies today recognize the need to invest heavily in exceptional customer experiences, all contact centers have budgets. A GPT-powered chatbot can offer a low-cost, intuitive alternative to investing in contact center outsourcing and additional staff.
Accessing keys from companies like OpenAI or leveraging GPT-3 chatbot tools built into a contact center platform is also far more straightforward (and cheaper) than in-house development.
The Limitations of a GPT-3 Chatbot
While GPT-powered chatbots have several benefits, they’re not without limitations. Gartner even issued a report warning companies of the risks of relying too heavily on solutions like ChatGPT in 2023. According to the analyst, these bots can still generate incorrect responses to queries and may present security issues when managing customer data.
Additionally, the earliest version of the OpenAI GPT model is relatively limited. It lacks access to up-to-date information, which makes it only capable of responding to specific queries.
While upgrading to solutions like GPT-4 could help address this issue, companies will still need to invest in substantial training strategies. Contact center vendors providing access to their bot-building tools may be able to help with some of the training requirements. However, businesses may still need to input their own data.
The Future of Contact Center Chatbots
The GPT-3 chatbot marks the beginning of a new revolution in the chatbot landscape for contact centers. With access to generative AI and large language models, companies can finally leave clunky, inefficient bots in the past. However, like any new and innovative tech, GPT bots must be correctly implemented into a contact center.
Working with a suitable vendor to access pre-built GPT solutions should prevent businesses from developing their own conversational AI tools from scratch. However, they’ll still need to ensure they use their bots correctly.
Implementing strategies to secure the data used by generative bots, preserve the human element in the contact center, and consistently improve efficiency will be essential.
As new solutions like GPT-4 enter the market, we’ll likely see countless new vendors exploring new ways to help companies create and implement their generative bots.