What Is Artificial Intelligence (AI)?
What Is Conversational AI? More Than Just Chatbots
The truth about conversational AI: Discover how today's technology is shaping our interactions in unexpected ways.
The GistEditor's Note: This article has been updated to include new data and information.
When people think of conversational artificial intelligence (AI) their first thought is often the chatbots they might find on enterprise websites. Those mini windows that pop up and ask if you need help from a digital assistant.
While that is one version, many other examples can illustrate the functionality and capabilities of conversational artificial intelligence technology.
What is conversational artificial intelligence, exactly, and how did it come to be? What does a conversation with artificial intelligence look like? And what impact will this technology have on business-consumer relationships?
The History of Conversational AI: From Chatbot to PresentThe standard definition of conversational AI is a combination of technologies — machine learning (ML) and natural language processing (NLP) — that allows people to have human-like interactions with computers. To understand this further, let's look at the evolution of conversational AI.
1960s: The Rise of the ChatbotChatbots made their debut in 1966 when a computer scientist at MIT, Joseph Weizenbaum, created Eliza, a chatbot based on a limited, predetermined flow. Eliza could simulate a psychotherapist's conversation through the use of a script, pattern matching and substitution methodology.
Although Eliza could pass a restricted version of the Turing test — a test that determines if a machine can display intelligent behavior indistinguishable from a human being — and fool people into thinking they were talking to another human, it was simply following rules and simulating the conversation with no real level of understanding.
1970s: New Natural Language UnderstandingA decade later, Kenneth Mark Colby at the Stanford Artificial Intelligence Laboratory created a new natural language processing program called PARRY. Although it was the first AI program to pass a full Turing test, it was still a rule-based, scripted program.
1990s: Optimized Natural Language GenerationIn 1995, Richard Wallace created the Artificial Linguistic Internet Computer Entity (ALICE). It used what was called the Artificial Intelligence Markup Language (AIML), which itself was a derivative of Extensible Markup Language (XML).
Like its predecessors, ALICE still relied on rule-matching input patterns to respond to human queries, and as such, none of them were using true conversational AI.
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The Advancement of Conversational AIWhat is conversational AI? It relies on NLP, automatic speech recognition (ASR), advanced dialog management and ML, and can have what can be viewed as actual conversations.
Conversational AI uses deep learning to continuously learn and improve from each conversation. It is flexible and able to jump from one topic to another, much like actual human speech and unlike traditional chatbots, which are limited to pre-defined scripts and rules and cannot respond with anything not originally inserted into its conversational flow.
Recent advancements in generative AI, such as OpenAI's GPT models and Google's Gemini, have transformed conversational AI by enabling more context-aware, creative and adaptive interactions. Unlike traditional scripted responses, generative AI is built upon large language models (LLMs) trained on huge datasets to understand context, predict user intent and generate human-like dialogue in real-time.
This technological advancement in AI has unlocked new possibilities across various industry domains.
As opposed to rule-based chatbots, these new capabilities represent a fundamental shift in what conversational AI can achieve, allowing for interactions that are not only efficient but also engaging and tailored to individual user needs.
"Rule-based or scripted chatbots are best suited for providing an interaction based solely on the most frequently asked questions. An 'FAQ' approach can only support very specific keywords being used," said Eric Carrasquilla, CEO at Vendavo.
"Conversational AI is ingesting the customer feedback and learning in real-time that value, which can be applied to the same question at a different point of a client's journey," he added.
By using conversational AI chatbots, basic contact queries such as delivery dates, tracking numbers and shipping fees can be easily and quickly taken care of, while more complex or serious customer service inquiries can be passed on to live customer service representatives.
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View all"The appropriate nature of timing can contribute to a higher success rate of solving customer problems on the first pass, instead of frustrating them with automated responses," said Carrasquilla.
Multimodal AI: Expanding Conversational CapabilitiesThe latest advancements in conversational/generative AI include the rise of multimodal AI models, which can process and respond to inputs across multiple formats, including text, images and voice. OpenAI's ChatGPT-4o, the multimodal version of ChatGPT, is a prime example, capable of interpreting images, understanding spoken language and generating coherent responses that integrate multiple modalities. This breakthrough enhances conversational AI's versatility, making it more relevant across industries.
In retail, multimodal AI is poised to enhance customer experiences by allowing users to upload photos for product recommendations or seek assistance through voice commands. For customer service, multimodal models can streamline interactions by integrating text and visual cues — for example, helping troubleshoot issues by analyzing a photo of a defective product. In accessibility, these models can provide inclusive solutions by converting speech to text for individuals with hearing impairments or offering voice-based navigation for visually impaired users.
Multimodal AI is not just a technical leap; it represents a shift toward more intuitive and user-centric interactions. By integrating different formats, conversational AI can deliver richer, more dynamic experiences that meet diverse user needs.
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People Trust Conversational AI SolutionsOne top use of AI today is to provide functionality to chatbots, allowing them to mimic human conversations and improve the customer experience.
A Statista report revealed that process automation and customer service were the two most popular applications of AI in American and European companies. AI chatbots exemplify this trend by automating routine tasks like answering FAQs, tracking orders and scheduling appointments, while simultaneously improving customer service through real-time, personalized interactions. Their ability to blend efficiency with a human-like conversational touch makes them a cornerstone of AI-driven strategies in both areas.
A Pew Research survey found that 27% of Americans interact with AI multiple times a day, while 28% engage with it daily or several times a week. More importantly, 65% of respondents reported using a brand's chatbot to answer questions, highlighting the growing role of AI in everyday customer interactions.
According to a Forbes Advisor article, despite ongoing concerns about AI, 65% of consumers express trust in businesses that use AI technology. Among them, 33% are very likely to trust such businesses, and another 32% are somewhat likely, reflecting a growing acceptance of AI-driven solutions.
It's not just customers that are beginning to trust conversational AI. Those established in their careers also use and trust conversational AI tools among their workplace resources. Oracle and Future Workplace's annual AI at Work report indicated that 64% of employees would trust an AI chatbot more than their manager — 50% have used an AI chatbot instead of going to their manager for advice.
Twenty-six percent of those polled said bots are better at providing unbiased information and 34% said they were better at maintaining work schedules. Not only that, but 65% of employees said they are optimistic, excited and grateful about having AI bot "co-workers" and nearly 25% indicated they have a gratifying relationship with AI at their workplace.
The Washington Post reported on the trend of people turning to conversational AI products or services, such as Replika and Microsoft's Xiaoice, for emotional fulfillment and even romance.
Amid growing advances in AI, many people have turned to AI-driven chatbots and voice bots for meaningful interactions that mimic human connection. Platforms like Xiaoice, which claims to have communicated with 660 million active users since its release in 2014, are a good example of how conversational AI has evolved to fulfill not just practical needs but also emotional and social ones, becoming an integral part of daily life.
Conversational AI Is Trusted — but Is It Safe?People trust conversational AI solutions and they find the technology helpful when they need to search for information. But does that mean its safe to use?
With the two examples of conversational AI above, where people have private conversations with a bot, perhaps even share personal information, the question of privacy and security might come to mind. How safe is conversational AI to use?
Like most things, conversational AI is as safe as it's built to be. Users not only have to trust the technology they're using but also the company that created and promoted that technology. Finding out if a specific conversational AI application is safe to use will require a little bit of research into how the bot was made and how it functions.
You'll want to look for three things when it comes to finding a safe AI bot:
Conversational AI users should also ensure they have a fundamental understanding of internet safety measures, including:
Traditional chatbots are text-based. They're typically found on only one of a brand's channels — usually a website. They aid in customer service conversations and can improve the overall customer experience.
Conversational AI solutions, however, are omnichannel. They can be accessed and used through many different platforms and mediums, including text, voice and video.
"The pairing of intelligent conversational journeys with a fine-tuned AI application allows for smarter, smoother choices for customers when they reach out to connect with companies," Carrasquilla suggested.
Among other common conversational AI examples is the digital assistant — think Cortana, Google Home, Amazon Alexa and Siri.
According to a Statista report, there are around 200 million smart speakers in use worldwide, which — along with virtual assistants — have facilitated the acceptance of conversational AI in the household. According to WorldMetrics, 41% of people who own a voice-activated speaker say it feels like talking to a friend or another person.
Some call centers also use digital assistant technology in a professional setting, taking the place of call center agents. These digital assistants can search for information and resolve customer queries quickly, allowing human employees to focus on more complex tasks.
Chris Radanovic, a former conversational AI expert at LivePerson and now director of product marketing at Infobip, told CMSWire that in his experience, using conversational AI applications, customers can connect with brands in the channels they use the most.
"Intelligent virtual concierges and bots instantly greet them, answer their questions and carry out transactions, and if needed connect them to agents with all of the contextual data they've collected over the course of the conversation."
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Conversational AI Facilitates Hyper-Personalization"Hyper-personalization combines AI and real-time data to deliver content that is specifically relevant to a customer," said Radanovic. And that hyper-personalization using customer data is something people expect today.
Radanovic emphasized that consumers and brands are embracing conversational AI because it provides personalized experiences that are much quicker and more convenient than traditional ways of interacting with businesses. Customers do not want to be waiting on hold for a phone call or clicking through tons of pages to find the right info.
According to Radanovic, conversational AI can be an effective way of eliminating pain points in the customer journey.
"A giant source of frustration for consumers is repeating information they've already shared, like re-confirming a phone number or having to re-explain a problem to multiple agents," he explained.
As brands adopt tools that allow conversational AI to connect customer data, said Radanovic — like connecting conversation histories with previously stated intentions — the conversations they have with customers will feel more personalized.
Conversational AI Is Part of Our Daily LivesTraditional chatbots remain useful for answering straightforward queries, but conversational AI has become an integral part of modern life.
Whether guiding shoppers in augmented reality, automating workflows in enterprises or supporting individuals with real-time translation, conversational AI is reshaping how people interact with technology. As it continues to learn and improve, conversational AI bridges the gap between human needs and digital possibilities.
Conversational AI models are not only very effective at emulating human conversations but they have also become a trusted form of communication. Businesses rely on conversational AI to stimulate customer interactions across multiple channels. The tech learns from those interactions, becoming smarter and offering up insights on customers, leading to deeper business-customer relationships.
But these bots go beyond pure business use. People use these bots to find information, simplify their routines and automate routine tasks. Ultimately, they've become an extension of people's daily lives.
What Companies Are Fueling The Progress In Natural Language Processing? Moving This Branch Of AI Past Translators And Speech-To-Text
AFP via Getty Images Key takeawaysChatbots have exploded in popularity in recent months, and there's a growing buzz surrounding the field of artificial intelligence and its various subsets. Natural language processing (NLP) is the subset of artificial intelligence (AI) that uses machine learning technology to allow computers to comprehend human language.
AI has many applications, including everything from self-driving cars to AI-driven investing. If you're curious about what AI can do for your portfolio, download the Q.Ai app to get started.
Natural language processing applications have moved beyond basic translators and speech-to-text with the emergence of ChatGPT and other powerful tools. We will look at this branch of AI and the companies fueling the recent progress in this area.
What's natural language processing all about?Natural language processing (NLP) is a subset of artificial intelligence (AI) that uses linguistics, machine learning, deep learning and coding to make human language comprehensible for machines. Natural language processing is a computer process enabling machines to understand and respond to text or voice inputs. The goal is for the machine to respond with text or voice as a human would.
The long-term objective of NLP is to help computers understand sentiment and intent so that we can move beyond basic language translators. This subset of AI focuses on interactive voice responses, text analytics, speech analytics and pattern and image recognition. One of the most popular uses right now is the text analytics segment since companies globally use this to improve customer service by analyzing consumer inputs.
The potential for NLP is formidable. According to Fortune Business Insights, the global market size for natural language processing could reach $161.81 billion by 2029. Market research conducted by IBM in 2021 showed that about half of businesses were utilizing NLP applications, many of which were in customer service.
How are businesses using NLP to improve operations?The primary benefit of NLP solutions for businesses is to use automation to cut costs and improve business operations to maximize productivity and profitability. Here are a few ways that NLP is being utilized right now by businesses globally:
You may be using NLP services daily without even noticing it. We enjoy more and more of these technological benefits as they advance. Here are some common examples of NLP:
We also can't ignore the role of AI and NLP in everyday services like streaming platforms and e-commerce websites (Amazon), where it feels like our results are customized by someone who knows us.
What companies are fueling the progress in natural language processing?While almost every business has to use some form of NLP and AI in its operations, some companies are fueling the recent progress in these technologies. Here are five companies in this space to keep an eye on.
MicrosoftMicrosoft has been making headlines lately since the company reportedly invested $10 billion in OpenAI, the startup behind DALL-E 2 and ChatGPT. These two tools alone have changed the entire landscape of AI and NLP innovations as the improvements bring this technology to the general public in new, exciting ways.
Microsoft Azure is the exclusive cloud provider for ChatGPT, and this platform also offers many services related to NLP. Some services include sentiment analysis, text classification, text summarization and entailment services.
IBMWhile IBM has generally been at the forefront of AI advancements, the company also offers specific NLP services. IBM allows you to build applications and solutions that use NLP to improve business operations.
One of the revenue streams for the company is the IBM Watson Natural Language Understanding service which uses deep learning to derive meaning from unstructured text data. On the Watson website, IBM touts that users have seen a 383% ROI over three years and that companies can increase productivity by 50% by reducing their time on information-gathering tasks.
AmazonThe significance of AI and NLP is felt at almost every level of Amazon's business. You may have used the Alexa device to put on your favorite song or found the perfect product on the e-commerce platform based on a recommendation. These are AI and NLP in action.
Amazon also offers Amazon Web Services (AWS) for cloud storage so businesses can complete their digital transformations. They also have Amazon Comprehend, an NLP service that uses machine learning to determine text's significance. The Comprehend service also offers sentiment analysis and custom segmentation so customers can add NLP to their apps.
LemonadeWhen discussing AI, you can't forget about the first insurance company fully Google
Even though Alphabet, the parent company of Google, recently revealed that it would be cutting 12,000 employees worldwide, they're also planning on launching 20 new products. Google has already offered a small sample group an exclusive look at a tool that will eventually be a competitor to ChatGPT, known as Bard. This chatbot is
The biggest issue for Google is that they want to offer an AI-powered chatbot that's safe, tackles misinformation, and shares factually accurate information. Google has been investing heavily in AI, and it's no secret that management wants to bring the company back to the forefront of this field. You can see Google utilizing NLP technology in every aspect of its business, including spam filters, predictive text when writing emails, search engines and translation tools.
How can you invest in NLP and AI?If you're a proponent of machine learning, there are many different ways to invest in AI and related technologies. There aren't companies that only focus on AI in the same way that Tesla focuses on EVs or Nike focuses on athletic wear because every successful business relies on some form of AI. You can, however, invest in major tech companies since they're becoming increasingly invested in AI. With Amazon relying on AI on everything from the Alexa device to powering the warehouses, this is one company that's all in.
OpenAI is projected to generate $1 billion in revenue in 2024. While you can't invest directly in OpenAI since they're a startup, you can invest in Microsoft or Nvidia. Microsoft's Azure will be the exclusive cloud provider for the startup, and most AI-based tools will rely on Nvidia for processing capabilities. In recent weeks, shares of Nvidia have shot up as the stock has been a favorite of investors looking to capitalize on this field.
You don't have to look any further if you want to see the capabilities of AI in investing. Q.Ai uses AI to offer investment options for those who don't want to be tracking the stock market daily. The good news is that Q.Ai also takes the guesswork out of investing if you want a hands-off approach. Check out the Emerging Tech Kit if you're a proponent of innovative technology.
The bottom lineNatural language processing and artificial intelligence are changing how businesses operate and impacting our daily lives. Significant advancements will continue with NLP using computational linguistics and machine learning to help machines process human language. As businesses worldwide continue to take advantage of NLP technology, the expectation is that they will improve productivity and profitability.
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