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January 11, 2024

How Conversational AI is Transforming Communication

John

Introduction

Conversational AI feels like a natural extension of ChatGPT. It makes sense that if you can converse with an AI assistant using text, you can also speak with it using voice. Until recently, however, true conversational AI has been impossible. Voice assistants like Alexa and Siri could understand basic components of human language, but their speech recognition software and AI analysis tools were rudimentary. Thus, normal and fluid conversations were elusive.

Today, platforms like Bland AI are enabling people and businesses to harness the power of conversational AI. Bland’s platform enables any business or person to send and receive phone calls where an AI speaks to another person.

The use cases for conversational AI are infinite. From conversational AI chatbots to conversational interfaces for navigating websites, every single interaction between companies and customers will be personalized. People will feel connected to the brands they purchase, causing additional satisfaction, retention, and revenue. Plus, websites will lose the friction of forms and checkboxes and will answer customers’ questions on the fly.

To learn more about the history of conversational AI, its current use cases, some of the associated challenges, and the technology’s future, read on!

Historical context

Early versions of conversational AI - like interactive voice response (IVR) - enabled users to create pre-defined conversational pathways. Through automatic speech recognition (ASR), these systems could identify which pathway to send people on, thereby enabling customer service lines to bucket and solve problems. After, banks, telecoms, and health insurance companies adopted the technology, creating the classic awful phone experiences of today.

Later on, Siri and Amazon Lex emerged as popular voice assistants. They both used primitive AI models to recognize key phrases alongside early text-to-speech systems to output responses with high-quality audio. At the time, both systems signified incredible jumps in the evolution of conversational AI. Yet they could not still truly empathize, connect with, and converse with humans in a natural language. Chit-chat still evaded them.

One decade later though, OpenAI released GPT3, a new Large Language Model (LLM) for text generation. Suddenly anyone could generate text - based on any prompt - paving the way for truly conversational intelligence. The AI system could respond to what other people say. Even then though, GPT3 was so primitive that when connected to phones, it failed to output anything human-feeling.

Finally, just now, a new wave of conversational AI models has paved the way for truly human-seeming AI. As the generative AI model for speech, transcription, and inference all simultaneously improved, teams like ours at Bland AI could leverage the exciting advancements to build new conversational AI systems.

Current Use Cases of Conversational AI

Today, innovative companies are using advanced conversational AI to enable personalized and relevant customer experiences. Conversational AI applications are taking hold in healthcare, e-commerce, small business, and recruiting. Plus conversational AI tools are enabling industry-agnostic use cases like customer engagement and support.

Transforming healthcare, e-commerce, and every industry in between

Starting in healthcare, medical practices can automate the phone calls they make. From sending patients appointment reminders and enabling them to reschedule to automating phone calls to share referrals with other practices. Plus, health insurance companies will use AI phone calls to communicate with patient populations in the language of their choice, enabling better outreach and education.

Then in e-commerce, brands will offer phone numbers for customers to call. Such phone calls will enable customers to build trust in the brand. Websites can quickly answer customers’ questions and point them toward the right product offering. By helping customers find what they want faster, brands will increase topline revenue. After purchases, by sending check-ins and additional promos, brands can also retain customers on subscriptions and get them to make repeat purchases.

Going to small businesses, many “mom and pop” shops lose revenue due to unanswered phone calls. Using a conversational AI tool - like Bland AI - to create an inbound phone number enables such businesses to answer every call. By doing that, small enterprises can capture every single dollar, and drive purchases with their conversational artificial intelligence assistants. It’s vital that companies also provide the AI with all the information it needs - enabling capabilities from making purchases to updating hours, etc.

Finally, recruiters can use conversational AI chatbots to screen every applicant. After training their conversational AI on what questions to ask, recruiters can send screener calls to every applicant, to collect additional information, make sure their background fits the role, and decide whether the person is worth a second interview. This step will free up time for recruiters, drive better candidate experiences, and enable companies to deeply screen every applicant to find the diamonds in the rough.

For an in-depth breakdown of other conversational AI use cases, read this guide to AI phone calls.

Customer support and engagement

Every company needs a conversational AI strategy that includes aspects of support and engagement. Conversational AI platforms enable every enterprise to create AI voice agents who learn the company’s knowledge base and can resolve customers’ problems. Simultaneously such conversational AI solutions can power customer updates and notices to prevent churn and boost repeat purchases.

The trick with making conversational AI great, though, is in the actual knowledge base you provide it. When enterprises have large datasets of information about customers and products, conversational AI becomes way better. It can specify exactly what a user wants based on their taste. The virtual agent can also access and update customers’ orders, enabling them to get exactly what they need.

Bland AI offers an easy-to-use AI phone calling API, enabling any developer to send a phone call where an artificial intelligence speaks to another person. To learn how to create a conversational AI solution to your company’s needs - or more specifically build a conversational AI chatbot that engages your customers, read this blog from Bland.

Challenges of Conversational AI

The best conversational AI use cases are for enterprises to improve their customer interactions. However, bad actors have found ways to abuse the power of machine learning to scam innocent people by replicating their loved ones’ voices.

Scams using Conversational AI

Unfortunately, we’ve entered an age where cloning voices has become all too easy. Going forward, new entrants to the AI market will need to build solutions with guardrails to prevent scammers from using conversational AI for bad. That includes moderating the prompts to the AI, thereby ensuring that the underlying large language models cannot output harmful or offensive statements. Additionally, it includes preventing people from cloning and using voices at scale - except after receiving explicit platform approval.

How Bland’s Platform Stops Spammers and Scammers

At Bland AI we’ve implemented a rigorous set of protections to prevent our conversational AI platform from being used by bad actors. Our AI filters prompts and gains natural language understanding to classify malicious use cases, to ban those users.

Given the power and potential potency of AI phone calling technology, we take moderation and filtering seriously. AI will unlock a new frontier of human connection, and we must ensure that we mitigate all the potentially harmful use cases that come with it.

The Future of Conversational AI

As machine learning engineers pioneer new techniques in the fields of natural language processing and deep learning, a new wave of powerful AI applications will emerge.

One of the most exciting use cases will be AI experts, created using fine-tuned large language models. Pretty soon, virtual agents will become skilled at therapy, all types of coaching, and even at being friends and companions. People are already using Character AI, for example, to connect with characters from popular video games, technologists like Elon Musk, and psychologists to drive self-understanding.

It’s quite possible that in under ten years, peoples’ closest friends will Be AI; companions who intimately understand their lives, support them endlessly, and help them find their way through life.

Similarly, social media will be overrun. Human agent accounts; AI’s that either role plays existing people or create new identities, will provide entertaining content, new storylines, etc. that engage audiences and enable wholly new ways to tell narratives. Social media platforms like Instagram and TikTok will become playgrounds for AI. A virtual agent will emerge to tell any given storyline, while the rest of us watch from the sidelines.

Changing how companies interact with customers

Lastly, conversational AI over the phone will fundamentally transform every industry. As previously noted, contact center flows are awful for customer experience because they use arbitrary dialog management tools to force conversations down pre-determined pathways. Speaking to robotic, emotionless beings, after being stuck on hold for hours at a time is a painful experience that most people hate. By implementing virtual agents, for customer support and engagement, however, companies in every industry can better solve their customer needs and enhance customer experience.

Plus, because conversational AI systems can gain a contextual understanding of any situation, they will bring about intelligent automation to every system that humans currently play a role in. We’ll see a new era of conversational commerce, where every time a customer visits a website, a chatbot answers their questions and helps them make purchases.

Conclusion

Ultimately, as improvements in large language models enable better conversational AI, we’ll all feel the difference. Virtual assistants will take over all types of customer engagement, creating a new customer service team that enables a better customer experience for every website visitor.

Every industry from e-commerce to small business and financial services to healthcare will fundamentally improve; customer interactions will be fully personalized and increased at scale. Aside from driving down operational costs and boosting customer satisfaction, conversational AI will bring the human element back to many of peoples’ day-to-day experiences that lacked it.

To get started with conversational AI, and to learn how to add AI phone calls to your existing applications, you can learn more on our landing page for Bland AI.

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Serving sectors including real estate, healthcare, logistics, financial services, alternative data, small business.

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