BotsCrew's Co-founders On What Is Voice AI & OpenAI's RealTime Voice API

Before OpenAI's RealTime Voice API, businesses were stuck with manual, clunky processes that slowed operations, frustrated customers, and drained productivity. Workers had to stop tasks, search through systems, and wrestle with outdated voice tech that barely understood context.

With OpenAI's RealTime Voice API, all that has changed. Businesses can empower their teams with fast, accurate voice assistants capable of real-time, dynamic responses. 

Workers get what they need — whether it's inventory details, customer data, or even step-by-step guidance — instantly and hands-free. Customer calls are resolved faster, operational workflows are streamlined, and businesses can focus on innovation instead of inefficiencies. It's a whole new era of seamless, voice-driven interactions, and companies are finally stepping into it.

✅ What is voice AI, Before vs After OpenAI's RealTime Voice API: what's changed?

✅ Why OpenAI's RealTime Voice API is a game-changer.

✅ How to use voice AI: real-world use cases.

✅ Why AI still needs a human.

✅ How we all need to change our perspective on AI to maximize its potential.

What's the buzz about the new real-time API? Once you try it, it is a whole new ballgame. This update brings a seamless experience — no more clunky, frustrating delays. So, what's improved?

— Effortless Speech Adaptation. The API now adapts to different speech speeds effortlessly. You can talk fast or slow, and it keeps up without skipping a beat. Furthermore, you can now interrupt it — just like in a normal conversation. Imagine you are mid-answer and realize it's off track. You can say, "Wait, no, that is not what I meant," or add more info on the fly. The API stops responding immediately. It's a vast improvement from the previous versions, where you had to wait until the response was over or deal with that awkward silence.

— No More Friction. The most significant improvement is the elimination of friction. For global agencies and businesses, it genuinely feels like a conversation with a human because there is no delay.

— Customizable Tone and Style. Developers can fine-tune the AI's tone, style, and voice persona to fit their brand identity or create unique conversational experiences. Whether you want a professional tone for customer support or a fun, friendly voice for a customer service chatbot, it is easy to adapt.

— Multi-Language Support. The API now supports over 50 languages, covering more than 97% of global speakers. Businesses can handle conversations in different languages without switching APIs, expanding the potential for global engagement and accessibility.

— Developer's Dream: One API, Endless Conversations. Developers no longer need to piece together multiple APIs for voice-to-text, generating responses with an LLM, and converting text back to speech. Now, there is just one streamlined API — voice in, voice out. And it works incredibly smoothly.

The new API bridges the gap between human conversation and AI interaction like never before, making it easier and faster for everyone — experts and newcomers alike.

When it comes to the new real-time voice API, what are the immediate, low-hanging fruit use cases? Which practical applications can businesses start leveraging right away?

Many businesses are surprised to learn that up to 70% of customer service inquiries are fundamental questions. Whether you are a large corporation or a small business, it doesn't matter. This API can automate inquiries beyond the basic "What are your hours of operation?" Instead, it can handle more complex queries that require third-party data, like "What's my order status?"

The experience remains seamless, even when making real-time API calls to external systems. There is no delay and no breakdown in conversation flow. This makes customer service automation a no-brainer for businesses.

Obviously, it's available 24/7. Imagine your customers calling after hours and getting immediate, professional responses instead of a voicemail saying, "We'll be back at 9 a.m. Monday." Whether it's a broken refrigerator or urgent assistance, 24/7 voice AI solutions ensure customers aren't left waiting over the weekend.

Another possible use case is in financial services and identity theft scenarios. Imagine you are a victim of identity theft and need to call multiple banks and financial institutions to explain the situation. Hours usually spent on hold, followed by a human filling out a form and emailing you a response. Automating these simple interactions would free up agents to handle more complex issues. For those looking to safeguard themselves, Cybernews has compiled a list of identity theft protection services that can help detect and prevent fraudulent activities.

However, banks are often cautious about adopting voice automation. There is a fear that personal details could be misheard or misinterpreted. Yet the current process of customers waiting 40 minutes on hold just to listen to hold music isn't acceptable. Therefore, it's time to start thinking about voice automation with real-time API. Some banks have  succeeded with chatbots — Bank of America, for instance.

One of the key areas where it can be a game-changer is in jobs that require hands-free operation. For example, in warehouses, workers often have to manage physical tasks like picking up items while also needing information, such as the location of products. Instead of having to stop what they’re doing to check their phones, they could use a voice assistant to get the information they need in real-time, all while continuing their work.

Similarly, in jobs like car repair or construction, workers often need to look up instructions or tools while physically engaged in the task, and doing so without taking off gloves or handling a device is crucial. A voice based conversational AI can provide an easy solution, reducing interruptions and increasing safety. This idea isn't just for convenience but also critical for safety, especially when workers need to access information while performing high-risk tasks.

Looking ahead, the combination of augmented reality (AR) and voice AI solutions could take this further, especially in hazardous work environments where instructions need to be delivered on the spot. For instance, AR glasses could help workers by projecting instructions or guidance while a voice based AI assistant explains what needs to be done, reducing the chances of mistakes.

Voice AI is rapidly becoming an essential tool across various industries. As this technology evolves, businesses need to be proactive and experiment with these solutions to stay competitive.

While real-time voice based AI technology shows a lot of promise, there are still a few challenges that businesses should consider before diving in. Let's break them down:

🤔 Use Case Selection. Not all use cases are suited for automation. While conversational voice AI is excellent for capturing lead details and answering basic questions, it may not be the best option for sensitive or complicated inquiries. Businesses should carefully choose which scenarios to automate and which to leave to human agents.

🤔 Pricing concerns. According to OpenAI's current pricing model, charges are based on the number of tokens processed. What that looks like in actual terms:

This adds up to about $15 per hour of conversation, which is comparable to minimum wage. This cost can catch businesses off-guard, especially if their interactions become more complex or lengthy.

However, OpenAI and other AI providers are constantly refining their models to reduce computational costs. Therefore, the cost is likely to drop over time. 

Today, the AI processes a lot of tokens, which drives up costs. Future improvements could reduce token usage while maintaining quality, making it more affordable. 

Furthermore, with players like Google, Amazon, and emerging startups in the AI space, OpenAI may need to adjust pricing to stay competitive. Lastly, as more companies integrate AI-driven voice solutions, higher demand leads to lower costs. Large-scale adoption often results in bulk pricing models or tiered discounts, making it more affordable.

🤔 Customer Experience Concerns. Voice based conversational AI can be frustrating in certain situations — especially if customers are calling in an emergency or have urgent, high-stress needs. To avoid negative experiences, businesses should clearly communicate that an AI is answering the call or ensure the AI's responses feel natural and transparent. Human follow-up should be offered quickly for cases that require escalation or more complex handling.

🤔 Balancing Automation and Personalization. For businesses that rely heavily on customer relationships, ensuring a personalized touch is critical. AI should enhance — not replace — the human touch where it matters most.

🤔 Slower Performance with Complex Integrations. While the voice-to-voice model itself can be high-speed, performance starts to degrade when third-party API integrations (like fetching weather data or order statuses) are too slow. This delay can ruin the seamless user experience that real-time voice interactions aim to provide.

*Whether you are new to Voice AI or looking for actionable insights, check our full podcast episode packed with ideas, real-world applications, and a hands-on demo to get you inspired.

When discussing voice AI solutions, big companies like banks have the resources to invest. But what about small businesses? Is it a smart move for them?

For small business owners who still answer the phone themselves or rely on a receptionist, voice based conversational AI can be a game-changer. It can:

— Improve call answer rates and provide faster lead capture. Local ad platforms like Google Maps and other local directories prioritize businesses that quickly respond to customer inquiries. If calls go unanswered or are delayed, businesses risk being deprioritized, leading to fewer inquiries and reduced visibility. Conversational voice AI eliminates these risks by providing instant, reliable call handling.

— Collect lead information. The voice AI can capture critical details such as the caller's name, phone number, location, and service needs during the call, ensuring no information is lost or overlooked.

— Schedule appointments based on customer needs. Businesses can automate appointment bookings directly through voice based AI, streamlining the customer journey without human intervention.

This allows business owners to focus on their work, whether on-site with customers or handling other tasks, without the stress of answering every phone call. Additionally, small businesses often cannot afford to have staff available around the clock to answer calls, leading to lost leads after business hours. AI voice chat provides a powerful solution by enabling 24/7 customer service. It ensures that customer calls are answered at any time, whether it's midnight or a holiday.

Voice AI doesn't need to be custom-built by the business. Many products are already launching with real-time API integrations to simplify the process. For example, conversational voice AI can be connected to a second phone line or directly to the business number.

The AI can also be trained using existing business data, such as website content. Some solutions even allow businesses to post a link to their website, enabling the AI to “learn” the company's details and provide accurate responses to customer inquiries.

For companies looking to integrate AI voice chat, the first step is understanding the specific business problem they aim to solve. It's crucial to start small, focusing on areas where voice technology will provide the most benefit.

Once you've identified a few opportunities, the next step is conducting a discovery phase, where you analyze the current process and figure out how voice can enhance it. From there, building a proof of concept allows you to test the idea in the real world. 

The feedback gathered from early users in this phase will be invaluable in refining the solution. Real-world testing and iteration are essential in making sure the technology works as expected. By getting the product in front of users early and gathering feedback, you can spot any issues or opportunities for improvement that may not have been obvious initially.

When considering the use of AI in voice-based services or other areas, it's essential to strike a balance between what can be automated and what should be handled by humans. Some areas where AI, especially in its current state, shouldn't be fully applied include:

1️⃣ Outbound Sales. While AI can help with lead generation and handling initial inquiries, fully automating sales calls or outbound marketing through AI may lead to a negative customer experience. People generally dislike receiving unsolicited calls, and while AI can be efficient, it can also be intrusive, particularly in outbound contexts.

2️⃣ High-Stakes Decisions. When it comes to significant investments, like mortgages or real estate, people tend to prefer human interaction. While AI can handle initial queries or data intake, the emotional aspect of such decisions makes it hard for AI to replicate the trust and nuance provided by a human expert. For instance, purchasing a home without physically seeing it or talking to a human feels too risky and personal for most buyers, even if AI is involved in showing properties through virtual tours.

3️⃣ Emotional and Complex Interactions. AI can handle structured tasks like providing information, booking appointments, or answering frequently asked questions. However, for scenarios that require empathy, judgment, or understanding of subtle emotional cues (like in customer service or therapeutic settings), AI struggles to deliver the same quality of experience that a trained human can provide.

Even as VR, voice based AI, and automation improve, the personal touch will still be needed to ensure confidence and trust in major decisions. Voice automation is far from eliminating human agents  — especially when there is high emotional or financial investment involved.