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With the rise of cloud communications, voice calls using the internet have prospered. Voice over Internet Protocol — or VoIP in short — has existed since 1995 and its significance to the way communication evolved through time is often overlooked.

For the general public, the ins and outs of VoIP may be vague. To put it simply, VoIP services use packet switching wherein the voice gets converted into a digital signal as it travels over to the receiving end. If you had WhatsApp calls and Zoom meetings or made any call via the internet, you’ve used VoIP. Wireless hot spots in locations such as airports, parks, and cafes may enable you to use VoIP service, depending on the speed and stability of the connection.

For enterprises, if VoIP seems like unchartered territory, it is worthy to consider what you would need from a provider. These can include call management and customer service; compliance and security; and support and integration.

Because it’s based on the cloud, VoIP is far more open to expansion than a traditional public switched telephone network (PSTN) line. As companies continue to demand greater flexibility in their voice communication systems, VoIP providers aim to be the best route forward. With new technological developments such as artificial intelligence (AI) and machine learning (ML), modern business telephony is transformed.

How AI/ML work in telephony

VoIP service providers are now introducing new features in VoIP services to attract users at both individual and corporate levels. With the surge of demand for international calling and incorporation of AI/ML, new market avenues are likely to open.

The telecom industry, in general, is growing at a fast pace. Hence, growth and innovation are also taking place in the VoIP setting as service providers offer advanced features for more convenience, reliability, mobility, productivity, and flexibility to end-users. Meanwhile, poor internet connectivity and power outage are some of the main factors that may hamper the growth of VoIP services in the global market.

According to Persistence Market Research, the global VoIP services market is likely to witness substantial growth, estimating $194.5 billion in revenue towards the end of 2024. VoIP providers are in a race to stay competitive. This is the reason why artificial intelligence has become an integral part of numerous functionalities within VoIP and business phone services. Essentially, whoever brings the most rewarding element will probably become a client favorite.

  • Conversational AI

One of the restrictions between machines and humans is the capability to understand the context and structure of language. With more advanced AI technology nowadays, the machines are trained to figure out what has been said through word-to-word processing.

Bringing conversational AI to life, this synthetic brain stimulates understanding, processing, and responding to voice data within machines. Natural language is context-dependent, and considering background noise, unusual speech patterns, and individual pronunciation, it’s quite challenging. Nonetheless, AI has made it possible by harnessing the computational power of the cloud. Siri, Cortana, Alexa, and Google Assistant are perfect examples of this.

Leveraging AI in real-time for several types of customer conversations hugely optimizes engagement and amplifies interaction. These can include offering suggestions as machine learning models conduct emotional analysis of customers and taking care of simple tasks such as FAQ, password resets, appointments, refund requests, or reservation adjustments.

  • AI transcription: speech-to-speech/text

In a customer service scenario, with a speech-to-speech translation model like Google’s Translator, calls in any language could be answered by a suitable agent. This makes customer care handling across borders easier and without delay whilst cutting the cost of building new call centers or hiring multilingual individuals.

Such models require more progress in the domain of machine learning for highly accurate translation. Turning speech into text is also one of the most clear-cut applications of AI voice processing in VoIP systems. Among the standard business VoIP features are voicemail-to-email and voicemail-to-text. This is helpful as messages get transcribed when callers don’t reach the person they were hoping to talk to. As an automated response, the transcript will be sent to the inbox of the concerned person.

Saving more time, AI can transcribe entire conversations and file them away for future reference. This can be incredibly handy in handling disputes or follow-up with clients. Another scenario is upon conducting interviews. With real-time AI translators, the voices are recognized on top of any ambient sound for precision.

  • Intelligent call routing

Another use of AI-powered business telephony tools is intelligent call routing (ICR). This is where businesses can avoid the initial unhappy customer aggravation condition, thanks to Interactive Voice Response (IVR).

Instead of forcing a caller to listen to a long list of options, IVR allows them to state their call’s purpose in their own words. This will give the AI an opportunity to discover the underlying intent of the caller and transfer it to the befitting representative available. Smart auto-attendants can prioritize calls with high urgency by classifying them by topic, reducing any unnecessary human agent interactions to increase the output capacity. This allows actual employees to focus on more complex requests.

To enhance the call routing process, leading VoIP providers are fully aware of the potential of AI integration. With a myriad of factors involved in optimizing the routing of countless calls, the call performance and quality data associated with the process can be handled by this technology to the full extent. As AI/ML evolve further in the coming years, we can expect to see implementations that automatically optimize routing and generate smarter results.

  • Predictive analytics

In the case of human-to-human conversations over a VoIP connection, many companies filter callers through an IVR system. A programmable voice AI is responsible for translating a voice command or button selection. Without a doubt, VoIP AI analytics allow deep insights into customer behavior. They can further predict their future engagement with the company, buying decisions, or communication patterns.

On the other hand, when a human operator receives a call, ML models can also make real-time inferences about caller intent. From the picked-up audio, insights can be reflected on-screen to help improve the interaction. This is particularly useful for customer service, sales calls, and support applications where one of the KPIs may be to keep short conversations to avoid a long queue or to identify responses that drive high-end opportunities.

Implementing predictive ML models can put forth the “next best action” (NBA) and help find patterns based on historic data and ongoing conversation characteristics. This can determine which actions are most likely to affect and lead to the desired outcome. Call transcripts can be combined with other collected data such as feedback forms or reviews.

  • Call data processing

When conversation intelligence is continually used on VoIP, AI can keep learning and be more familiarized with the data involved. Using the data backlog, including conversations and solutions derived from voice calls, AI can be trained to answer in a specific manner — with fewer errors in due time.

This can be particularly helpful if an AI discovers a surge of one specific question or a range of questions on a specific topic. Setting up automatic responses using virtual assistants or building better decision trees for IVR can be suggested. In the case where businesses store the call recordings on the stack, a conversation intelligence system can be used to audit the calls for specific entities or keyword phrases or censor any sensitive data.

Speaker separation and identification are an important part of building a robust ML system for VoIP. Some off-the-shelf conversational AI APIs or open-source models can be utilized on both voice and text data simultaneously.

Concluding observation

VoIP is definitely a lucrative way enterprises can tap into. As a wide variety of communications features escape the high cost of landlines, the digital world becomes more ideal for verbal conversations as well. Businesses of all sizes adopt this upgraded technology. Thus, many are discovering the potential that VoIP has when combined with AI.

AI/ML and VoIP carry out more benefits when brought together, serving customers better and improving efficiency. An AI-powered VoIP system can go beyond delivering voice calls. Other features like video conferencing, screen sharing, instant messaging, and live chat, can be linked to help organizations streamline communications and boost teamwork.

As more enterprises adopt UCaaS to consolidate their communication needs into one centralized platform, VoIP providers will develop more AI/ML-powered features to enhance team collaboration, content sharing, and meeting support to attract business users.

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