VoIP and AI: The Smart Future of the Desk Phone
Business telephony is on track to fundamentally change with the growth of Voice over Internet Protocol (VoIP) usage.
The global VoIP software market is expected to surpass $30 billion by 2025, with high adoption rates across the world. It has only accelerated due to the pandemic forcing industries to shift to remote work, leading to the global mobile VoIP market having a projected value of $183.7 billion by 2027.
In the UK, we are already set to switch off the country’s traditional phone network in 2025, transitioning every phone line to be digital and route calls via VoIP.
The ongoing evolution of phone technology toward VoIP comes with the integration of smart technologies — artificial intelligence (AI) and machine learning. In this article, we’ll go over the ways AI and machine learning will revolutionise phone communications.
Pre-Conversation Data Retrieval
VoIP enables businesses to retrieve important data from callers, such as identity, location, intent, and call history before a conversation even happens. Voiced AI can help callers through an interactive voice response (IVR) system to funnel them to the right channels, whether it’s to another AI or a human representative, using the collected data.
With predictive machine learning models, it’s also possible for AI to recommend to human operators the next best action based on call history and past conversations. Conversations can be significantly reduced, shortening queue times between callers, or they can be directed to upsell opportunities.
Enhanced Live Customer Service
AI can help improve the customer experience as a call is going by acting as a live personal assistant to human operators. It can perform rudimentary tasks for operators such as searching for callers’ personal data and past transactions, so conversations can continue uninterrupted.
AI can also go as far as performing real-time speech analysis to determine mood and intent based on what callers are currently saying and how they say it. With such information, AI can act as smart coaches to human operators on the fly, suggesting actions that would make for the best responses.
Real-time Translation
The advances in AI speech recognition are such that it’s possible for VoIP calls to have real-time translation of any language. By bringing down communication barriers with this technology, businesses that operate across geographical areas can greatly reduce costs that would include outsourced call centres and hiring multilingual customer service agents.
Currently, speech-to-text translation is a more viable solution, with automated voicemail transcription to emails and texts as standard processes. More resources devoted to machine learning development should soon make real-time speech-to-speech translation more accurate and responsive to be applicable for business calls.
Operations Optimisation
A great deal of customer enquiries can be addressed via automation. Frequently asked questions, common troubleshooting problems, scheduling of appointments, and ordering products can all be handled by voiced AI over IVR. Doing so would allow human operators to tackle nuanced tasks, reducing the cost of hiring and training just to be able to field simple calls.
AI has also advanced enough to take on more complex processes. It can book meetings, send invites, readjust reservations, and create itineraries based on data extracted from a caller’s speech and call history. Further development via machine learning will only expand the actions AI can achieve for even further task optimisation.
Call Recording Analysis
Recorded calls run through AI analytics can provide insights to improve transactions. Data from call transcripts and real-time speech recognition can be processed by AI to generate reports that evaluate customer satisfaction, agent performance, and trending issues, among a host of other valuable information.
Machine learning would allow AI to go through vast data sets collected from calls to recognise behaviours and patterns, identify key phrases, and highlight coaching opportunities. The more data collected for AI to process, the better it will get at taking such actions, which in turn would make for more accurate predictions of future customer engagements. The better AI is at predictive analytics, the more tailored the customer experience will be for maximum engagement.
Improved VoIP Security
The digital nature of VoIP means it can be targeted by hackers. Machine learning would work toward stopping such cyberattacks, improving over time with more data to process to keep apace with advances in VoIP hacking. AI can be trained through software testing techniques such as functional protocol testing to detect bugs in VoIP systems that could be exploited.
Other malicious behaviours that machine learning AI can be trained to detect and prevent include eavesdropping, caller ID spoofing, phishing, and audio injection. Hacked VoIP calls can drain resources quickly through a long sequence of short calls or take up capacity by redirecting legitimate calls to hackers. It would be worth the cost to invest in AI to improve VoIP security compared to the expenses and loss of trust resulting from cybercrime.
Preparing for the Future
The move from landline phones to VoIP is inevitable, especially in the world of business telephony where companies are dealing with the great transition to remote work and are looking for every competitive advantage to deliver superior customer service. The future tech of AI and machine learning perfectly complement the growing adoption of digital phone networks. In fact, it is projected that AI will power 95% of customer interactions by 2025. Businesses that recognise the oncoming change today are certain to gain the upper hand tomorrow.
Be ready for the future of corporate communications by updating your business’ IT and VoIP phone network with Evolvit. Contact us today to schedule a consultation.
