Voice AI: The CX accelerator you can’t afford to ignore
The need to implement Voice AI and digital solutions are now imperative to be competitive.
If the past few years have taught us anything, it’s that human talent is a precious commodity – and it’s a crime to waste it on repetitive, thankless and mind-numbing work.
Many companies have learned this the hard way as “the Great Resignation” has rippled through their ranks. A Microsoft study found that over 40 per cent of the global workforce were considering leaving their employer within the year. And it’s not all about the money; employees cite job insecurity and failure to recognise performance as key motivators for moving on to greener pastures.
As good talent becomes harder to find, companies are going to great lengths to keep their existing workers on board – expanding the use of hybrid work and investing in employee well-being, among others.
More companies have also found the answer in automation: not to replace existing workers, but to free them for higher-value work within the organisation.
A recent BCG/MIT study found that 90 per cent of large companies were already using AI-driven automation solutions to drive gains in customer service, with 70 per cent of respondents reporting up to a 10 per cent increase in revenue as a result. Tellingly, over two in three respondents saw potential in voice and chatbots “to personalise customer communication and can even reduce operating costs by two or threefold”.
Automation driven by Conversational AI (technology that enables human-like voice interactions between computers and humans) is making considerable progress in the business world, though its adoption has not yet caught up with other non-voice technologies like robotic process automation (RPA).
For starters, individual companies do not have access to the massive data sets required to train native Conversational AI bots from scratch. Most customer automation resides inside corporate data centres, siloed across departments in different places and formats.
Secondly, the deep learning that works so well with numbers and chess moves falls flat when trying to understand human conversation. “Words are arbitrary symbols,” explains MIT Technology Review’s Will Knight. “Two words can be similar in meaning while containing completely different letters, for instance; and the same word can mean various things in different contexts.”
Machine learning algorithms must understand context as well as sentence structure (“I made her duck” means different things in different contexts) and decipher sarcasm, humour, and other quirks of language.
Today’s Conversational AI technology has tackled both problems head-on with significant success. Advances in natural language processing (NLP) algorithms have improved Conversational AI’s ability to decipher and interpret speakers’ words and intent. AI-driven conversations now sound more “natural” and can go beyond the stilted “yes/no” inputs of previous chatbots.
In short, Conversational AI can communicate almost as a human might do – it understands the spoken word, can decipher the speakers’ intent, and provide spoken context-appropriate responses.
It’s only a matter of time before automating voice calls using Conversational AI becomes standard in most businesses – with an eye to reducing the load on human talent, and making them available for higher-value work within the enterprise.
Consider how much of business-to-consumer voice communication is rule-based and repetitive, where customers ask simple questions or confirm information; or where agents call to issue payment reminders. These rule-based calls can be automated with Conversational AI, and escalated to human agents for high touch interactions. Accenture finds that Conversational AI can reduce low-end, repetitive tasks by 20 per cent—a full day’s worth of work per week.
Furthermore, automation can also address a hidden hazard in call centre work: the toll taken by emotional labour, or regulating one’s emotions to perform the job well. Worker performance can be compromised by hours upon hours of dealing with disagreeable, challenging customers; no wonder call centres report alarmingly high turnover rates of up to 45 per cent.
Instead of putting humans through the wringer, businesses might call on Conversational AI bots to converse with customers, allowing human talent to simply monitor the call from a distance. AI bots are also unlikely to get tired and snappy at customers, removing another customer-service risk.
With Conversational AI doing the “heavy lifting” of talking to high-volume, low-value, challenging clients, agents can easily exceed customer service KPIs – engaging and supporting higher-value customers and feeling more fulfilled on the job at the same time.
As voice automation helps to keep employees happy, companies will also start to see the long-term benefits gradually over time.
Automating conversations can reduce the average cost per call, in more ways than one. Automated voice bots can field calls 24 hours a day, seven days a week, increasing output without a commensurate increase in personnel overhead.
Bots can also gather information from callers, and send that data seamlessly to connected CRM or ERP systems. Product registration, insurance policy verification, and customer authentication (among others) can be done by Conversational AI, but outperforming human agents in speed, efficiency and accuracy.
Automated Conversational AI can also easily handle overflows in customer call volumes. Customer service teams can rely on AI voice bots to take on low-value calls, relieving human agents during sudden increases in volume. And unlike human agents, Conversational AI can easily categorise calls based on customer needs, and automatically respond based on the customer’s intent.
As technology advances in intelligence, businesses can depend more on AI to assist in their day-to-day tasks. Automating voice conversations, while late to the game, is making up for lost time. Voice bots now take much of the drudgery out of call centre work, allowing managers to allocate more meaningful work to human talent without compromising revenues and the quality of their output.
Today’s Conversational AI is now a convenient, transparent, turnkey solution for companies that desire greater efficiency without taxing their talent. Voice AI platforms like AI Rudder learn from an ever-growing database of interactions, delivering higher-quality interactions, smoother communications, and a more human-like experience for their customers.