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AI is leading the march of technologies disrupting the enterprise. Industries like healthcare, ecommerce and banking are embracing artificial intelligence because AI has proven to enhance employees’ productivity by simplifying monotonous office tasks.
However, there is a longstanding controversy around AI-driven technologies that can understand and perform more than humans in business processes. This is the premise of a recent report from voice software specialist Red Box, called “Being Human: How and why machines are learning the art of conversation.” The report surveyed a pool of business leaders in the U.K. and U.S. to learn how they used iterations of conversational AI, which comprises automated messaging and speech-enabled applications that personalize interactions with humans.
The world has witnessed the power of conversational AI, especially with virtual personal assistants like Amazon’s Alexa and Apple’s Siri. What’s most fascinating about digital voice assistants is they can work with different devices like smart speakers, smart speakers and smartwatches. As voice recognition technology continues to expand its reach, Statista projects the global market for voice recognition tech to reach $30 billion in 2026.
AI may listen better than humans in the coming years
One highlight from Red Box’s recent report is that 47% of the participants believe AI will be able to listen as well as, or even better than, humans. When asked how soon this will occur, 52% estimate ten years. Interestingly, a third of the respondents believe it will only take five years to happen.
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The rapid growth of AI in the workplace worries many workers and CEOs, especially because of job retention. There’s a common belief that companies will embark on massive layoffs because AI optimizes operational times and provides company decision-makers with deeper insights. It would seem that humans are no longer needed, but some experts say AI should complement human intelligence rather than replace it.
Providing exceptional customer experience
Bad customer service provokes customer churn, making companies lose revenue and positive feedback. From poorly trained customer support workers to the inability to solve issues using self-service options, the aspects of a poor customer experience go on for miles.
To scale productivity and portray a positive image, companies are utilizing AI-driven tools. The Red Box report said 28% of the respondents used conversational AI to optimize customer support. Almost a quarter of the respondents use it to offer agent assistance in real-time.
Today, businesses adopt AI in modern contact centers to interact with customers, define their inquiries and provide them with instant support. For instance, while a customer is on a call, the AI displays informative articles related to their inquiry. This saves operational time and effort for the human agent.
Improving employee experience
Employee engagement is a burning issue today. When employees feel disengaged, they’re unlikely to be productive in their roles and will shop for better working conditions elsewhere. It’s a key player in the great resignation crisis that has badly affected industries, especially hospitality and retail.
Recently, concepts like remote work and hybrid work have become an integral part of organizations. Companies are now portraying remote work availability as a workplace benefit, attracting top talents from the labor market. Furthermore, a Gallup report showed that providing a remote work option increases employee engagement.
While remote work promises advantages like flexible work hours and better work-life balance, managers now expect more work to be done. To enable employees to cope with these demands, some companies have started using AI-powered tools to handle repetitive tasks like recruitment and onboarding. The Red Box report reveals 30% of respondents have adopted this approach.
Improving fraud detection and risk management
The Red Box report found that 33% of the U.K.-based business leaders and 29% of the U.S.-based business leaders identify fraud detection and risk management as their major use cases of AI. Additionally, conversational AI is largely used in spaces founded on legacy systems, like finance and healthcare. Businesses operating on outdated legacy systems are highly susceptible to threat actors.
Companies also now use AI to enhance internal security by analyzing transactions and ultimately detecting fraud. Depending on the algorithms with which the AI-powered tool operates, it can flag suspicious transactions or deny them. This simplifies the fraud investigator’s job, allowing them to act promptly.
In risk management, an AI-oriented approach enables companies to analyze and manage threats faster. They can use ML algorithms to assess huge amounts of data — a method that generates many prediction models for risk managers to effectively handle risks with. Other use cases include data classification and risk reduction.
Problems facing AI and a proposed remedy
Despite the many business use cases, AI-oriented technology continues to face setbacks. The report said AI’s inability to completely grasp the nuances of human communication negates its efforts to understand emotion and sentiment. Other challenges indicated in the report include customer interactions across multiple departments and the use of jargon.
Adam Sypniewski, CTO at Deepgram, an automated speech recognition specialist, identifies the reason behind AI’s inability to learn the art of human conversation. According to him “most cognitive modeling is small-scale, often academic.”
However, he believes when organizations start thinking big and model their AI solutions on the customers’ cognitive state, such organizations will “build compelling voice experiences that could help customers and identify opportunities to improve.”
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