- The report noted that 28% of the participants used conversational AI to optimize customer support. Almost a quarter of the respondents said they use it to offer agent assistance in real-time.
- The Red Box report found that 29% of the U.S. business leaders and 33% of the U.K. business leaders identify fraud detection and risk management as their major AI use cases.
Among all existing technologies, Artificial Intelligence (AI) is leading the race, disrupting the enterprise. Various industries ranging from healthcare, banking, and e-commerce are embracing AI as it has proven benefits like simplifying monotonous tasks and enhancing employee productivity.
However, it has also invited many controversies about AI-driven technologies that may understand and perform more than humans in business processes. Recently, a voice software specialist, Red Box, published a report titled, “Being Human: How and why machines are learning the art of conversation.” The survey was conducted among a slew of business leaders across the U.S. and the U.K. to see how they used iterations of conversational AI, which includes speech-enabled applications and automated messaging that personalize interactions with humans.
Conversational AI is not new to the world, especially after virtual personal assistants like Amazon’s Alexa and Apple’s Siri came into existence. What makes voice assistants more fascinating is their ability to work with various devices like smartwatches, smart speakers, etc. With a surge in voice recognition technology, Statista projects that the global voice recognition tech market might reach USD 30 billion in 2026.
AI may be a better listener than humans in the coming years
One significant highlight from the recent Red Box report is that 47% of the participants believe that AI will be able to listen well or even better than humans. However, when the participants were asked about their views on how soon that will happen, 52% estimated it to be in the next 10 years. One-third of the surveyed people believe that it may take five years.
The rapid growth of AI in workplaces has worried many CEOs and employees, especially about job retention. It is a common belief that companies may lay off numerous employees 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 that AI should go hand-in-hand with human intelligence rather than replace it.
Offering top-notch customer experience
Several companies have lost positive feedback and revenue due to poor customer service. The aspects of a poor customer experience can range from poorly trained customer support workers to the inability to solve issues using self-service options.
Companies are making use of AI-driven tools to enhance their company image and scale productivity. The report noted that 28% of the participants used conversational AI to optimize customer support. Almost a quarter of the respondents said they use it to offer agent assistance in real-time.
Today, businesses adopt AI in modern contact centers to carry customer interaction, define their inquiries and provide them with instant support. For example, a customer on chat/call will be provided with informative articles or FAQs related to their query.
Enhancing employee experience
Employee engagement is a burning issue today. When employees feel disinterested, they are less likely to be productive in their roles and will shop for better working conditions elsewhere. This is one of the significant aspects of the great resignation crisis that has negatively impacted several industries, especially retail and hospitality.
Thanks to the pandemic, remote and hybrid work modules have become an integral part of organizations. Companies are even promoting the availability of remote work as a workplace benefit to attract talented people from the labor market. Further, a Gallup report showed that the remote work option increases employee engagement.
On the one hand, employees get benefits like flexible work hours and better work-life balance from the remote work module, managers now expect them to be more productive. To cope with such demands, some companies have started using AI-powered tools that can handle repetitive tasks like recruitment and onboarding. The Red Box report reveals that 30% of participants have already adopted this approach.
Improving fraud detection and risk management
The Red Box report found that 29% of the U.S. business leaders and 33% of the U.K. business leaders identify fraud detection and risk management as their major AI use cases. Conversational AI is broadly used in industries like healthcare and finance that are founded on legacy systems. Businesses that operate on outdated legacy systems are highly susceptible to threats and risks.
Companies also use AI to increase internal security by inspecting every transaction and detecting fraud. Based on the algorithms with which the AI-powered tool operates, it can flag suspicious transactions or deny them. Hence, AI simplifies the work of fraud investigators and enables them to act promptly.
The AI-oriented approach plays a vital role in risk management by enabling companies to identify and manage threats promptly. They can also use Machine Learning (ML) algorithms to evaluate big data – a method that generates many prediction models for risk managers to handle risks effectively. Data classification and risk reduction are other use cases.
Challenges faced due to AI and the proposed solution
AI-oriented technology faces setbacks despite the numerous business use cases. The report noted that AI’s inability to grasp human communication nuances negates its effort to understand human emotion. Other challenges include unnecessary jargon and customer interactions across multiple departments.
Adam Sypniewski, the CTO of Deepgram and an automated speech recognition specialist, identify the reason behind AI’s inability to learn and understand human conservation. He mentioned that “most cognitive modeling is small-scale, often academic.”
However, he believes that when businesses think big and models their AI solutions on the customers’ cognitive state; they will “build compelling voice experiences that could help customers and identify opportunities to improve.”