For over a century we have been using machines, and as technology has advanced, they have taken on an increasing role in our lives, carrying out a variety of daily tasks. Today, it is safe to say we are even dependent on many things on machines designed to act intelligently.
Nevertheless, when people hear the term “artificial intelligence,” the instinctual reaction is still one of confusion, concern, and even fear.
For over a century we have been using machines, and as technology has advanced, they have taken on an increasing role in our lives, carrying out a variety of daily tasks. Today, it is safe to say we are even dependent on many things on machines designed to act intelligently. Nevertheless, when people hear the term “artificial intelligence,” the instinctual reaction is still one of confusion, concern, and even fear.
No doubt part of the fear of AI has been implanted by Hollywood and science fiction, which has perpetuated a generally negative association of AI that keeps us in fear of the future, one where machines copy intelligent human behavior until they become even smarter than humans, eventually becoming the ultimate threat to our very existence (see “the Matrix”). In fact, according to a survey conducted by Chapman University regarding Americans’ fears, technology ranked as second-highest on the fear scale, while 22% of those surveyed feared artificial intelligence specifically.
The truth is, some form of applied AI is already at work in a vast number of applications that are useful in virtually every field. However, what is important to remember is that a machine is still ultimately just a piece of equipment made up of various parts that work together to perform a function when given the power to do so. Similarly, regarding the powerful and complex algorithms of “neural networks” that are fueling machine learning applications, and which work to classify information in the same way a human brain does. There were actual people that created and programmed the algorithms, devising the logic and steps the machine requires to carry out the given tasks.
AI and Customer Service
Today, one of the main fields beginning to reap the benefits of new AI technology is customer service automation. In fact, one of the predictions in Gartner’s Customer 360 summit was that by 2020, customers will manage 85% of their relationship with enterprises without interacting with a human!
In the meantime, as customers voice their complaints across all channels, via phone, email, online chat, and social media, etc., companies are struggling to respond quickly enough to their customers on all fronts. In fact, according to Accenture, businesses are losing $1.6 trillion annually due to poor customer service, so a new digital IT strategy is a pressing issue for many brands.
Artificial intelligence allows companies to respond to customers faster and with more accuracy. Instead of agents needing to memorize company’s customer policies and promotions, while sifting through multiple databases looking for relevant customer information and processing it, all while on a call with the customer, computers utilizing machine learning applications can now understand a customer’s question, quickly search its memory banks, and give the best, most accurate, answer. However, answers are not just pulled from a database. It’s cognitive, meaning it can comprehend the sentiment and nuances of the request. How? The vast amount of customer data that is collected by companies is used essentially as a “knowledge base” for an AI system. The more data you feed the AI system, the more it learns from the data, the more patterns it recognizes, and the more effectively it can communicate and handle customers. By sensing or being told whether its answers are right or wrong, it alters the approach it takes in the future, so its accuracy is always improving.
Furthermore, to keep up with the massive growth of messaging channels, companies can leverage artificial intelligence to meet the rising volume of support requests, while also supporting increased demands for speed of response and accuracy. In fact, customer service is the first industry already seeing the massive benefits of such change management. By deploying both messaging and AI together, companies can scale a customer service operation, connect quickly to more customers, while also cutting customer service costs.
The truth is, despite the speculation that AI chatbots will completely replace humans in call centers, there will always be those customers who need the human touch. The successful companies will be those that use chatbots to help agents take care of those tasks that can be easily automated, such as helping to make an online transaction or looking up a customer’s order status. As a result, AI support can ideally provide what customers need before they seek out human support. If not, it can at least route the right messages to the right people, helping customer service reps to prioritize their responses, and thus leading to increased sales and customer engagement opportunities for brands.
With the clear benefits AI offers companies, its integration into everyday IT operations is only going to keep growing, and by leveraging its capabilities to match increased customer service expectations, brands can now reap the benefits of this changing digital landscape. That is nothing to be afraid of!
[About the author] Dylon Mills is the Director of Marketing Content Strategy & Development at Jacada. As such, Dylon’s main responsibilities are to strategize, create, and deliver content for Jacada’s product portfolio that aligns with the global Go-To-Market strategy, corporate positioning, and marketing campaigns. Dylon’s prior work experience includes Product Management at one of the top Fortune 500 Technology companies, Symantec Corporation. Outside of work, Dylon enjoys problem-solving and any project that includes building/tinkering with tools. Dylon holds a BS Consumer Economics from the University of Georgia.