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CNNMoney, citing a PwC report, declared that 38 percent of USA jobs will be lost due to robots and artificial intelligence over the coming 15 years. Jobs that perform routine, repetitive tasks and are in industries include manufacturing, banking, education, retail and hospitality. The same warning bells are being rung by The Economist, New York Times, The Guardian and others. The World Economic Forum cites a “net loss of over 5 million jobs by 2020 in 15 major developed and emerging economies.” The mainstream media headlines around automation related job loss are akin to Chicken Little’s warning that the sky was falling. The sensationalism overstates reality. The impression is that job loss due to automation is a recent phenomenon. It’s not. The ATM was created in 1967 and has taken over 30 years to evolve into what we take for granted today. Did it significantly reduce bank teller jobs? Yes, over a long period of time. But it did not eliminate the position; it evolved. There are countless examples of how technology has changed economies, professions and industries. This has been going long before the steam engine and electricity was invented. The pace of technological change today is, however, increasingly faster. PwC’s 15 years forecast for job loss is challenging to believe when we look at the reality of what it takes to implement artificial intelligence. Spoiler alert - our ability to forecast the timing of future events with a measurable degree of accuracy isn’t particularly good. Rurik Bradbury, Head of Research at LivePerson, a mobile and online messaging company, has a different perspective. “The prospect of replacing entire jobs with just technology is unlikely,” shares Bradbury. “There is a lot of confusion about AI with more talk than actual deployment.” Today’s artificial intelligence technologies are capable of performing tasks at the atomic level. These are very narrowly defined tasks that operate within a clearly defined set of responses. Based on LivePerson’s customer experience, Bradbury strongly believes that AI can perform, on average, 40 percent of the tasks comprising customer care jobs. In other words, AI driving the level of unemployment forecasted by CNN within the next 15 to 20 years is unlikely. Even if we just focus on customer care jobs across all industries. Here’s why. Jobs are comprised of a multitude of tasks as well as a wide range of problem solving situations that require lateral thinking and complex, emotion-based human interactions. Bringing in AI to a customer support position, for example, requires the job to be broken down into its detailed components. On average approximately 40 to 50 percent of tasks in a call center are good candidates for automation. These are tasks that a call center agent or manager can trigger – updating your address, for example. The dialog between the AI and the customer is controlled by how the AI application is programmed and closely measured with human oversight. AI does not run without tight controls in place. The analytics include sentiment analysis that tells management which AI-conducted customer interactions were positive or negative. Negative interactions can result in shifting that task back to a human or reprogramming the AI software. AI doesn’t replace workers; it augments their ability to be more effective and productive. That doesn’t mean that the nature of work will not change, it will. The operative word is augmented – Bradbury calls it “job sharing.” Routine, data-driven, narrowly defined subtasks will be automated freeing the human worker to engage in higher level, most sophisticated tasks such as creative problem solving, strategic thinking and relationship building. The latter being things humans are much better suited for. Based on Bradbury’s research and LivePerson customers’ experience, the rate of AI taking over human tasks is slower than popular media would lead you to believe. First, to effectively employ AI to drive a positive, productive customer experience requires a clear plan based on gradual automation over time. Secondly, the current rate of automating tasks is one percent a year. In the case of the 40 percent of call center agent tasks that could be candidates for automation, companies would be extremely hard pressed to achieve that level of automation within ten to fifteen years. So much for predictions. That doesn’t mean ignore artificial intelligence. Approach it with a solid plan based on best practices. Here are a few of Bradbury’s suggestions:
- Collect a data set of good (read: successful) customer interactions and categorize them, identifying the most frequent interactions.
- Pick candidates for automation based on opportunities to improve the interaction. Start with a very small group of interactions to experiment with.
- Take a subset of these identified interactions and create a chatbot or AI interface that is specific to the atomic task being automated. The more granular the definition and automation of the task, the higher the success. 70 percent of current AI tasks fail because they are too general.
- Put the AI task into production aside a team of call center agents and test. That means collect data, perform A/B testing, and analyze the conversations and their outcomes. Evolve the AI software over time based on the results of the analysis.
- As success is realized, automate additional tasks based on the same testing and analysis approach. Set performance thresholds for each AI task. Keep in mind that AI applications work in tandem with employees and need to be orchestrated are part of a company’s ecosystem.
Journey mapping is a core discipline and competency of leading organizations. No longer considered a marketing or customer success initiative, leaders are realizing that everyone benefits from understanding journey maps and how they can be acted upon. And by ‘everyone’ I mean everyone – from Finance to R&D/Engineering to Facilities. Directly or indirectly, every job contributes to measurably delivering a consistent, valued customer experience. While the concept of sharing journey maps and coaching employees on how to operationalize journeys in their jobs is widely agreed to, implementation typically meets with resistance. Common objections include:
- The maps will get into the hands of competitors.
- Employees aren’t interested and won’t understand.
- Being challenged by peers on the process, results and recommendations.
- It takes too long to explain how and why specific touchpoints should change.
- Belief that any process changes just need to be implemented in IT systems and applications.
- Develop internal audience-specific versions of the journey map(s).
- Socialize journey maps through multiple channels.
- Develop and share interactive versions of the journey where people can explore and learn about journeys at their own pace and through their own perspective. This enables people to drill into the details or not – consider using a 3D tool like Kaon and check out Genroe’s review of journey tools.
- Host open lunches or breakfasts to help team members understand the journey, how they can impact customer delight and what alignment would look like. Use these sessions to address skepticism and gain buy-in.
- Bring customers in (virtually or in-person) to talk through their experience and how they define value-add, preference and intent. Building a bond between internal employees and customers is crucial to not only successfully implementing change but to maintain alignment with customers’ evolving expectations.
- Define a phased roll-out plan.
A bad review.
Here is a story that outlines some common mishaps that can occur when communication breaks down between a host and a guest, and a simple solution that can change the outcome for the better.
A Common Scenario
Gary, a recently retired professor, is excited about his upcoming travel and his first Airbnb! After booking his reservation, Gary isn’t sure the reservation is confirmed since Huey, the Host, never sent him a confirmation email or thanked him for the booking. Nonetheless, Gary isn’t too bothered and looks forward to his travels.
Travel day is here and Gary finally arrives to his Airbnb destination. He seems a bit confused seeing many parking spaces and tries to remember if Huey ever provided parking details. Gary sees a few empty spots in the parking lot and decides to park in one of them. As Gary begins to remove the luggage from his car, a neighbor approaches him. The neighbor explains that Gary has parked in his parking space. Slightly irritated, but trying not to let it spoil his trip, Gary puts the luggage back in his car and drives to a different parking spot.
Standing in front of the home, Gary rings the doorbell. After waiting a few minutes, he looks around to see if Huey may have left the keys in a lockbox or maybe inside the planter. No lockbox, no keys. Gary decides to call Huey, but there is no answer. Gary is now beginning to get anxious and kicks the front doormat in frustration, when he happens upon the door key which had been hidden beneath it. Gary uses the key to enter the home.
Gary is a tired from his travel thus far and hopes the remainder of his stay goes more smoothly. The home looks nice and Gary is excited to email his friends back home to tell them about his Airbnb adventure thus far. Gary turns on his computer but can’t seem to connect to the internet. There are multiple Wifi signals available, but all require a password to gain access. He looks around the room for instructions but can’t find anything. It occurs to him that maybe the passcode is on the bottom side of the internet router. No such luck! Gary gives up and goes to the kitchen for a glass of water. There on the refrigerator door, on a small sticky, he sees the words “Wifi Passcode”.
During the morning of Gary’s departure, he sips his coffee while reading the newspaper, when the front door opens. A group of people enter with a mop, a broom, and a vacuum cleaner in hand. The cleaning crew has arrived and wants to clean the home and prepare it for the next guest. Annoyed and embarrassed, Gary makes his way to the bedroom to change out of his pajamas.
You can’t help but feel bad for Gary and can only imagine the type of review he will be leaving for Huey.
A Better Way
Now, let’s rewind and imagine an entirely different scenario. One where Gary receives a Confirmation message from Huey minutes after booking his reservation. Then, 24 hours before his scheduled arrival, Gary receives a Check-In message with very specific instructions about parking, where to find the house keys, the Wifi passcode and other pertinent details he will need to make his stay a more enjoyable one.
In this scenario, things go so well for Gary and he truly enjoys the start to his retirement, that he actually wishes he could stay longer. Coincidentally, Gary hears the Airbnb app chime from his phone. Gary pulls out his phone to see a message waiting for him from Huey. The message informs Gary of a vacancy after his scheduled departure, and Huey provided an offer should Gary choose to extend his stay. Gary is pleasantly surprised and decides to extend his trip for two additional days.
The day before his updated departure date, Gary receives a very nice email from Huey reminding him of the Check-Out time and informing him of the Check-Out instructions. Gary has truly enjoyed his first Airbnb experience and looks forward to writing an excellent 5-star review for Huey.
Automate and Simplify
In the latter scenario, Huey has added message automation software to his arsenal of tools. Message automation software allows Huey to create personalized messages that include all of the important details that his guests may need. The messages are delivered into the Airbnb message thread on a pre-set schedule for Gary and all of Huey’s future guests so he will never have guest communication issues again. Riding this wave of the short-term rental market, the host who is most prepared will be the one who delivers the happiest guests. And a happy guest translates into a 5-star review, which means a higher listing ranking and more bookings.
I was inspired to write this story after recently renting an Airbnb from a super host that used a new piece of software to communicate with me. That software was Aviva IQ, a Silicon Valley startup. Necessity remains the mother of invention, the founders developed the SaaS based application out of their frustration in delivering a streamlined communication process that didn’t require immense levels of manual work. Aviva IQ allows Hosts to automate their Airbnb messages so important details about the reservation can trickle out over time, at the optimal time. For the guest, it means having a consistent and enjoyable experience. Their focus is on their trip and less on the details and concerns about rental logistics.
Everyone gets a good night sleep.
First published in HuffingtonPost
Chatbots came on the scene in 2011 as business intelligence, artificial intelligence and messaging platforms combined into new forms of responsive technology. New ways were needed to support companies interacting with buyers and provide customer support that aligned and could evolve with changing communication habits. What is a chatbot? A messaging application, sometimes referred to as a conversational interface, designed to simplify complex predefined task(s). The ‘chatbot’ label covers a number of categories including stand-alone applications, AI tools, bot developer frameworks and messaging, bot discovery, connectors/shared services, and analytics. VentureBeat recently released a bot landscape which undoubtedly will rapidly expand in the near future. Today, chatbots are seen as easy and fun ways to help customers achieve an outcome. You’ll encounter them on web sites, social media and even on your smartphone. Say hello to Siri, Allo and Alexa, to name a few. To further adoption developers are making chatbots more human-like with personalities, capable of recognizing speech patterns and interpreting non-verbal cues to make interactions even smoother. The excitement is not in what they are capable of doing today but in their future trajectory. As cited in The Chatbot Magazine, “Messaging apps are the platforms of the future and bots will be how their users access all sorts of services” shares Peter Rojas, Entrepreneur in Residence at Betaworks. Verizon Ventures is an active investor in the chatbot market. According to Christie Pitts, Manager – Ventures Development, Verizon Ventures, “Chatbots represent a new trend in how people access information, make decisions, and communicate. We think that chatbots are the beginning of a new form of digital access, which centers on messaging. Messaging has become a huge component of how we interact with our devices, and how we stay connected with the people, businesses and the day-to-day activities of life. Chatbots bring commerce into this part of our lives, and will open up new opportunities.” When asked why chatbots are strategic to Verizon, Pitts replied, “At heart, Verizon is a technology company and as such is constantly at the forefront of understanding and delivering on new market opportunities, and one of our top priorities is simplifying communication with our customers.” They have invested in companies like Spark Cognition, Adtheorent, Q Sensei, and MapD. Verizon sees AI as an enabling technology layer that can lead to huge gains. Companies working with AI technologies will create valuable solutions that augment the way people communicate, with each other and machines. Chatbot technology is part of Relay Network’s customer experience communication solution. Their approach is to first determine the specific use cases that could benefit from this technology. Matt Gillin, CEO of Relay Network, believes “that a customer relationship and communication pattern needs to exist first before you can employ technologies, like bots, to facilitate the relationship further.” When asked about guidelines when employing chatbots, Gillin’s recommendation is bots are best “for scripted transactions or tasks that don’t require a lot back and forth.” Chatbots are most effective in situations where a customer is trying to resolve routine issues, complete specific tasks like placing an order, or guiding a user through a multi-step process. The benefit is the ability to “close the loop with the customer along a process, efficiently and in a delightful way,” shares Gillin. The ROI is in cost reduction, efficiency and improved customer satisfaction. Chatbots also play a role in marketing. By tagging specific content to certain chatbot words or phrases, content could be delivered in any number of pre-defined conversations. With deep understanding of the customer journey and emotions, through the eyes of the buyer, content and bot conversations can be successfully mapped and programmed. Verizon is excited about chatbots and the advances that are happening in the field of artificial intelligence. Over time, great leaps in technology have provided huge benefits to our lives. It’s easy, however, to get carried away with the allure of artificial intelligence and human-machine relationships. “Sometimes advancement comes with trepidation,” says Pitts. “Outcomes can be predictable and beneficial, or at times unpredictable and present new challenges. In the long view it is clear that technology improvements are a net benefit to society.” Yet, lurking in the background is the concern about unintended consequences. We become enamored with technology and its potential to do good. We don’t think about the possibility of a dark side; how the technology’s original intent can be perverted to do harm. A few examples are social media cyberbullying and sexting. It’s a lesson we seem unable to learn. Dr. Liraz Margalit, Director of Behavioral Analytics for Clicktale, an enterprise-class experience management platform, blames our tendency to see the world through rose-colored glasses as a “lack of psychology research in the early stages of technology development. As a result we don’t plan for all the issues that will arise.” For some the unintended consequences are already here. Our willful blindness about the dark side of technology has some expressing concern. Futurists like James Canton to technology giants Alphabet, Amazon, IBM, Facebook and Microsoft are calling for an AI framework that takes into account social and economic policies. Dr. Margalit states that “interacting with chatbots creates in our brains a new model which results in a new state of mind.” We may intellectually know we’re interacting with a computer but our brain perceives it as companionship. The more human-like chatbots become, the more our brains gravitate to a companionship model. And that is where the slippery slope begins. As users increasingly interact with chatbots, they subconsciously perceive that bot as a friend – one that makes them feel good because the user unconsciously has control over the relationship. No need for you to be nice and pleasant, the chatbot is selfless, always ready and available to serve you and in a good mood. Dr. Margalit calls it “designing technology for companionship without demand for friendship.” She believes incorporating humanoid social robots into our lives “invariably alters the dynamics of human relationships and gives rise to a society that isn’t completely real.” So what’s the wrong with that? Unfortunately, some users cannot tell the difference between a chatbot and human chat. Take a look at what happening in China with Tay and Xiaolce. This is known as the ‘Eliza Effect’ where people think they are communicating with a real person when in actuality it is a piece of software. When these same users then interact with fellow human-beings, things go awry. They bring into the real-world human-to-human interaction a mental model partially based on how they felt and behaved while interacting with a bot. Dr. Margalit cites several studies done with children that are heavy smartphone users. These studies found a correlation to rudeness, impatience, imitation of video hero behavior, and disconnected attitude toward the real world. Asymmetrical digital interactions are easier and don’t require effort on our part to really understand the perspective of other people, especially if their views are different. Gillin isn’t too worried about the slippery slope, “the focus of an organization on improving a brand’s business will keep it from running into the AI moral dilemma”. Pitts and her Verizon team believe that “elements of AI like machine learning, natural language processing, and neural networks are poised to power the next wave of a digital revolution. Smartphones and ubiquitous access to high quality wireless networks have improved our lives in countless ways. AI-powered solutions will very likely further this transformation.” Interestingly, both Gillin and Margalit believe that chatbots should be visually tagged with a universally accepted icon so the unaware among us are always reminded we’re interacting with software, not our best friend. “Bots are changing rapidly as technology improves,” shares Pitts. “A bot that provides information today could provide contextual recommendations tomorrow. We are looking forward to watching these new technologies and integrating them when it will benefit our customers.” Chatbots are not likely to take over and drive all forms of customer communication. The technology isn’t that advanced and remains dependent on human design and oversight. The importance of this technology is its role as a stepping stone to the new world of IoT (Internet of Things) wherein traditional roles of sales, marketing and customer service will be completed transformed. We can either focus on redefining, in advance, what tomorrow’s organization, culture, and customer relationships should look like and guide technology development to further that transformation. Or we can be smitten with creating humanoid social bots that mimic us because in today’s increasingly isolating society we all need a new best friend. Originally posted in Forbes