Chris is exhausted! As the director of a BPO, he has a pile of complaints from customers about long wait times for services. Not just this, he can see the customer service desks struggling to address tens of thousands of customer queries, accounting teams spending hours on reconciling reports, and data entry operators attempting to decipher the handwriting on application forms faxed by the client so they can enter the data in their systems. On the way to a meeting, he sees the HR manager overloaded with KYC documents of new joiners.
In the evening, as he leaves for home in his autonomous car, he worries about the scenario at work and ponders how it can be sorted. He wonders if there is some way to not only reduce paperwork but also save manual efforts and time while getting the important tasks completed with utmost accuracy.
As he reaches home, Chris gathers drone deliveries from the drop box, and is greeted by a next-gen smart assistant. After unpacking his parcels, he lays on a couch to relax just when the smart assistant played his favorite music, and he thinks how it manages to play the songs that exactly fit his frame of mind. Knowing that Chris would not want to cook dinner, the bot had already ordered his favorite food from a nearby restaurant.
Thank goodness for the smart digital assistant, Chris has his alarm set and meetings scheduled for the next day. The next morning, as he gets ready to leave from home, he is warned by the bot about traffic conditions on the road, and is recommended to leave at least 15 minutes prior to make it in time for the meeting at 10 a.m.
Back at work, Chris wonders how the workplace would look different if digital assistants would be there to support, just like at home.
We are in the year 2018, and technologies like conversational artificial intelligence (AI), robotics process automation (RPA), and machine learning have profoundly empowered us – at home and work, both.
Looking at Chris’s scenario, how easy would the customer service delivery be if he deploys a self-learning AI-based chatbot to address countless customer queries? It would not only help in reducing cost and saving labor hours for business-critical tasks, but most importantly, assure delivery of better customer services quickly.
Not just this, deployment of RPA and machine learning can support Chris in simplifying data processing tasks for the accounting team that would otherwise spend several hours in downloading invoices from four different vendor portals, uploading them into an ERP system, and verifying the values with the corresponding purchase orders, and eventually approve or reject them manually on the system. An RPA-powered bot can easily execute the process with some amount of scripting.
In another instance, a voice-enabled assistant can be deployed to quickly get detailed business insights like Who is our largest client in Asia? or How has the volume of sales increased from Q1 to Q2 this year? Besides easy and quick access to actionable data, this is bound to help Chris boost client engagement, acquisition, as well as monetization.
After the launch of a voice-based digital assistant in 2011, we have seen it being applied to a number of devices – becoming a deep-rooted element in our everyday user experience.
Whether we term it as a virtual assistant, digital assistant, smart assistant, or a voice assistant, we are basically referring to a digital application that lets users give commands or ask questions using an instant messaging platform or even their natural language. A virtual assistant can exist in several forms – on a desktop or smartphone, within a speaker, or in web or mobile applications.
Taking AI a notch higher is RPA. The software and services based on RPA can run applications the way a human operator would. RPA-based bots can perform a number of functions that individuals would spend a lot of time and efforts on. For instance, in Chris’s scenario, the manual data entry jobs that would usually take several hours to complete, can be simplified and paced up with bots.
Maturing every passing day, AI-based assistants are capable of searching for information, managing schedules, and assisting with routine activities in more instinctive ways. These tasks can include anything from playing music that suits the mood, ordering a cab or meal, managing emails, booking a meeting room, and much more. In fact, these activities are just the beginning, we are now seeing them help in complex, business situations as well. We can see their application in areas such as analyzing customer feedback about a particular product or service, managing inventory, forecasting sales, public health, and many more.
In another instance, self-learning bots can address user queries and re-route queries to humans in case they are unable to understand a customer’s accent or language. Best of all, they learn as they interact more with users and continuously improve their capabilities.
The potential business benefits of AI, RPA, and cognitive technologies are much broader than effort, time, and cost savings that may be implied by the term automation like quick decision-making, better outcomes, greater efficiency, reduced operational costs, as well as product and service innovation.
So as we get accustomed to digital assistants doing more things for us, the next question is: Where do they go from here?
I believe as the world of smart assistants grows stronger, and we continue to witness their implementation in an enterprise scenario, we are undoubtedly bound to experience some surprises as well as set-backs. Before we even know it, we shall see a number of smart assistants around – supporting us with their immense knowledge – without getting upset or perplexed. Moreover, it would certainly be a boon for consumers to not be told again, “All of our customer service representatives are busy at the moment. Please stay on hold till you are connected to the next available agent to attend to your query.”