In enterprise conversations of 2020, inevitably, one would come across bots in various contexts. References to chatbots, RPA bots, CPA bots, and next-gen multifunctional cognitive agents will be sprinkled across conversations involving enterprise productivity, efficiency, automation, and user experience. What are these bots? How are they different? What does the future hold for the bots, as well as the enterprise?
A bot is typically a software application to do a specific task, often simple and repetitive. If you consider the level of sophistication or intelligence as a benchmark of progress, the bots can vary from rudimentary desktop automation bots to highly sophisticated multifunctional cognitive agents. With chatbots being somewhere in the middle end of the spectrum as a transitory technology.
The image below shows some of the common technologies and automation terminologies in chronological order.
RDA Bots (Robotic Desktop Automation) – These are rudimentary screen scraping technologies, created as a bridge between current systems and incompatible legacy systems. They take over the bulk of repetitive data entry or form-filling tasks from humans.
For example, a standalone desktop application or a client-server/thin client system without any APIs or eternal connectors available that require a human agent to go through form fields on a screen. Typically XY coordinates are used on the desktop screen to retrieve the data and enter it into another system (read newer technology with APIs available) and work with manual intervention. This is a prevalent technology since the 90s.
RPA Bots (Robotic Process Automation) – Performing desktop automation with added digital triggers or self-service (unattended), these bots deal with only structured data and predefined activity choreography to do the tasks repeatedly. RPA bots started getting popular in the early 2000s.
RDA and RPA function at a repetitive task level and add value to the enterprise in reducing the workload of the employees.
Chatbots
Chatbots are usually scripted decision trees where set-up tasks are completed in a top-down flow with button clicks and filler sentences. Chatbots handle simple repetitive chats where the bot creator scripts user chat and bot responses.
CPA (Cognitive Process Automation)
CPA uses AI to replace human intelligence or cognition-related work and works with unstructured data along with natural language understanding and generation. This type of automation produces insights, and analytics and takes actions at or above human capability. They started to gain prominence around mid-2019.
RPA bots work by recording the user’s action on the screen and repeating the same set of actions – i.e. they mimic human repetitive actions while Cognitive Process Automation mimics human cognition. For simplicity, one can think of RPA as a software robot(bot) that mimics human actions, whereas CPA is concerned with the simulation of human intelligence by machines. Cognition refers to gaining knowledge and comprehension; cognitive processes include knowing, remembering, solving, etc. mostly encompassing language and perception.
Cognitive Process Automation automates processes that require human cognition and the process of attaining this cognition is basically AI training. At a very fundamental level, RPA is associated with doing and CPA is associated with thinking and learning. chatbots are transitory technology since chat itself is a cognitive function. The current set of chatbots with scripted inputs and outputs will not be scalable to the next level of cognition due to the limitations of the intent classification systems deployed and the limited learning on the user actions. chatbots were relevant as a stop-gap solution while complex cognition AI models were maturing and giving rise to Multifunctional Cognitive Agents which are capable of cognition with unstructured data (voice/text/images/videos/PDFs/Spreadsheets, etc.) along with structured data and free-flowing conversations.
E42 AI workers are capable of functioning as fully cognitive business assistants at or above human capability.
For the first time in human history, there is competition for humans from Multifunctional Cognitive Agents for a place in the enterprise workforce. Multifunctional Cognitive Agents, or E42 AI workers use various cognitive capabilities like reading unstructured text, structured data, scanned documents, pictures, videos, etc. to perform various tasks as part of the enterprise workforce. Just like training a new employee, one can add various data sources to the E42 platform and create Multifunctional Cognitive Agents.
For example, an AI worker can be inducted into an enterprise as a receptionist to carry out tasks like recognizing and welcoming people, checking their documentation, booking appointments, welcoming customers, and solving their problems, etc. These tasks involve face recognition and identification, document scanning, data extraction, and validation, and conversations to complete a task. Similarly, AI workers could also be trained to generate reports from available data just like an analyst.
E42 AI workers can be deployed in operations, ITSM, employee engagement, HR management, or various other business processes. With their super-efficient cognitive capabilities, and ability to train a limited amount of data on a platform and create new AI Models, these intelligent human-like agents create immense opportunities in the enterprise workforce of today and tomorrow.
AI workers can bring in massive ROI for any business as they can be designed to accomplish a huge volume of work in a short period of time. This inevitably takes a load off the human core team in any business process and helps them concentrate on more pressing issues. From boosting productivity in the workplace to carrying out error-free operations with minimal human interventions, AI co-workers can be custom-configured to resolve pain points and drive an enterprise towards excellent business results.
