By Rashmi Tambe, AI & ML – Head of Business and Strategy, Persistent Systems
As per McKinsey Global Institute report, ~50% of current work activities are automatable by adapting current automation technologies. Robotic Process Automation (RPA) is one such technology that can execute rule-based activities and automate business processes. By 2030, between 400-800 million works could be displaced by automation and need to switch occupation. However, automation combined with artificial intelligence (AI) has the potential to raise throughput, lift productivity and contribute to economic growth. Therefore, if your company has not yet started on automation roadmap, now is the right time!
Although, the common perception about automation is that it can undertake routine, low-skill and repetitive tasks, the landscape is moving towards cognitive Business Automation.
• As the scope of automation broadens towards more dynamic process orchestration across many applications and platforms, the underlying data structures also become more complex and involve unstructured data at real time.
• Secondly, there are increasing expectations of social and emotional quotient around human-machine interaction which require understanding of natural language E.g. a customer support chatbot needs to understand the intricacies of human language and interpret correct intent before taking automated action.
Consequently, automation goes beyond mimicking human actions and starts interpreting complex data, enables process transformation and creates new business values.
In the upcoming era of cognitive automation, following are the key trends to watch out for,
1. Natural Language Processing (NLP) will become intrinsic part of business workflows. Companies will look beyond chatbots and explore more enterprise workflows that involve NLP interpretation and insights and process unstructured data such as documents, emails, call center transcripts, support ticket summary etc. E.g. A typical Backofficefunction deals with lot of unstructured document processing. Along with standard application of OCR and RPA, NLP tools are being used to extract entities from documents and enable straight-through processing.
2. Confluence of AI, IoT, Big data and Industry 4.0 will continue to evolve and disrupt manufacturing and industrial vertical. Machine learning combined with IoT data from sensors will significantly impact business processes such as predictive maintenance, supply chain management and quality control.
3. Voice assistants and smart machines will continue to proliferate and automate customer expertise. A humanoid bot at the bank, Amazon Alexa based customer service, a washing machine ordering detergent online is not a distant imagination but already a reality! Every aspect of customer experience will be automated via AI and IoT. Automation tool will not work in isolation in an enterprise but will integrate with peripheral technologies to provide end-to-end customer experience.
4. RPA will be more involved in decision making than just repetitive automation. E.g. health insurance claim processing will be automated based on historical data of claim processing and will require less human involvement for claim approvals. A Machine learning algorithm along with RPA will handle complex decision making via deciphering behavioural changes, recognizing patterns in data and finding out anomalies.
5. RPA bots are no-collar digital workforce. As with any digital workforce, it will require plan around monitoring, auditing, exception handling, fall back, compliance and governance. Significant amount enterprise automation effort will be dedicated to establishing these guidelines.
6. New type of jobs. While there is lot of fear about automation taking away jobs, there will be huge requirement of reskilling workforce to handle new types of jobs.As per Mckinsey Global Institute report, 1/3 of new jobs created in the US in the past 25 years were types that did not exist earlier. Automation combined with AI contributing to productivity shifts will lead to economic growth resulting in new demand-supply equations. According to Forrester Research, over the next 10 years, nearly 15 million new jobs will be created in the US because of AI.The nature of these new jobs may not be defined or imagined right now but it will surely demand nimble ways of reskilling the workforce.
If you are about to embark on your automation journey or have recently started, address following aspects of automation roadmap in order to have a successful enterprise implementation:
1. Is Artificial Intelligence part of your automation strategy?
2. Are you using RPA tool in isolation for automation of couple of repetitive, rule-based processes?
3. How do you plan to handle unstructured enterprise data during process automation?
4. What is the final goal of your automation strategy? Is it only about optimization and cost reduction or do you also plan to address customer experience elevation?
5. Is your leadership ready to make shift towards cognitive Business Automation?
6. And finally, have you come up plan for reskilling your human workforce after automating their manual work?
AI is the new electricity and a powerful combination of automation and AI is poised to disrupt enterprise landscape. If you have not yet started in this direction, remember a Chinese proverb, “The best time to plant a tree was 20 years ago. The second best time is now.”
According to a Mckinsey and Company blog, RPA is part of a larger family of technologies that are classified as part of the Intelligent Process Automation (IPA). RPA essentially takes the robot out of a human. RPA software mimics the human activity, leveraging a stream of Cognitive Intelligence and Automation techniques to carry out a ‘task within a process’.
That sounds great! I believe that businesses need to leverage AI and automation to serve customers and provide real-time solutions, and so does Mike Kail. It helped me put things into perspective, hope it does the same for you as well.