In the new era of intelligent automation, cognitive solutions will reshape organizations and teams.
With robots reshaping the future of work, there is an increasing demand for automation across all sectors and within all service lines, whether IT, HR, back office or front office, as well as core industry-specific processes. All organizations are looking to gain efficiency, agility and competitiveness.
But with the results delivered by IA, the focus in the near future will be on the people that make the enterprise. Freed from previously boring and redundant tasks, humans will have time for much more creativity in helping to deliver the organization’s objectives. Jobs that involve leadership, and tasks that are more interpersonal in nature, can be built on and bettered. In this way, IA technology can be used to improve an employee’s skills rather than getting in the way of them. Automation is not merely about cutting costs, but rather enhancing the business and supporting its employees.
The development and deployment of cognitive solutions is currently in its early stages, and most enterprises are still striving for efficiency and effectiveness. But there will soon be a combined evolution and revolution in cognitive, founded on technologies and disciplines such as machine learning (ML), neuro-linguistic programming, image visualization, security and governance. The convergence of cognitive with other technologies like Internet of Things and blockchain will further improve human-to-machine interactions and create intelligent enterprises. The span and tenor of the applications in this area will be almost boundless.
All of this has profound implications for the future of the firm.
What will change?
The cognitive enterprise of tomorrow will be more agile, capable of faster innovation cycles and, therefore, more competitive. Intelligence-infused apps will become mainstream and open up more possibilities for the enterprise and its workforce.
From a data accessibility and insight point of view, our working days in the future will be simpler. The IA journey is all about data: how to provide it at the right time to the right people in the best format, without spending many hours manually processing data on a screen. Avoiding the manual handling of data from multiple sources could also help prevent errors that could be damaging to the business. The aim of IA is to give people – whether they’re clerks, accountants, financial, HR or procurement resources, marketers or directors – the output they need in the most comprehensive manner, while making their working days hassle-free and, best of all, less boring.
Today, most mainstream platforms, applications and enterprise resource planning systems (ERPs) are already becoming augmented with some form of intelligence. For example, Microsoft is embedding cognitive search capabilities into its suite of data processing tools, and SAP provides similar possibilities with its new module Leonardo. People are regularly interacting with chatbots or virtual assistants to find information, to be guided through a process or to be given access to relevant pieces of data. Chatbots can also provide basic support to employees about typical HR issues, for example.
Organizations across the world and across all industries are implementing or experimenting with IA, in an effort to become yet more efficient and optimized for the cognitive future. To illustrate such experiments, let us consider a robotic process automation (RPA) solution that extracts emails received at a service center, augmented by an ML solution that allows the capture of the tone as well as the sentiment of its sender (angry, happy or just asking simple questions) to best prioritize the requests and tailor the response. It allows better management of the customer’s expectations, as well as more efficient treatment of priorities. This can help free up valuable time and increase efficiency, and illustrates just one of many solutions that we have been designing and implementing extensively at EY and for our clients.
What needs to happen to prepare for the changes?
Tomorrow’s workforce will need to adjust to the new intelligence-infused apps and the adapted processes they will drive. So training and preparing the workforce needs to begin as early as possible.
Training, in fact, needs to be at the heart of the cognitive revolution: academic institutions needs to make sure that learning curriculums include disruptive and new technologies, from primary school all the way up to university. This could be achieved by gradually introducing the concepts of AI and cognitive computing, from theory to practice, via hands-on labs in key academic subjects such as mathematics, physics and even social economics.