When AI and other intelligent technologies enter the workplace, many jobs that are based on production or industrial processes will be eliminated. Big changes will need to be made to move from the mentality of controlling a process to meet a goal, to facilitating flexible design with the aim of delivering value. Although agile started as a retaliation to inflexible and ineffective practices in the software industry, it has gone far beyond those limitations. Changing corporate or organizational culture is hard. The change from a control process to a collaborative process involves including people in a whole new light. The shifts in workplace paradigms will be anything but painless. Almost every job that requires an individual to process transaction data in front of a screen will be at risk. The critical criteria will be the level of redundancy and routine. Machines will replace humans where the job process are repeated regularly and where the individual tasks can be made to be independent (Gerlind Wisskirchen, 2017).
Distributed cognition is a way of looking at the workplace and determining how work is performed. New work practices influenced by the integration of technologies causes an examination of distributed cognition between people, objects and other people. When cognitive agility is referred to in the workplace, it usually encompasses both the individual’s interactions with self and others and the collective interactions of groups of people. Both individually distributed cognition and collectively distributed cognition combine to create the extended cognitive system. The individual system is a single actor and can include multiple other people and objects. Collectively distributed cognition involves multi-person activities, objects and resources. Examples of this include systems of one variety or another, either well-structured and functional or ill structured and sloppy, which tends to include processes, participants or objects that are either under or over specified. Both of these concepts come from classic cognitive science which provides a framework to examine intelligence and problem solving.
Distributing work across groups or involving collaboration requires breaking the work up into parts so that individuals or agents can bring their expertise to sub tasks within a larger business objective. This examination of how information is represented in the workplace and then transformed, combined and disseminated is, theoretically, in alignment with business and performance goals. Problems solving then can be reliant on one individual or distributed throughout the system with various degrees of reliability and efficiency. Intelligence then sits at the systems level in distributed cognition and can and does include AI or any other technologies that can and does support the idea of problem solving and attaining business goals (Perry, 1999). Understanding this is key to the functioning of the work organization, both for the individual and for the collective organization. So both knowledge and skills combine with the organization of those individuals and subgroups to support the work environment.
Agile environments support a continuous adaption of new tasks to support business processes that allow for flexible reactions in specific situations. In this way each case, each order, each customer has the ability to remain unique and be treated, at least for the most part, to accommodate that distinctiveness. KISS (Knowledge Intensive Service Support), is just one of many acronyms use to try to qualify dynamic and agile tasks. There are always exceptions, unforeseen events, unpredictable situations, variations and complex tasks. “A task is a definition of a particular item of work that specifies the requirements and the goal of that work” (Simon Brander, 2011, p. 10). Different resources can be used to accommodate different tasks. In an agile environment, the approach is initiated to shorten the gap between the initial process design and the process execution. The most important principle of the agile enterprise is to learn and adjust along the way (Mouser, 2015).
