Automating decision-making and operational workflows with artificial intelligence-powered cloud services

Automating workflows to better support business operations and employees has grown in popularity recently. The goal is to allocate mundane and repetitive tasks to software, freeing up human employees for more demanding and productive roles. This trend has been accelerated by the recent explosion of cloud services infused with advanced artificial intelligence capabilities. Major cloud service providers have not only expanded the breadth of their product offerings – such as intelligent document processing, intelligent search, and voice capabilities – but also are building increasingly sophisticated AI capabilities into individual services, such as document and image processing, information retrieval, and personalization and recommendations. Moreover, these capabilities have been made available in ways that simplify their integration into existing as well as new enterprise applications, enabling organizations to quickly automate operational workflows in ways that can improve overall employee productivity (Breivold & Crnkovic, 2011; Dastjerdi et al., 2015; Ghosh & Mallick, 2022).

As a result, organizations can now automate time-consuming, repetitive manual tasks that contribute little to business objectives and may be viewed as uninteresting by employees. Empowering employees to devote more time and energy to high-value business tasks creates job enrichment that can lead to significant increases in job satisfaction and engagement. Decreasing the burden of mundane task performance on front-line employees can help mitigate fatigue that can lead to errors and neglect that in turn can adversely affect customers. Such de-risking of workflow tasks is particularly valuable in service industries that are experiencing increasingly high employee turnover rates. Automating such tasks also creates the potential for cost savings, which can be significant if technology service levels rise and wages continue to increase. Indeed, if these rises continue, the business case for implementing automation technology will become even stronger.

With its continuing emphasis on Policy as a Service, and on decision-defining templates, the AI-enabled cloud now provides a layered architecture for automating enterprise decision-making, process automation and monitoring for high-volume low-complexity tasks. Automation of decision-making and operational processes lowers the overhead of back office functions and enables organizations to focus their resources on creating value (Sculley et al., 2015; Villamizar et al., 2016).