During the coronavirus pandemic, digital transformation and automation efforts have accelerated as organizations look to streamline workflows and reduce operational costs. On Thursday, IBM announced a definitive agreement to acquire Italy-based process mining software company, myInvenio. "Digital transformation is accelerating across industries as companies face increasing challenges with managing critical IT systems and complex business applications that span the hybrid cloud landscape," said Dinesh Nirmal, general manager, IBM Automation. The move highlights IBM's investments to provide an AI-enabled automation suite "one-stop shop" for organizations, the company said, with capabilities such as robotic process automation, document processing and process mining among others. IBM said the acquisition will provide companies with "data-driven software" in areas such as sales, production and accounting and could help organizations identify processes for potential AI-enabled automation.

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However, for many IT organizations, AI is not just on the IT leader's radar as a business enabler: It's having fundamental impacts on the function itself – from automating some longstanding functions to demanding greater involvement and newer approaches from IT teams. AI is beginning to reshape IT in a number of ways that forward-looking IT leaders will want to follow. Let's consider five worth watching: Tools to automate traditional break-fix and other IT service desk processes are not new, but they're getting significant traction these days, says Wayne Butterfield, director of cognitive automation and innovation at ISG. "An IT Service Desk is as prone to repetition (and therefore automation) as a customer service operation," he says. That's not the only area of hyper AI-enabled automation coming for the IT function. "IT has quickly become not just a partner but a consumer as well, leveraging AI for security and system management to automate processes and move at the speed of an AI-driven enterprise," says Shawn Rogers, vice president of analytic strategy at TIBCO.

AI-enabled automation has generated its share of controversy. We've all heard the predictions: 40% of jobs will be eliminated by AI, echoed venture capitalist Kai-Fu Lee on 60 Minutes recently. And experts say this is even worse news for women. According to the Institute for Women's Policy Research, women "… are 58% of the workers at the highest risk." Women tend to hold the types of job ripe for automation: customer service and administrative positions that involve routine, repeatable tasks, according to the research.

International Data Corporation (IDC) has published a framework designed to guide business and IT decision makers faced with planning and investment decisions related to artificial intelligence (AI) for automation. The framework defines the expected levels of human-machine interaction and the hierarchy of automation scope, which can then serve as a basis for assessing data, algorithm, IT, staffing requirements, and potential risks at the intersection of AI capabilities and use cases. IDC has published a framework designed to guide planning and investment decisions related to artificial intelligence (AI) for automation. "IDC's AI-based automation evolution framework was developed based on global market research that highlighted two lessons," said Dan Vesset, group vice president, Analytics and Information Management Research at IDC. "First is the need to understand the components of the evolving relationship between humans and machines. Second is to understand the scope of AI-based automation. Once these two dimensions are brought into focus, the planning and investment decisions associated with AI-based automation will be much clearer."

At District 3, my research is focused on assessing the labor impacts of AI-enabled automation in the financial services industry in Quebec, Canada. At McGill University, I'm building out an introductory curriculum via a 4-part workshop series to introduce the topic of the ethical development of AI to students, faculty, staff and alumni of the McGill community. I'm also actively researching the impacts of AI-enabled technologies pervading the field of medicine, especially on how this affects doctors in training and impacts on different fields where AI systems are doing well on narrowly defined domains. I founded the meetup group on AI Ethics in Montreal that meets once every two weeks to do a deep dive on different aspects of the ethical development of AI. We also work together as a community to provide feedback and recommendations to public documents like the Montreal Ethical AI Declaration.