Deep Automation: CIO Lessons Learned During a Large-Scale Manufacturing Project

This IDC Perspective provides insights into a new dimension of automation that is emerging: deep automation. With deep automation, you can automate almost anything that is highly "teachable," using language. That means AI can be applied to almost any manufacturing or business process.Deep automation captures expert knowledge and stores it in a graph database using structural causal model representations. This becomes a collective intelligence knowledge base that can be continuously "taught" using causal AI to expose cause-and-effect relationships, which become the basis for automated unbiased business decisions.While most AI/machine learning solutions require (and are limited by) a massive source of machine-generated data, the unique knowledge base for deep automation is taught to the model from readily available language-based documents including books, white papers, and subject matter expert (SME) interviews.To move from teaching knowledge to the model to having it make automated decisions requires a newly rediscovered technology: the structural causal model technology first developed by Judea Pearl in the 1980s. This model enables an organization to use its unique knowledge base to massively expand its decision-making capabilities by exploiting the model's capability to navigate through impedance gates with minimum friction.While users and subject matter experts will teach the model their best practices, the quality of the output from the model, the UI, will determine how efficient and effective the machine-human symbiosis is; in essence, it becomes a "business companion" to the user."Just the idea of deep automation, teaching machines to make complex decisions, can appear to be a daunting challenge to an organization, from both the business perspective and the IT perspective," says Robert Multhaup, adjunct research advisor with IDC's IT Executive Programs (IEP). "The CIO sits in the middle of this dilemma and is in a unique position to steer the organization through this labyrinth of new ways of doing business, a new human-machine intersection, a new culture of knowledge sharing, and a new competitive weapon."