It’s not easy to make automation simpler. Many early adopters of simple automation have found in retrospect that perhaps they went too fast. They would do well to slow down just long enough to ask a few key questions and put a governance framework in place. One company had more than five teams working on emerging automation in an uncoordinated fashion. They didn’t know what the other teams were working on; they didn’t even have a common definition of automation.

The need for a governance framework runs deep because a different governance model is needed when teams are empowered to use no-code tools. Think of the potential problems if only one person knows how a particular bot works. Poor controls that allow an error to become systemic to a process could put the whole company at risk. If a change to a source system like an ERP breaks a bot, and there are hundreds of bots tapping into that ERP, that change creates an operational nightmare. And when AI is part of a process, how will you explain its decisions to customers or other stakeholders? For reasons such as these, an enterprise-wide governance and controls framework is critical when automation is assigned to business units.

View the automation toolbox

Roadmap to intelligent automation

Governance also includes building a roadmap to more-intelligent automation. Automating end-to-end processes often means orchestrating work among humans and machines across multiple automation technologies. This orchestration requires IT to develop a framework enabling automation to bloom independently across the enterprise, while progressing toward a common vision. Data accessibility is an important consideration in tying together simple automation with intelligent automation.

In addition, cognitive frameworks with advanced machine learning often fall back squarely on IT to develop. Thus, the IT function’s role shifts toward governance in some areas, but control in others.