As organizations, most notably enterprise organizations, prioritize their digital transformation initiatives, the spotlight turns to process automation as a means to enhance efficiency across various functional areas. However, before automation can take center stage, it requires a concerted effort involving automation teams, functional departments, governance, IT, audit, and more. Furthermore, before any functional area process or processes can be automated, there are many steps that must be taken between automation teams, the functional area in need of an automation roll-out, as well as many other parties, such as governance and oversight, IT, audit, and much more, so to ensure program feasibility prior to launch.

In this session, topics of discussion will include, yet will not be limited to:

• Working effectively with various areas of the business, so to help identify which processes could, should, or should not be automated
• Identifying, reviewing, and analyzing current and future automation program rollouts
• Challenges and solutions of collaborating with various functional area leaders, with respect to determining if a potential automation program meets the required technical, infrastructure, workforce, audit, governance, and other business requirements

As enterprise automation leaders, you’re certainly very aware of hyperautomation and how it’s a complex integration of a wide array of IA technologies that can rapidly automate and augment complex business processes - and optimize a wide array of automation programs. That said, you’re also very familiar with the technical and program management challenges associated with hyperautomation programs, which there are many. However, considering the rewards it can offer an enterprise organization, it’s certainly something worth discussing with your peers, so to be able to better execute on your current or upcoming hyperautomation program rollouts.

In this session, topics of discussion will include, yet will not be limited to:

• Hyperautomation capabilities and potential use cases
• Data governance, quality, and optimization
• Technical, infrastructure, and workforce requirements
• Common challenges and potential solutions surrounding planning and implementing hyperautomation initiatives