While the health crisis caused by the COVID-19 pandemic will eventually subside, its effects on business models will be long lasting, and the post-pandemic world will require a massive shift in business models. As a concept, the ‘density-driven’ model involves enterprise customers coming to an enterprise’s place of offering to be served. Now, with the pandemic, businesses have been forced to reconsider ‘density-driven’ models in favor of more ‘non-dense’ or ‘boundary less’ models where offerings are delivered to customers wherever they want to be. The HOLMES Advisory Board met in October 2020 to collectively discuss how enterprises can remodel their business and how AI and Automation can play a significant role in enabling that.
From an enterprise’s perspective of Automation and AI, both humans and digital workers will be critical as they move toward business models that favor reduced human density. Organizations looking to integrate AI and Automation into their processes often find themselves asking questions regarding when to trust intelligent machine automation and when to trust human judgement, as well as when to augment humans with machines and vice versa.
The session prompted an interesting perspective about how autonomous enterprises exists at different automation levels, ranging from basic automation to a level of maturity where humans have become optional -- true zero-touch operations. Ethics become important as one moves up the value chain, and it becomes essential to begin the process with humans and end the process with humans.
Organizations hoping to achieve full stack automation must balance the right use cases before moving toward automation at every process level. Automation feasibility assessments begin with business and privacy impact analysis and then move toward achieving a balance between human-driven controls and system controls.
Our discussions also brought forward why trust should be the bedrock of technology adoption and that automation labs are what organizations should consider incorporating into their ecosystems to both fail and succeed more quickly.