No subject has animated the minds of technologists and business experts in the last decade more than "Digital Transformation." The term refers to the set of principles, processes, and technologies required to move an organization from analog to digital. It is a packed term because it implies a variety of things, including the notion that business and technology are quickly converging into a singularity. Indeed, modern organizations are built on technology-based chassis as they build products, provide services, and engage with the world. The business benefits of Digital Transformation are real.

Prepare for structural changes and ethical workplace transformation now by helping employees adjust to the role of machines in their jobs. The rise of powerful analytics and automated decision-making will ultimately create a massive change in roles and tasks that will redefine work. Leaders need to prepare for wide-scale change management now. The workforce of the future demands a new approach to business as usual-- one that is employee-centric and transparent. Establish clear enterprise-wide policies around the deployment of AI, including the use of data and privacy standards.

Prepare for structural changes and ethical workplace transformation now by helping employees adjust to the role of machines in their jobs – it's no secret that the workforce of the future calls for a new approach in business-- one that is totally employee-centric and transparent. The rise of powerful analytics and automated decision-making will ultimately create a massive change in roles and tasks that will redefine work. Establish clear enterprise-wide policies now about the deployment of AI, including the use of data and standards of privacy – Through GDPR regulation and the American AI Initiative we've seen that ultimately, the lead in educating, training, and managing the AI-enabled workforce rests with business--and the sooner leaders set forth on this journey, the more influence they will have on coming initiatives and regulations. Build algorithms that are secure and have a strong "ethical compass" – When creating algorithms to deploy AI responsibly, security and governance of the data is crucial to the overall integrity of the model, as well as establishing clear lines of ownership to generate accountability. Ensure the goal and purpose of critical algorithms are clearly defined and documented to mitigate bias – Every leader should have a moral imperative to mitigate bias by governing AI along its entire lifecycle--from its ideation and build to its continuing evolution--and then take new steps to manage and guide an increasingly diverse workforce as the nature of work changes.