“‘Digital transformation is less of a digital problem than it is a transformation problem,” said Westerman in a recent webinar for MIT Sloan Management Review. “It’s a leadership problem for envisioning and driving change.’
With consumers and organizations finally ready to embrace digital change at scale, how should companies leverage that shift to facilitate future transformation? Westerman identified four areas where companies should focus their next-generation digital initiatives:
“Human-centered design has a vital role across three key areas: Design thinking can help companies map their systems to understand how and where AI fits. Design is needed to devise better tools to create, monitor, and manage AI. And design must create new interfaces centered around the kind of information that AI delivers users.
Design can frame AI-driven user experiences to end users in a manner that engenders trust and helps the end user understand the scope, strengths, and weaknesses of a given system. In turn, fear and mistrust are alleviated around the mysterious black boxes.”
“AI in web design has come a long way and even got its own name, that’s artificial design intelligence (ADI).
The ADI design technology used by popular web design agencies across New York applies machine learning to recognize the client requirements and matches them with the existing market trends, helping the designers to create a design faster.
A CX maturity model follows the four major UX components – value, desirability, usability, and adaptability.”
“Consider the user experience early – Understanding how users will engage with your AI product at the start of model development can help to put useful guardrails on your AI project and ensure the team is focused on a shared end goal.
If we take the ‘”Recommended for You” section of a movie streaming service, for example, outlining what the user will see in this feature before kicking off data analysis will allow the team to focus only on model outputs that will add value. So if your user research determined the movie title, image, actors and length will be valuable information for the user to see in the recommendation, the engineering team would have important context when deciding which data sets should train the model. Actor and movie length data seem key to ensuring recommendations are accurate.”