Companies around the world are adapting to new ways of doing business, with automation and artificial intelligence playing an important role amid the ongoing pandemic. These insights from MIT Sloan Management Review can help ensure digital transformation initiatives are successful while also resilient in the face of new disruption. As enterprises consider what digital transformation will look like after the pandemic, MIT Sloan senior lecturerGeorge Westermanencourages business leaders to leave behind their pre-pandemic assumptions about innovation. Instead, he said in a recent webinar, lean into how COVID-19 forced enterprises to change for the better. The collective response to the pandemic challenged longstanding notions about the efficiency of remote work, the agility of corporate IT departments, the rigidity of government regulators, and the willingness of customers to embrace (and pay for) digital interactions.

One of the great challenges we have seen businesses face in recent years is how they approach data and analytics (and now artificial intelligence) when their industries are undergoing major transformation. It's hard enough to create a data-driven culture, compete on analytics, develop data-driven products and services, and so forth under normal business conditions, as we noted in our March column about the newest NewVantage Partners survey on big data and AI. But doing it while your business and industry are transforming -- the old line of changing out a jet engine while the plane is flying through turbulence at 35,000 feet -- is really tough. It's so difficult, in fact, that we always have our doubts when executives claim to have done it successfully. We are much more trusting when we're told that the organization is simply making progress toward the goal.