UPS are replacing fixed daily routes with dynamic ones adjusted in real time for weather and traffic — again with machine learning. Only cognitive technologies can handle all the necessary data. And at some point supply chains may be powered by autonomously driven trucks, which will bring enormous changes to that domain.

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Defined simply, innovation is, of course, the introduction of something new. We presume that the purpose of introducing something new into a process is to bring about major, radical change. Process innovation combines a structure for doing work with an orientation to visible and dramatic results. It involves stepping back from a process to inquire into its overall business objective, and then effecting creative and radical change to realize order-of-magnitude improvements in the way that objective is accomplished.

We refer to these companies’ all-in approaches in multiple ways — “AI fueled,” “AI powered,” “AI enabled,” etc. The common thread is that they are at the far end of the scale in their spending, planning, strategizing, implementing, and changing with regard to AI technology.

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We believe that every large organization — and certainly those that are or aspire to be AI first — should designate smart people to follow AI technology trends, try out new technologies, and import them when they seem to fit the organization’s needs. These people don’t need to be fantastic data scientists or AI engineers, but they do need to understand the key technologies in AI and how they support use cases and business needs.

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In definitional terms, a process is simply a structured, measured set of activities designed to produce a specific output for a particular customer or market. It implies a strong emphasis on how work is done within an organization, in contrast to a product focus’s emphasis on what. A process is thus a specific ordering of work activities across time and space, with a beginning and an end, and clearly defined inputs and outputs: a structure for action.

The availability of all this data means that virtually every business or organizational activity can be viewed as a big data problem or initiative. Manufacturing, in which most machines already have one or more microprocessors, is increasingly a big-data environment. Consumer marketing, with myriad customer touchpoints and clickstreams, is already a big data problem. Google has even described its self-driving car as a big-data project.

Another AI-oriented company that has established several ecosystems — also in partnership with Palantir, in which it has made a substantial investment — is SOMPO Holdings, a large insurance and elder care company based in Japan. SOMPO

Peter Drucker wasn’t exaggerating when he noted that the fate of advanced economies depends on making knowledge workers more productive. There is no business or economic issue that is more important to our long-term competitiveness and standard of living.