In the 1800s, ice was king. Harvested from the frozen expanses of lakes and rivers, it was essential for food preservation, healthcare and comfort. But ice was expensive and innovators began to experiment with ice manufacturing machines.
In his seminal book "The Dynamics of Innovation," James M. Utterback surveys discontinuous technological change through history: ice, typewriters, lighting, imaging and glass manufacturing. What can this teach us about the impact of AI and how organisations should respond?
When ice manufacturers first felt the tremors of change, they responded by optimising their existing processes, using machines to augment and automate tasks done by workers to lower costs and improve quality.
As a consequence, the market for harvested ice grew to a peak in 1886. A success that obscured the proliferation of ice-manufacturing plants that made what the harvesters saw as an inferior product. But as we now know, initial faltering experiments with ice manufacturing eventually led to refrigeration and the death of the ice harvesting industry.
What can this teach us about AI? Is your organisation using AI to automate and augment what it already does? Or is it on the cusp of a more radical shift that redefines how customer needs are fulfilled?
We are in the foothills of the AI era, not at the peak. Organisations can wait and see what innovators do and try to follow fast, or they can experiment with new ways to fulfil customer needs. History shows that most large organisations will dabble, but others whose names we don’t yet know will overtake them. Amazon was a small startup online bookstore in the age of dial-up modems.
For larger organisations to survive, they must be gardeners and sow many different seeds. That means giving their people the skills, space and encouragement to run experiments and to see what grows and thrives. Most innovative businesses are created and grown through trial and error, not from a boardroom-defined strategy. In the AI era, a gardener's mindset is more important than ever.