AI has evolved significantly in the last few years with many organizations already strategically integrating it into their business model. With AI being accessible to businesses of all sizes, how can organizations put it into practice?

In theory, the power of AI and machine learning (ML) can make great things possible, but theory is not enough. To learn and realize the full merit of these technologies, they need to be tried and tested in an actual production environment.

A November 2019 survey by Gartner suggests that more organizations are moving towards an adaptable, change-ready culture, which is a positive sign.

Artificial intelligence is all around us.

Not so long ago, artificial intelligence (AI) existed only in the world of science fiction - but today, AI pervades our daily lives – whether we’re aware of it or not.  So much of what we do and the tools we use or dependent on data-driven analytics.

Take these examples:

Have you used a ride-sharing service (like Uber or Lyft) lately? These companies track millions of metrics each day, then employ machine learning (DL) and deep learning (DL) – both subsets of AI – to match drivers with riders, optimize routes, develop safety processes, and much more. 

Laundry time? Some washing machine manufacturers are introducing next-generation models controlled by apps – and those apps use AI to determine the best cycle for the type of clothes you’re washing, and also help with maintenance and troubleshooting to ensure your machine is operating to optimal results. 

In the healthcare space, one organization has trained and taught algorithms to augment the work of radiologists, allowing them to make diagnoses more accurately and efficiently.