It’s not a new revelation that data is constantly increasing in volume, velocity and variety of sources. Neither is the idea of robots carrying out tasks for us – after all, code has been executing commands for decades. What’s radically changing our world right now is the convergence of these elements with the growth of technology and increasing connectivity of devices, along with blockchain and the internet of trust.

As such a level of interaction, the stage is set for data analytics and artificial intelligence – guided by human intelligence – to tackle complex issues in fundamentally new ways.

Speaking at the Chief Data and Analytics Officer conference in Sydney, in this webcast PwC’s Chief Data Scientist Matt Kuperholz explains how AI is being used pragmatically to solve actual business problems.

Arguing that ‘practical AI’ is less about technology and more about process, he offers seven case studies to illustrate ways in which artificial intelligence has produced demonstrable and scalable business results. Including:

  • Oil companies selecting drilling sites.
  • A large bank seeking a better understanding of its customers.
  • Advertisers tracking market presence and effectiveness of spend.
  • Safety and incident prevention in mining and heavy industry.
  • The internet of things and leveraging predictive maintenance in a factory.
  • An airline, operating on antiquated systems, mining its booking data to power customer loyalty and marketing efforts.
  • Fraud detection for banks, insurers and gaming agencies.

The key to becoming truly analytically enabled, says Kuperholz, is not to start with a novel analytical or technical challenge but rather to start with a business challenge: one that’s meaningful, as well as carefully ranked and chosen. Then, to follow a process. Identify the challenge, engineer and analyse the data and make sure you deploy it effectively.

Watch Matt Kuperholz’s full CDAO 2017 presentation in the video below: